Concomitants of Dual Generalized Order Statistics from Bivariate Burr III Distribution

Μέγεθος: px
Εμφάνιση ξεκινά από τη σελίδα:

Download "Concomitants of Dual Generalized Order Statistics from Bivariate Burr III Distribution"

Transcript

1 Journal of Statstcal Theory and Applcatons, Vol. 4, No. 3 September 5, 4-56 Concomtants of Dual Generalzed Order Statstcs from Bvarate Burr III Dstrbuton Haseeb Athar, Nayabuddn and Zuber Akhter Department of Statstcs & Operatons Research Algarh Muslm Unversty, Algarh -, Inda haseebathar@hotmal.com Receved 3 Aprl 4; Accepted March 5 In ths paper probablty densty functon of sngle concomtant and ont probablty densty functon of two concomtants of dual generalzed order statstcs from bvarate Burr III dstrbuton are obtaned and expressons for sngle and product moments are derved. Further, results are deduced for the order statstcs and lower record values. Keywords: Dual generalzed order statstcs; order statstcs; lower record values; concomtants; bvarate Burr III dstrbuton. Mathematcs Subect Classfcaton: 6G3.. Introducton The probablty densty functon pd f of bvarate Burr III dstrbuton [Rodrguez, 98] s gven as f x,y c c + α k x k + α k y k + + α x k + α y k c+, x,y >, k, k,c, α, α >. and the correspondng dstrbuton functon d f s Fx,y + α x k + α y k c, x,y >, k, k,c, α, α >.. The condtonal pd f of Y gven X s f y x c + α k y k+ + α x k c+ + α x k + α y k, y >..3 c+ The margnal pd f of X s f x c α k x k + { + α x k, x >..4 } c+ The margnal d f of X s Correspondng author 4

2 Haseeb Athar, Nayabuddn and Zuber Akhter Fx + α x k c, x >..5 Order statstcs, record values and several other model of ordered random varables can be vewed as specal case of generalzed order statstcs gos[kamps, 995]. Burkschat 3 ntroduced the concept of dual generalzed order statstcs dgos to enable a common approach to descendng ordered rv s lke reverse order statstcs and lower record values. Let X be a contnuous random varables wth d f Fx and the pd f f x, x α,β. Further, Let n N, k, m m,m,...,m n _ R n, M r n r m such that γ r k + n r + M r for all r,,...,n. Then X d r,n, m,k r,,...,n are called dgos f ther pd f s gven by [Burkschat et al. 3] k n γ n on the cone F > x x... x n > F. [ Fx ] m [Fxn f x ] k f xn.6 If m,,,...,n, k, then X d r,n,m,k reduces to the n r + th order statstcs, X n r+:n from the sample X,X,...,X n and at m, X d r,n,m,k reduces to r th, k lower record values. For more detals on order statstcs and record values, one may refer to Davd and Nagaraa 3 and Ahsanullah 4 respectvely. In vew of.6, the pd f of X d r,n,m,k s f r,n,m,k x and ont pd f of X d r,n,m,k and X d s,n,m,k, r < s n s f r,s,n,m,k x,y C r r! [Fx]γ r f xg r m Fx.7 C s r!s r! [Fx]m f x g r m Fx [h m Fy hm Fx ] s r [Fy] γ s f y, x > y.8 where C r r γ h m x m + xm+ logx, m, m and g m x h m x h m, x,. Let X,Y,,,...,n, be the n pars of ndependent random varables from some bvarate populaton wth dstrbuton functon Fx, y. If we arrange the X varates n descendng order as 4

3 Concomtants of Dual Generalzed Order Statstcs... X,n,m,k X,n,m,k... Xn,n,m,k then Y varates pared not necessarly n descendng order wth these dual generalzed ordered statstcs are called the concomtants of dual generalzed order statstcs and are denoted by Y [,n,m,k],y [,n,m,k],...,y [n,n,m,k]. The pd f of Y [r,n,m,k], the r th concomtant of dual generalzed order statstcs s gven as g [r,n,m,k] y and the ont pdf of Y [r,n,m,k] and Y [s,n,m,k], r < s n s g [r,s,n,m,k] y,y f y x f r,n,m,k x dx.9 x. Probablty Densty Functon of Y [r,n,m,k] f y x f y x f r,s,n,m,k x,x dx dx.. For the bvarate Burr III dstrbuton as gven n., the pd f of g [r,n,m,k] y n vew of.3,.4,.5,.7 and.9 s gven as r α k C r g [r,n,m,k] y r!m + r c c + y +k r α k x +k + α x k + α y k c+ + α x k dx.. cγ r Let t α x k, then the R.H.S. of. reduces to r α k C r r!m + r c c + y +k r Snce x v a + x µ x + y ρ dx where +t + α y k c+ +t cγr dt.. a, b F ; x a p b p x p c p c p p! s the Gauss hypergeometrc seres µ, v Γv Γµ v + ρ Γµ + ρ a µ y v ρ F ; y a.3 µ + ρ [ arg a < Π, Re v >, arg y < Π, Re ρ > Re v µ], Γλ + n λ n, λ,,,..., Γλ [Prudnkov et. al,986].5 s the Pochhammer symbol..4 4

4 Haseeb Athar, Nayabuddn and Zuber Akhter Therefore., becomes r α k C r g [r,n,m,k] y r!m + r c c + y +k r + α y k c+ cγ r + c γ r c, F ; α y k..6 c γ r + 3. Moment of Y [r,n,m,k] For the bvarate Burr III dstrbuton as gven n., the a th moment of Y [r,n,m,k] s gven as, E Y a [r,n,m,k] y a g [r,n,m,k] y dy 3. r α k C r r!m + r c c + r cγ r + c γ r c, y a y +k + α y k c+ F ; α y k dy 3. c γ r + r α k C r r!m + r c c + r cγ r + cγ r c p p y a y +k + α y k c+ α y k p dy. 3.3 p cγ r + p p! Now lettng t + α y k n 3.3, we get k α a r C r r r!m + r c c + cγ r + Snce p cγ r c p p p cγ r + p p! t c+ t p a k dt. 3.4 y x λ x y µ dx Γλ µ Γµ Γλ y µ λ, < Re µ < Re < λ 3.5 [c.f. Erdély et al., 954]. 43

5 Concomtants of Dual Generalzed Order Statstcs... Therefore R.H.S. of 3.4 becomes k α a r C r r!m + r c c + r cγ r + p cγ r c p p p cγ r + p p! Γc + a k p Γp + a k. 3.6 Γc + Now on applcaton of.5 and usng λ n n λ n, n,,3,..., λ, ±, ±,... [Srvastava and Karlsson,985] 3.7 n 3.6 and smplfyng, we get E Y a [r,n,m,k] k α a r C r r!m + r c c + r cγ r + p cγ r c p p a k p cγ r + p c a k p p! Γc + a k Γ a k. 3.8 Γc + We have the generalzed Gauss seres or the generalzed hypergeometrc seres. α... α p pf q,z β... β q k α k α k...α p k z k β k β k...β q k k!. 3.9 Thus applyng 3.9 n 3.8, we have E Y a [r,n,m,k] α a k C r c c + r!m + r r r cγ r + Γc + a k Γ a k Γc + cγ r c,, a k 3 F,. 3. cγ r +, c a k Notng that [prudnkov et al, 986] 44

6 Haseeb Athar, Nayabuddn and Zuber Akhter N,, a 3F, b, a m, m,, b b a m b + N a 3 F,. 3. b N, a, Now usng 3. n 3., we can wrte α k a c C r r!m + r r r Γc + a k Γ a k Γc + c + a k a k c,, cγ r 3 F,. 3. c, + a k, Usng relaton 3.9 n 3., we get α k a c C r r!m + r r r Γc + a k Γ a k Γc + c + a k a k, cγ r F ; a k Notng that [Prudnkov et al., 986]. a b F ; Γ c Γ c a b, Re c a b >, c, ±, ±,..., 3.4 Γ c a Γ c b c Applyng 3.4 n 3.3, we get 45

7 Concomtants of Dual Generalzed Order Statstcs... α k a C r r!m + r r r c + a k Γc + a k Γ a k c Γc γ r + a 3.5 c k α k a C r r!m + r r r c + a k Γc + a k Γ a k Γc + k a B + n r + + m + c k m +,. 3.6 Snce, b a a b Ba + k, c Bk, c + b 3.7 a where Ba,b s the complete beta functon. Therefore, E y a [r,n,m,k] α k a C r Γc + + a m + r k Γ a k c Γc Γ k+n rm++ a c k m+ Γ k+nm++ a c k m+ 3.8 E y a k [r,n,m,k] α a Γc + + a k Γ a k c Γc r + a c k γ. 3.9 Remark 3. : If m, k n 3., we get sngle moment of concomtants of order statstcs from bvarate Burr III dstrbuton as; E y a [n r+:n] n! n r! α k a Γc + + a k Γ a k c Γc Γn r + + a c k Γn + + a c k. If we replace n r + by r, then E y a [r:n] n! r! α a Γc + + a k k Γ a k c Γc Γr + a c k Γn + + a c k and at r n, we get 46

8 Haseeb Athar, Nayabuddn and Zuber Akhter E y a n [n:n] n c + a k α k a Γc + + a k Γ a k. 3. Γc It may be noted that for the order statstcs, the k th moments of Y [r:n] s µ [r:n] k n n y r r n r µ [:] k y. 3. Therefore, E y a [r:n] n r n r r c + a k α k a Γc + + a k Γ a k Γc 3. as obtaned by Begum and Khan,998. Remark 3. : Set m n 3., to get moment of k th lower record value from bvarate Burr III dstrbuton as; E y a [r,n,,k] α a k Γc + + a k Γ a k c Γc + a c k k r Jont Probablty Densty Functon of Y [r,n,m,k] and Y [s,n,m,k] For the bvarate Burr III dstrbuton as gven n., the ont pd f of Y [r,n,m,k] and Y [s,n,m,k] n vew of.3,.4,.5,.8 and. s gven as g [r,s,n,m,k] y,y C s r!s r!m + s c c + α k α k y +k y +k r s r + r s r where, x +k + α x k cs r+ m+ c + α x k + α y k Ix,y dx 4. c+ x Ix,y α k x +k + α x k cγ s Settng t + α x k, then the R.H.S. of 4. reduces to + α x k + α y k dx. 4. c+ 47

9 Concomtants of Dual Generalzed Order Statstcs... Ix,y λ β +α x k t α + t λ β dt 4.3 where α cγ s c, β c + and λ α y k Note that [Prudnkov et al., 986]. + z a p p a p z p. 4.4 p! Now n vew of 4.4, 4.3 after smplfcaton yelds Ix,y λ β l l β l λ l + α x k α l α l. 4.5 Now puttng the value of Ix,y from 4.5 n 4., we obtan g [r,s,n,m,k] y,y c c + α k α k C s r!s r!m + s y +k y +k r s r + r s r λ β l l α l β l λ l x +k + α x k cs r+ m+ c+cγ s c l Settng t + α x k n 4.6, and after smplfcaton we get + α x k + α y k dx. 4.6 c+ g [r,s,n,m,k] y,y C s r!s r!m + s c c + α k y +k y +k r s r + r s r λ β δ β l β l λ l α + l p β p δ p θ α + l + p p! 4.7 where δ α y k and θ cs r + m + c. 48

10 Haseeb Athar, Nayabuddn and Zuber Akhter By settng d α and g θ α n 4.7, we get c c + α k C s r!s r!m + s r s r + r s r y +k y +k λ β δ β l β l λ l d + l p β p δ p g + p + l p!. 4.8 Now after puttng the value of λ and δ n 4.8, we have c c + α k C s r!s r!m + s r s r + r s r y +k y +k α y k β α y k β l Notng that [Srvastava and Karlsson, 985]. l α y k β l d + l p β p p α y k g + p + l p! 4.9 λ + m λ λ + m λ m 4. λ + m + n λ λ + m+n λ m+n. 4. Usng relaton 4. and 4. n 4.9, t becomes c c + C s r!s r!m + s r s r + r s r dg α k y +k α k y α y k β α y k +k β l p p α y k g p+l β l d l β p g + p+l d + l We have the Kampede Feret s seres [Srvastava and Karlsson, 985] F p:q;k l:m;n a p : b q ; c k ; x,y α l β m γ n p! l α y k. 4. r s Therefore after usng 4.3, we fnally get p a r+s q b r k c s x r l α r+s m β r n γ s r! y s s!

11 Concomtants of Dual Generalzed Order Statstcs... g [r,s,n,m,k] y,y c c + C s r!s r!m + s r s r + r s r dg α k y +k α k y α y k β +k α y k F :; β :; g + ; d + ; g; β; d; β; ; α y k, α y k Product Moments of two concomtants Y [r,n,m,k] and Y [s,n,m,k] For Burr type III dstrbuton, the product Moments of two concomtants Y [r,n,m,k] and Y [s,n,m,k] s gven as E Y a [r,n,m,k] Y b [s,n,m,k] In vew of 4.4 and 5., we have y a y b g [r,s,n,m,k] y,y dy dy. 5. E Y a [r,n,m,k] Y b [s,n,m,k] A y a y b α k y +k α k y α y k β α y k +k β F :; :; g ; β ; d; β; ; g + ; d + ; α y k, α y k dy dy 5. where, Thus, A c c + C s r!s r!m + s r s r + r s r dg. 5.3 E Y a [r,n,m,k] Y b [s,n,m,k] A y a y b α k y +k α k y α y k β α y k +k β l p p α y k g p+l β l d l β p g + p+l d + l p! l α y k dy dy. 5.4 By Srvastava and Karlsson 985, we have 5

12 Haseeb Athar, Nayabuddn and Zuber Akhter λ m+n λ m λ + m n. 5.5 On applyng 5.5 n 5.4, we get A y b α k y +k α y k β l g l g + l β l d l l α y k d + l { y a α k y +k β p g + l p α y k β p A y b α k y +k α y k β l α y k g + + l p g l g + l β l d l p! p d + l y a α k y +k β; g + l α y k F β g + l + Now lettng α y k z n 5.7, we have dy } dy 5.6 l α y k ; α y k dy dy. 5.7 A α a k y b α k y +k α y k β l g l g + l β l d l l α y k d + l z β+ k a F β; g + l g + l + ; z dz dy 5.8 Snce a, b a, c b F ; x x a F c c ; x x. 5.9 Therefore on usng relaton 5.9 n 5., we have A α a k y b α k y +k α y k β l g l g + l β l d l l α y k d + l p β p { p g + l + p } z k a z β+p dz dy. 5. 5

13 Concomtants of Dual Generalzed Order Statstcs... Now usng relaton 3.5 n 5., we get A α a k g g + l Γβ + a k Γ a k Γβ y b α k y +k α y k β l l α y k β l d l d + l Now n vew of 3.4, 5. becomes β + a k ; F ; dy. 5. g + l + k α a g A Γβ + a k Γ a k { y b α k y +k } Γβ α y k dy β β l d l l l α y k d + l Usng relaton 4. n 5., we get g + β a k + l. 5. α a k A g g + β a k Γβ + a k Γ a k { Γβ y b α k y +k } α y k dy β β l d l g + β a k l l d + l α y k g + β a k l l. 5.3 Further settng z α y k n 5.3, t becomes α a+b k A g g + β a k Γβ + a k Γ a k Γβ z β+ b Set z t n 5.4, to get k 3 F d; g + β a k ; β d + ; g + β a k ; z dz. 5.4 α a+b k A g g + β a k Γβ + a k Γ a k Γβ 5

14 Haseeb Athar, Nayabuddn and Zuber Akhter d; g + β a t β+ k b k ; β 3 F ; t dz. 5.5 d + ; g + β a k Note that [Prudnkov et al., 986] a, a, a 3 x s 3F ; x dx b, b Γb Γb Γs Γa s Γa s Γa 3 s Γa Γa Γa 3 Γb s Γb s Now usng relatons 5.6 n 5.5, we get 5.6 α a+b k g A g + β a k b k d + β b k Γβ + a k Γ a k Γβ Γβ + b k Γ b k. 5.7 Γβ Fnally puttng the values of A, d, g and β n 5.7, we have E Y a [r,n,m,k] Y b [s,n,m,k] α a+b c c + C k s Γβ + a k Γ a k r! s r!m + s Γβ Γβ + b k Γ b k Γβ r s r r + s r [c{k + n s + m + } + b k ] [c{k + n r + m + } + a k + b k ] 5.8 α a+b k c c + C s Γβ + a k Γ a k r! s r!m + s Γβ Γβ + b k Γ b k r Γβ s r s r k b B + n s + + m + r k B + n r + + a m + + b ck m +, ck m +,

15 Concomtants of Dual Generalzed Order Statstcs... On usng relaton 3.7 n 5.9, we get α a+b k c + C s Γβ + a k Γ a k r! s r!m + s Γβ Γβ + b k Γ b k Γβ k B + n r + a + b m + ck m +, r k b B + n s + m + ck m +, s r, 5. whch after smplfcaton yelds E Y a [r,n,m,k] Y b [s,n,m,k] α a+b k c + Γβ + a k Γ a k Γβ Γβ + b k Γ b k Γβ r a+b + c k γ s r+ + b c k γ. 5. Remark 5. : By settng m, k n 5.8, we get product moments of concomtant of order statstcs from bvarate Burr III dstrbuton as E Y a [n s+:n] Y b [n r+:n] α a+b c c + n! k r! s r!n s! Γβ + b k Γ b k Γβ r Γβ + a k Γ a k. Γβ s r r + s r [cn s b k ] [cn r a k + b k ] 5. Replace n s + by r and n r + by s n 5., we get E Y a [r:n] Y b [s:n] α a+b c c + n! Γβ + a k k Γ a k r! s r!n s! Γβ Γβ + b k Γ b k Γβ n s s r n s + s r [cr + c + b k ] [cs + c + a k + b k ] 54

16 Haseeb Athar, Nayabuddn and Zuber Akhter E Y a [r:n] Y b [s:n] n! r! α a+b Γc + + a k k Γ a k Γc + + b k Γ b k Γc + Γr + b ck Γs + b ck as obtaned by Begum and Khan, 998. Γs + a+b ck Γn + + a+b ck Remark 5. : If m n 5., we get product moment of concomtants of k th lower record values from bvarate Burr III dstrbuton as E Y a [r,n,,k] Y b [s,n,,k] α a+b k c + Γβ + a k Γ a k Γβ Γβ + b k Γ b k Γβ + a+b c k k r + b s r. 5.3 c k k Puttng the value of β n 5., we get E Y a [r,n,,k] Y b [s,n,,k] α a+b Γc + + a k k Γ a k Γc + Γc + + b k Γ b k Γc + + a+b c k k r + b c k k s r 5.4 Acknowledgement The authors are thankful to Professor M. Ahsanullah, Rder Unversty, Lawrencevlle, NJ, USA for hs frutful suggestons. References [] Ahsanullah, M. 4: Record Values-Theory and Applcatons. Unversty Press of Amerca, Lanham, Maryland. [] Begum, A.A. and Khan, A.H. 998: Concomtants of order statstcs from bvarates Burr III dstrbuton. Journal of Statstcal Researh, 3, 5 5. [3] Burkschat, M.; Cramer, E. and Kamps, U. 3: Dual generalzed order statstcs. Metron, LXI, 3-6. [4] Davd, H. A. and Nagaraa, H. N. 3: Order Statstcs, John Wley, New York. [5] Erdély, A., Magnus, W., Oberhetnger, F. and Trcom, F. G.954: Tables of Integral Transforms. McGraw-Hll, New York. [6] Kamps, U. 995: A concept of generalzed order statstcs. B.G. Teubner Stuttgart, Germany. [7] Prudnkov, A. P., Brychkov, Yu. A. and Marchev, O. I. 986: Integral and seres: More Specal Functons Vol.3. Gordon and Breach Scence Publsher, New York. 55

17 Concomtants of Dual Generalzed Order Statstcs... [8] Rodrguez, R. N. 98: Burr dstrbutons: Encyclopeda of Statstcal Scence. Vol., Kotz and Johnson, ed., John Wley and Sons, New York. [9] Srvastava, H. M. and Karlsson 985: Multple Gaussan Hypergeometrc seres. John Wley & Sons, New York. 56

Concomitants of generalized order statistics from bivariate Lomax distribution

Concomitants of generalized order statistics from bivariate Lomax distribution ProbStat Forum, Volume 6, October 23, Pages 73 88 ISSN 974-3235 ProbStat Forum s an e-ournal. For detals please vst www.probstat.org.n Concomtants of generalzed order statstcs from bvarate Lomax dstrbuton

Διαβάστε περισσότερα

Generalized Fibonacci-Like Polynomial and its. Determinantal Identities

Generalized Fibonacci-Like Polynomial and its. Determinantal Identities Int. J. Contemp. Math. Scences, Vol. 7, 01, no. 9, 1415-140 Generalzed Fbonacc-Le Polynomal and ts Determnantal Identtes V. K. Gupta 1, Yashwant K. Panwar and Ompraash Shwal 3 1 Department of Mathematcs,

Διαβάστε περισσότερα

One and two particle density matrices for single determinant HF wavefunctions. (1) = φ 2. )β(1) ( ) ) + β(1)β * β. (1)ρ RHF

One and two particle density matrices for single determinant HF wavefunctions. (1) = φ 2. )β(1) ( ) ) + β(1)β * β. (1)ρ RHF One and two partcle densty matrces for sngle determnant HF wavefunctons One partcle densty matrx Gven the Hartree-Fock wavefuncton ψ (,,3,!, = Âϕ (ϕ (ϕ (3!ϕ ( 3 The electronc energy s ψ H ψ = ϕ ( f ( ϕ

Διαβάστε περισσότερα

5 Haar, R. Haar,. Antonads 994, Dogaru & Carn Kerkyacharan & Pcard 996. : Haar. Haar, y r x f rt xβ r + ε r x β r + mr k β r k ψ kx + ε r x, r,.. x [,

5 Haar, R. Haar,. Antonads 994, Dogaru & Carn Kerkyacharan & Pcard 996. : Haar. Haar, y r x f rt xβ r + ε r x β r + mr k β r k ψ kx + ε r x, r,.. x [, 4 Chnese Journal of Appled Probablty and Statstcs Vol.6 No. Apr. Haar,, 6,, 34 E-,,, 34 Haar.., D-, A- Q-,. :, Haar,. : O.6..,..,.. Herzberg & Traves 994, Oyet & Wens, Oyet Tan & Herzberg 6, 7. Haar Haar.,

Διαβάστε περισσότερα

Multi-dimensional Central Limit Theorem

Multi-dimensional Central Limit Theorem Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t tme

Διαβάστε περισσότερα

Multi-dimensional Central Limit Theorem

Multi-dimensional Central Limit Theorem Mult-dmensonal Central Lmt heorem Outlne () () () t as () + () + + () () () Consder a sequence of ndependent random proceses t, t, dentcal to some ( t). Assume t 0. Defne the sum process t t t t () t ();

Διαβάστε περισσότερα

Variance of Trait in an Inbred Population. Variance of Trait in an Inbred Population

Variance of Trait in an Inbred Population. Variance of Trait in an Inbred Population Varance of Trat n an Inbred Populaton Varance of Trat n an Inbred Populaton Varance of Trat n an Inbred Populaton Revew of Mean Trat Value n Inbred Populatons We showed n the last lecture that for a populaton

Διαβάστε περισσότερα

Matrices and Determinants

Matrices and Determinants Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z

Διαβάστε περισσότερα

A summation formula ramified with hypergeometric function and involving recurrence relation

A summation formula ramified with hypergeometric function and involving recurrence relation South Asian Journal of Mathematics 017, Vol. 7 ( 1): 1 4 www.sajm-online.com ISSN 51-151 RESEARCH ARTICLE A summation formula ramified with hypergeometric function and involving recurrence relation Salahuddin

Διαβάστε περισσότερα

A Class of Orthohomological Triangles

A Class of Orthohomological Triangles A Class of Orthohomologcal Trangles Prof. Claudu Coandă Natonal College Carol I Craova Romana. Prof. Florentn Smarandache Unversty of New Mexco Gallup USA Prof. Ion Pătraşcu Natonal College Fraţ Buzeşt

Διαβάστε περισσότερα

α & β spatial orbitals in

α & β spatial orbitals in The atrx Hartree-Fock equatons The most common method of solvng the Hartree-Fock equatons f the spatal btals s to expand them n terms of known functons, { χ µ } µ= consder the spn-unrestrcted case. We

Διαβάστε περισσότερα

Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών. ΗΥ-570: Στατιστική Επεξεργασία Σήµατος. ιδάσκων : Α. Μουχτάρης. εύτερη Σειρά Ασκήσεων.

Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών. ΗΥ-570: Στατιστική Επεξεργασία Σήµατος. ιδάσκων : Α. Μουχτάρης. εύτερη Σειρά Ασκήσεων. Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 2015 ιδάσκων : Α. Μουχτάρης εύτερη Σειρά Ασκήσεων Λύσεις Ασκηση 1. 1. Consder the gven expresson for R 1/2 : R 1/2

Διαβάστε περισσότερα

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit Ting Zhang Stanford May 11, 2001 Stanford, 5/11/2001 1 Outline Ordinal Classification Ordinal Addition Ordinal Multiplication Ordinal

Διαβάστε περισσότερα

C.S. 430 Assignment 6, Sample Solutions

C.S. 430 Assignment 6, Sample Solutions C.S. 430 Assignment 6, Sample Solutions Paul Liu November 15, 2007 Note that these are sample solutions only; in many cases there were many acceptable answers. 1 Reynolds Problem 10.1 1.1 Normal-order

Διαβάστε περισσότερα

ST5224: Advanced Statistical Theory II

ST5224: Advanced Statistical Theory II ST5224: Advanced Statistical Theory II 2014/2015: Semester II Tutorial 7 1. Let X be a sample from a population P and consider testing hypotheses H 0 : P = P 0 versus H 1 : P = P 1, where P j is a known

Διαβάστε περισσότερα

Solution Series 9. i=1 x i and i=1 x i.

Solution Series 9. i=1 x i and i=1 x i. Lecturer: Prof. Dr. Mete SONER Coordinator: Yilin WANG Solution Series 9 Q1. Let α, β >, the p.d.f. of a beta distribution with parameters α and β is { Γ(α+β) Γ(α)Γ(β) f(x α, β) xα 1 (1 x) β 1 for < x

Διαβάστε περισσότερα

Commutative Monoids in Intuitionistic Fuzzy Sets

Commutative Monoids in Intuitionistic Fuzzy Sets Commutative Monoids in Intuitionistic Fuzzy Sets S K Mala #1, Dr. MM Shanmugapriya *2 1 PhD Scholar in Mathematics, Karpagam University, Coimbatore, Tamilnadu- 641021 Assistant Professor of Mathematics,

Διαβάστε περισσότερα

EE512: Error Control Coding

EE512: Error Control Coding EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3

Διαβάστε περισσότερα

SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018

SCITECH Volume 13, Issue 2 RESEARCH ORGANISATION Published online: March 29, 2018 Journal of rogressive Research in Mathematics(JRM) ISSN: 2395-028 SCITECH Volume 3, Issue 2 RESEARCH ORGANISATION ublished online: March 29, 208 Journal of rogressive Research in Mathematics www.scitecresearch.com/journals

Διαβάστε περισσότερα

Some generalization of Cauchy s and Wilson s functional equations on abelian groups

Some generalization of Cauchy s and Wilson s functional equations on abelian groups Aequat. Math. 89 (2015), 591 603 c The Author(s) 2013. Ths artcle s publshed wth open access at Sprngerlnk.com 0001-9054/15/030591-13 publshed onlne December 6, 2013 DOI 10.1007/s00010-013-0244-4 Aequatones

Διαβάστε περισσότερα

k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R +

k A = [k, k]( )[a 1, a 2 ] = [ka 1,ka 2 ] 4For the division of two intervals of confidence in R + Chapter 3. Fuzzy Arithmetic 3- Fuzzy arithmetic: ~Addition(+) and subtraction (-): Let A = [a and B = [b, b in R If x [a and y [b, b than x+y [a +b +b Symbolically,we write A(+)B = [a (+)[b, b = [a +b

Διαβάστε περισσότερα

An Inventory of Continuous Distributions

An Inventory of Continuous Distributions Appendi A An Inventory of Continuous Distributions A.1 Introduction The incomplete gamma function is given by Also, define Γ(α; ) = 1 with = G(α; ) = Z 0 Z 0 Z t α 1 e t dt, α > 0, >0 t α 1 e t dt, α >

Διαβάστε περισσότερα

Statistical Inference I Locally most powerful tests

Statistical Inference I Locally most powerful tests Statistical Inference I Locally most powerful tests Shirsendu Mukherjee Department of Statistics, Asutosh College, Kolkata, India. shirsendu st@yahoo.co.in So far we have treated the testing of one-sided

Διαβάστε περισσότερα

LECTURE 4 : ARMA PROCESSES

LECTURE 4 : ARMA PROCESSES LECTURE 4 : ARMA PROCESSES Movng-Average Processes The MA(q) process, s defned by (53) y(t) =µ ε(t)+µ 1 ε(t 1) + +µ q ε(t q) =µ(l)ε(t), where µ(l) =µ +µ 1 L+ +µ q L q and where ε(t) s whte nose An MA model

Διαβάστε περισσότερα

Homomorphism of Intuitionistic Fuzzy Groups

Homomorphism of Intuitionistic Fuzzy Groups International Mathematical Forum, Vol. 6, 20, no. 64, 369-378 Homomorphism o Intuitionistic Fuzz Groups P. K. Sharma Department o Mathematics, D..V. College Jalandhar Cit, Punjab, India pksharma@davjalandhar.com

Διαβάστε περισσότερα

ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =?

ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =? Teko Classes IITJEE/AIEEE Maths by SUHAAG SIR, Bhopal, Ph (0755) 3 00 000 www.tekoclasses.com ANSWERSHEET (TOPIC DIFFERENTIAL CALCULUS) COLLECTION # Question Type A.Single Correct Type Q. (A) Sol least

Διαβάστε περισσότερα

Second Order Partial Differential Equations

Second Order Partial Differential Equations Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y

Διαβάστε περισσότερα

6.1. Dirac Equation. Hamiltonian. Dirac Eq.

6.1. Dirac Equation. Hamiltonian. Dirac Eq. 6.1. Dirac Equation Ref: M.Kaku, Quantum Field Theory, Oxford Univ Press (1993) η μν = η μν = diag(1, -1, -1, -1) p 0 = p 0 p = p i = -p i p μ p μ = p 0 p 0 + p i p i = E c 2 - p 2 = (m c) 2 H = c p 2

Διαβάστε περισσότερα

Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------

Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- ----------------- Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin

Διαβάστε περισσότερα

Neutralino contributions to Dark Matter, LHC and future Linear Collider searches

Neutralino contributions to Dark Matter, LHC and future Linear Collider searches Neutralno contrbutons to Dark Matter, LHC and future Lnear Collder searches G.J. Gounars Unversty of Thessalonk, Collaboraton wth J. Layssac, P.I. Porfyrads, F.M. Renard and wth Th. Dakonds for the γz

Διαβάστε περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr T t N n) Pr max X 1,..., X N ) t N n) Pr max

Διαβάστε περισσότερα

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.

Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ. Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο The time integral of a force is referred to as impulse, is determined by and is obtained from: Newton s 2 nd Law of motion states that the action

Διαβάστε περισσότερα

Homework 8 Model Solution Section

Homework 8 Model Solution Section MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx

Διαβάστε περισσότερα

ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ

ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΜΕΡΟΣ ΙΙΙ ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΓΕΝΙΚΕΣ ΠΑΡΑΤΗΡΗΣΕΙΣ ΕΠΙΔΡΑΣΗ Μ.Β ΣΤΙΣ ΙΔΙΟΤΗΤΕΣ ΠΟΛΥΜΕΡΩΝ ΜΑΘΗΜΑΤΙΚΗ ΠΕΡΙΓΡΑΦΗ ΤΗΣ ΚΑΤΑΝΟΜΗΣ ΜΟΡΙΑΚΟΥ ΒΑΡΟΥΣ ΣΥΝΑΡΤΗΣΗ ΠΙΘΑΝΟΤΗΤΟΣ (ΔΙΑΦΟΡΙΚΗ) Probablty Densty Functon

Διαβάστε περισσότερα

Supplementary materials for Statistical Estimation and Testing via the Sorted l 1 Norm

Supplementary materials for Statistical Estimation and Testing via the Sorted l 1 Norm Sulementary materals for Statstcal Estmaton and Testng va the Sorted l Norm Małgorzata Bogdan * Ewout van den Berg Weje Su Emmanuel J. Candès October 03 Abstract In ths note we gve a roof showng that even

Διαβάστε περισσότερα

The one-dimensional periodic Schrödinger equation

The one-dimensional periodic Schrödinger equation The one-dmensonal perodc Schrödnger equaon Jordan Bell jordan.bell@gmal.com Deparmen of Mahemacs, Unversy of Torono Aprl 23, 26 Translaons and convoluon For y, le τ y f(x f(x y. To say ha f : C s unformly

Διαβάστε περισσότερα

8.324 Relativistic Quantum Field Theory II

8.324 Relativistic Quantum Field Theory II Lecture 8.3 Relatvstc Quantum Feld Theory II Fall 00 8.3 Relatvstc Quantum Feld Theory II MIT OpenCourseWare Lecture Notes Hon Lu, Fall 00 Lecture 5.: RENORMALIZATION GROUP FLOW Consder the bare acton

Διαβάστε περισσότερα

Other Test Constructions: Likelihood Ratio & Bayes Tests

Other Test Constructions: Likelihood Ratio & Bayes Tests Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :

Διαβάστε περισσότερα

Vidyamandir Classes. Solutions to Revision Test Series - 2/ ACEG / IITJEE (Mathematics) = 2 centre = r. a

Vidyamandir Classes. Solutions to Revision Test Series - 2/ ACEG / IITJEE (Mathematics) = 2 centre = r. a Per -.(D).() Vdymndr lsses Solutons to evson est Seres - / EG / JEE - (Mthemtcs) Let nd re dmetrcl ends of crcle Let nd D re dmetrcl ends of crcle Hence mnmum dstnce s. y + 4 + 4 6 Let verte (h, k) then

Διαβάστε περισσότερα

SPECIAL FUNCTIONS and POLYNOMIALS

SPECIAL FUNCTIONS and POLYNOMIALS SPECIAL FUNCTIONS and POLYNOMIALS Gerard t Hooft Stefan Nobbenhuis Institute for Theoretical Physics Utrecht University, Leuvenlaan 4 3584 CC Utrecht, the Netherlands and Spinoza Institute Postbox 8.195

Διαβάστε περισσότερα

Math221: HW# 1 solutions

Math221: HW# 1 solutions Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin

Διαβάστε περισσότερα

ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ

ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΜΕΡΟΣ ΙΙI ΜΟΡΙΑΚΟ ΒΑΡΟΣ ΠΟΛΥΜΕΡΩΝ ΓΕΝΙΚΕΣ ΠΑΡΑΤΗΡΗΣΕΙΣ ΕΠΙ ΡΑΣΗ Μ.Β ΣΤΙΣ Ι ΙΟΤΗΤΕΣ ΠΟΛΥΜΕΡΩΝ ΜΑΘΗΜΑΤΙΚΗ ΠΕΡΙΓΡΑΦΗ ΤΗΣ ΚΑΤΑΝΟΜΗΣ ΜΟΡΙΑΚΟΥ ΒΑΡΟΥΣ ΣΥΝΑΡΤΗΣΗ ΠΙΘΑΝΟΤΗΤΟΣ ( ΙΑΦΟΡΙΚΗ) Probablty Densty Functon

Διαβάστε περισσότερα

ΠΤΥΧΙΑΚΗ/ ΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ

ΠΤΥΧΙΑΚΗ/ ΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ ΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΣΧΟΛΗ ΘΕΤΙΚΩΝ ΕΠΙΣΤΗΜΩΝ ΤΜΗΜΑ ΠΛΗΡΟΦΟΡΙΚΗΣ ΠΤΥΧΙΑΚΗ/ ΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ «ΚΛΑ ΕΜΑ ΟΜΑ ΑΣ ΚΑΤΑ ΠΕΡΙΠΤΩΣΗ ΜΕΣΩ ΤΑΞΙΝΟΜΗΣΗΣ ΠΟΛΛΑΠΛΩΝ ΕΤΙΚΕΤΩΝ» (Instance-Based Ensemble

Διαβάστε περισσότερα

The k-α-exponential Function

The k-α-exponential Function Int Journal of Math Analysis, Vol 7, 213, no 11, 535-542 The --Exponential Function Luciano L Luque and Rubén A Cerutti Faculty of Exact Sciences National University of Nordeste Av Libertad 554 34 Corrientes,

Διαβάστε περισσότερα

2. THEORY OF EQUATIONS. PREVIOUS EAMCET Bits.

2. THEORY OF EQUATIONS. PREVIOUS EAMCET Bits. EAMCET-. THEORY OF EQUATIONS PREVIOUS EAMCET Bits. Each of the roots of the equation x 6x + 6x 5= are increased by k so that the new transformed equation does not contain term. Then k =... - 4. - Sol.

Διαβάστε περισσότερα

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics

Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics Fourier Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Not all functions can be represented by Taylor series. f (k) (c) A Taylor series f (x) = (x c)

Διαβάστε περισσότερα

2 Composition. Invertible Mappings

2 Composition. Invertible Mappings Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,

Διαβάστε περισσότερα

8.1 The Nature of Heteroskedasticity 8.2 Using the Least Squares Estimator 8.3 The Generalized Least Squares Estimator 8.

8.1 The Nature of Heteroskedasticity 8.2 Using the Least Squares Estimator 8.3 The Generalized Least Squares Estimator 8. 8.1 The Nature of Heteroskedastcty 8. Usng the Least Squares Estmator 8.3 The Generalzed Least Squares Estmator 8.4 Detectng Heteroskedastcty E( y) = β+β 1 x e = y E( y ) = y β β x 1 y = β+β x + e 1 Fgure

Διαβάστε περισσότερα

Some Theorems on Multiple. A-Function Transform

Some Theorems on Multiple. A-Function Transform Int. J. Contemp. Math. Scences, Vol. 7, 202, no. 20, 995-004 Some Theoems on Multple A-Functon Tansfom Pathma J SCSVMV Deemed Unvesty,Kanchpuam, Tamlnadu, Inda & Dept.of Mathematcs, Manpal Insttute of

Διαβάστε περισσότερα

4.6 Autoregressive Moving Average Model ARMA(1,1)

4.6 Autoregressive Moving Average Model ARMA(1,1) 84 CHAPTER 4. STATIONARY TS MODELS 4.6 Autoregressive Moving Average Model ARMA(,) This section is an introduction to a wide class of models ARMA(p,q) which we will consider in more detail later in this

Διαβάστε περισσότερα

ON NEGATIVE MOMENTS OF CERTAIN DISCRETE DISTRIBUTIONS

ON NEGATIVE MOMENTS OF CERTAIN DISCRETE DISTRIBUTIONS Pa J Statist 2009 Vol 25(2), 135-140 ON NEGTIVE MOMENTS OF CERTIN DISCRETE DISTRIBUTIONS Masood nwar 1 and Munir hmad 2 1 Department of Maematics, COMSTS Institute of Information Technology, Islamabad,

Διαβάστε περισσότερα

Answers - Worksheet A ALGEBRA PMT. 1 a = 7 b = 11 c = 1 3. e = 0.1 f = 0.3 g = 2 h = 10 i = 3 j = d = k = 3 1. = 1 or 0.5 l =

Answers - Worksheet A ALGEBRA PMT. 1 a = 7 b = 11 c = 1 3. e = 0.1 f = 0.3 g = 2 h = 10 i = 3 j = d = k = 3 1. = 1 or 0.5 l = C ALGEBRA Answers - Worksheet A a 7 b c d e 0. f 0. g h 0 i j k 6 8 or 0. l or 8 a 7 b 0 c 7 d 6 e f g 6 h 8 8 i 6 j k 6 l a 9 b c d 9 7 e 00 0 f 8 9 a b 7 7 c 6 d 9 e 6 6 f 6 8 g 9 h 0 0 i j 6 7 7 k 9

Διαβάστε περισσότερα

Example Sheet 3 Solutions

Example Sheet 3 Solutions Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note

Διαβάστε περισσότερα

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =

Διαβάστε περισσότερα

Trigonometry 1.TRIGONOMETRIC RATIOS

Trigonometry 1.TRIGONOMETRIC RATIOS Trigonometry.TRIGONOMETRIC RATIOS. If a ray OP makes an angle with the positive direction of X-axis then y x i) Sin ii) cos r r iii) tan x y (x 0) iv) cot y x (y 0) y P v) sec x r (x 0) vi) cosec y r (y

Διαβάστε περισσότερα

Solutions to Exercise Sheet 5

Solutions to Exercise Sheet 5 Solutions to Eercise Sheet 5 jacques@ucsd.edu. Let X and Y be random variables with joint pdf f(, y) = 3y( + y) where and y. Determine each of the following probabilities. Solutions. a. P (X ). b. P (X

Διαβάστε περισσότερα

b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!

b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds! MTH U341 urface Integrals, tokes theorem, the divergence theorem To be turned in Wed., Dec. 1. 1. Let be the sphere of radius a, x 2 + y 2 + z 2 a 2. a. Use spherical coordinates (with ρ a) to parametrize.

Διαβάστε περισσότερα

Aquinas College. Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET

Aquinas College. Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET Aquinas College Edexcel Mathematical formulae and statistics tables DO NOT WRITE ON THIS BOOKLET Pearson Edexcel Level 3 Advanced Subsidiary and Advanced GCE in Mathematics and Further Mathematics Mathematical

Διαβάστε περισσότερα

On the k-bessel Functions

On the k-bessel Functions International Mathematical Forum, Vol. 7, 01, no. 38, 1851-1857 On the k-bessel Functions Ruben Alejandro Cerutti Faculty of Exact Sciences National University of Nordeste. Avda. Libertad 5540 (3400) Corrientes,

Διαβάστε περισσότερα

derivation of the Laplacian from rectangular to spherical coordinates

derivation of the Laplacian from rectangular to spherical coordinates derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used

Διαβάστε περισσότερα

Solutions to Selected Homework Problems 1.26 Claim: α : S S which is 1-1 but not onto β : S S which is onto but not 1-1. y z = z y y, z S.

Solutions to Selected Homework Problems 1.26 Claim: α : S S which is 1-1 but not onto β : S S which is onto but not 1-1. y z = z y y, z S. Solutions to Selected Homework Problems 1.26 Claim: α : S S which is 1-1 but not onto β : S S which is onto but not 1-1. Proof. ( ) Since α is 1-1, β : S S such that β α = id S. Since β α = id S is onto,

Διαβάστε περισσότερα

Constant Elasticity of Substitution in Applied General Equilibrium

Constant Elasticity of Substitution in Applied General Equilibrium Constant Elastct of Substtuton n Appled General Equlbru The choce of nput levels that nze the cost of producton for an set of nput prces and a fed level of producton can be epressed as n sty.. f Ltng for

Διαβάστε περισσότερα

THE SECOND WEIGHTED MOMENT OF ζ. S. Bettin & J.B. Conrey

THE SECOND WEIGHTED MOMENT OF ζ. S. Bettin & J.B. Conrey THE SECOND WEIGHTED MOMENT OF ζ by S. Bettn & J.B. Conrey Abstract. We gve an explct formula for the second weghted moment of ζs) on the crtcal lne talored for fast computatons wth any desred accuracy.

Διαβάστε περισσότερα

On Generating Relations of Some Triple. Hypergeometric Functions

On Generating Relations of Some Triple. Hypergeometric Functions It. Joural of Math. Aalysis, Vol. 5,, o., 5 - O Geeratig Relatios of Some Triple Hypergeometric Fuctios Fadhle B. F. Mohse ad Gamal A. Qashash Departmet of Mathematics, Faculty of Educatio Zigibar Ade

Διαβάστε περισσότερα

Finite Field Problems: Solutions

Finite Field Problems: Solutions Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The

Διαβάστε περισσότερα

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions

SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions SCHOOL OF MATHEMATICAL SCIENCES GLMA Linear Mathematics 00- Examination Solutions. (a) i. ( + 5i)( i) = (6 + 5) + (5 )i = + i. Real part is, imaginary part is. (b) ii. + 5i i ( + 5i)( + i) = ( i)( + i)

Διαβάστε περισσότερα

Generalized Linear Model [GLM]

Generalized Linear Model [GLM] Generalzed Lnear Model [GLM]. ก. ก Emal: nkom@kku.ac.th A Lttle Hstory Multple lnear regresson normal dstrbuton & dentty lnk (Legendre, Guass: early 19th century). ANOVA normal dstrbuton & dentty lnk (Fsher:

Διαβάστε περισσότερα

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.

Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1. Exercises 0 More exercises are available in Elementary Differential Equations. If you have a problem to solve any of them, feel free to come to office hour. Problem Find a fundamental matrix of the given

Διαβάστε περισσότερα

2 Lagrangian and Green functions in d dimensions

2 Lagrangian and Green functions in d dimensions Renormalzaton of φ scalar feld theory December 6 Pdf fle generated on February 7, 8. TODO Examne ε n the two-pont functon cf Sterman. Lagrangan and Green functons n d dmensons In these notes, we ll use

Διαβάστε περισσότερα

Vol. 34 ( 2014 ) No. 4. J. of Math. (PRC) : A : (2014) Frank-Wolfe [7],. Frank-Wolfe, ( ).

Vol. 34 ( 2014 ) No. 4. J. of Math. (PRC) : A : (2014) Frank-Wolfe [7],. Frank-Wolfe, ( ). Vol. 4 ( 214 ) No. 4 J. of Math. (PRC) 1,2, 1 (1., 472) (2., 714) :.,.,,,..,. : ; ; ; MR(21) : 9B2 : : A : 255-7797(214)4-759-7 1,,,,, [1 ].,, [4 6],, Frank-Wolfe, Frank-Wolfe [7],.,,.,,,., UE,, UE. O-D,,,,,

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

Areas and Lengths in Polar Coordinates Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the

Διαβάστε περισσότερα

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8 questions or comments to Dan Fetter 1

Econ 2110: Fall 2008 Suggested Solutions to Problem Set 8  questions or comments to Dan Fetter 1 Eon : Fall 8 Suggested Solutions to Problem Set 8 Email questions or omments to Dan Fetter Problem. Let X be a salar with density f(x, θ) (θx + θ) [ x ] with θ. (a) Find the most powerful level α test

Διαβάστε περισσότερα

1 Complete Set of Grassmann States

1 Complete Set of Grassmann States Physcs 610 Homework 8 Solutons 1 Complete Set of Grassmann States For Θ, Θ, Θ, Θ each ndependent n-member sets of Grassmann varables, and usng the summaton conventon ΘΘ Θ Θ Θ Θ, prove the dentty e ΘΘ dθ

Διαβάστε περισσότερα

6.3 Forecasting ARMA processes

6.3 Forecasting ARMA processes 122 CHAPTER 6. ARMA MODELS 6.3 Forecasting ARMA processes The purpose of forecasting is to predict future values of a TS based on the data collected to the present. In this section we will discuss a linear

Διαβάστε περισσότερα

Section 8.3 Trigonometric Equations

Section 8.3 Trigonometric Equations 99 Section 8. Trigonometric Equations Objective 1: Solve Equations Involving One Trigonometric Function. In this section and the next, we will exple how to solving equations involving trigonometric functions.

Διαβάστε περισσότερα

The Simply Typed Lambda Calculus

The Simply Typed Lambda Calculus Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and

Διαβάστε περισσότερα

SOLVING CUBICS AND QUARTICS BY RADICALS

SOLVING CUBICS AND QUARTICS BY RADICALS SOLVING CUBICS AND QUARTICS BY RADICALS The purpose of this handout is to record the classical formulas expressing the roots of degree three and degree four polynomials in terms of radicals. We begin with

Διαβάστε περισσότερα

Modelling Lifetime Dependence for Older Ages using a Multivariate Pareto Distribution

Modelling Lifetime Dependence for Older Ages using a Multivariate Pareto Distribution Modellng Lfetme Dependence for Older Ages usng a Multvarate Pareto Dstrbuton Danel H Ala Znovy Landsman Mchael Sherrs 3 School of Mathematcs, Statstcs and Actuaral Scence Unversty of Kent, Canterbury,

Διαβάστε περισσότερα

Partial Differential Equations in Biology The boundary element method. March 26, 2013

Partial Differential Equations in Biology The boundary element method. March 26, 2013 The boundary element method March 26, 203 Introduction and notation The problem: u = f in D R d u = ϕ in Γ D u n = g on Γ N, where D = Γ D Γ N, Γ D Γ N = (possibly, Γ D = [Neumann problem] or Γ N = [Dirichlet

Διαβάστε περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM Solutions to Question 1 a) The cumulative distribution function of T conditional on N n is Pr (T t N n) Pr (max (X 1,..., X N ) t N n) Pr (max

Διαβάστε περισσότερα

ΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα,

ΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα, ΗΥ537: Έλεγχος Πόρων και Επίδοση σε Ευρυζωνικά Δίκτυα Βασίλειος Σύρης Τμήμα Επιστήμης Υπολογιστών Πανεπιστήμιο Κρήτης Εαρινό εξάμηνο 2008 Economcs Contents The contet The basc model user utlty, rces and

Διαβάστε περισσότερα

CAPM. VaR Value at Risk. VaR. RAROC Risk-Adjusted Return on Capital

CAPM. VaR Value at Risk. VaR. RAROC Risk-Adjusted Return on Capital C RAM 3002 C RAROC Rsk-Adjusted Return on Captal C C RAM Rsk-Adjusted erformance Measure C RAM RAM Bootstrap RAM C RAROC RAM Bootstrap F830.9 A CAM 2 CAM 3 Value at Rsk RAROC Rsk-Adjusted Return on Captal

Διαβάστε περισσότερα

Statistics 104: Quantitative Methods for Economics Formula and Theorem Review

Statistics 104: Quantitative Methods for Economics Formula and Theorem Review Harvard College Statistics 104: Quantitative Methods for Economics Formula and Theorem Review Tommy MacWilliam, 13 tmacwilliam@college.harvard.edu March 10, 2011 Contents 1 Introduction to Data 5 1.1 Sample

Διαβάστε περισσότερα

Quadratic Expressions

Quadratic Expressions Quadratic Expressions. The standard form of a quadratic equation is ax + bx + c = 0 where a, b, c R and a 0. The roots of ax + bx + c = 0 are b ± b a 4ac. 3. For the equation ax +bx+c = 0, sum of the roots

Διαβάστε περισσότερα

IIT JEE (2013) (Trigonomtery 1) Solutions

IIT JEE (2013) (Trigonomtery 1) Solutions L.K. Gupta (Mathematic Classes) www.pioeermathematics.com MOBILE: 985577, 677 (+) PAPER B IIT JEE (0) (Trigoomtery ) Solutios TOWARDS IIT JEE IS NOT A JOURNEY, IT S A BATTLE, ONLY THE TOUGHEST WILL SURVIVE

Διαβάστε περισσότερα

Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee

Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee Appendi to On the stability of a compressible aisymmetric rotating flow in a pipe By Z. Rusak & J. H. Lee Journal of Fluid Mechanics, vol. 5 4, pp. 5 4 This material has not been copy-edited or typeset

Διαβάστε περισσότερα

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β

3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β 3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle

Διαβάστε περισσότερα

Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3

Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 1 State vector space and the dual space Space of wavefunctions The space of wavefunctions is the set of all

Διαβάστε περισσότερα

DiracDelta. Notations. Primary definition. Specific values. General characteristics. Traditional name. Traditional notation

DiracDelta. Notations. Primary definition. Specific values. General characteristics. Traditional name. Traditional notation DiracDelta Notations Traditional name Dirac delta function Traditional notation x Mathematica StandardForm notation DiracDeltax Primary definition 4.03.02.000.0 x Π lim ε ; x ε0 x 2 2 ε Specific values

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

Areas and Lengths in Polar Coordinates Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the

Διαβάστε περισσότερα

forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with

forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with Week 03: C lassification of S econd- Order L inear Equations In last week s lectures we have illustrated how to obtain the general solutions of first order PDEs using the method of characteristics. We

Διαβάστε περισσότερα

Differentiation exercise show differential equation

Differentiation exercise show differential equation Differentiation exercise show differential equation 1. If y x sin 2x, prove that x d2 y 2 2 + 2y x + 4xy 0 y x sin 2x sin 2x + 2x cos 2x 2 2cos 2x + (2 cos 2x 4x sin 2x) x d2 y 2 2 + 2y x + 4xy (2x cos

Διαβάστε περισσότερα

A Note on Intuitionistic Fuzzy. Equivalence Relation

A Note on Intuitionistic Fuzzy. Equivalence Relation International Mathematical Forum, 5, 2010, no. 67, 3301-3307 A Note on Intuitionistic Fuzzy Equivalence Relation D. K. Basnet Dept. of Mathematics, Assam University Silchar-788011, Assam, India dkbasnet@rediffmail.com

Διαβάστε περισσότερα

Duals of the QCQP and SDP Sparse SVM. Antoni B. Chan, Nuno Vasconcelos, and Gert R. G. Lanckriet

Duals of the QCQP and SDP Sparse SVM. Antoni B. Chan, Nuno Vasconcelos, and Gert R. G. Lanckriet Duals of the QCQP and SDP Sparse SVM Anton B. Chan, Nuno Vasconcelos, and Gert R. G. Lanckret SVCL-TR 007-0 v Aprl 007 Duals of the QCQP and SDP Sparse SVM Anton B. Chan, Nuno Vasconcelos, and Gert R.

Διαβάστε περισσότερα

Main source: "Discrete-time systems and computer control" by Α. ΣΚΟΔΡΑΣ ΨΗΦΙΑΚΟΣ ΕΛΕΓΧΟΣ ΔΙΑΛΕΞΗ 4 ΔΙΑΦΑΝΕΙΑ 1

Main source: Discrete-time systems and computer control by Α. ΣΚΟΔΡΑΣ ΨΗΦΙΑΚΟΣ ΕΛΕΓΧΟΣ ΔΙΑΛΕΞΗ 4 ΔΙΑΦΑΝΕΙΑ 1 Main source: "Discrete-time systems and computer control" by Α. ΣΚΟΔΡΑΣ ΨΗΦΙΑΚΟΣ ΕΛΕΓΧΟΣ ΔΙΑΛΕΞΗ 4 ΔΙΑΦΑΝΕΙΑ 1 A Brief History of Sampling Research 1915 - Edmund Taylor Whittaker (1873-1956) devised a

Διαβάστε περισσότερα

Exam Statistics 6 th September 2017 Solution

Exam Statistics 6 th September 2017 Solution Exam Statstcs 6 th September 17 Soluto Maura Mezzett Exercse 1 Let (X 1,..., X be a raom sample of... raom varables. Let f θ (x be the esty fucto. Let ˆθ be the MLE of θ, θ be the true parameter, L(θ be

Διαβάστε περισσότερα

9.09. # 1. Area inside the oval limaçon r = cos θ. To graph, start with θ = 0 so r = 6. Compute dr

9.09. # 1. Area inside the oval limaçon r = cos θ. To graph, start with θ = 0 so r = 6. Compute dr 9.9 #. Area inside the oval limaçon r = + cos. To graph, start with = so r =. Compute d = sin. Interesting points are where d vanishes, or at =,,, etc. For these values of we compute r:,,, and the values

Διαβάστε περισσότερα

( y) Partial Differential Equations

( y) Partial Differential Equations Partial Dierential Equations Linear P.D.Es. contains no owers roducts o the deendent variables / an o its derivatives can occasionall be solved. Consider eamle ( ) a (sometimes written as a ) we can integrate

Διαβάστε περισσότερα

MINIMAL CLOSED SETS AND MAXIMAL CLOSED SETS

MINIMAL CLOSED SETS AND MAXIMAL CLOSED SETS MINIMAL CLOSED SETS AND MAXIMAL CLOSED SETS FUMIE NAKAOKA AND NOBUYUKI ODA Received 20 December 2005; Revised 28 May 2006; Accepted 6 August 2006 Some properties of minimal closed sets and maximal closed

Διαβάστε περισσότερα

Technical Report: A Unified Framework for Analysis of Path Selection Based Decode-and-Forward (DF) Cooperation in Wireless Systems

Technical Report: A Unified Framework for Analysis of Path Selection Based Decode-and-Forward (DF) Cooperation in Wireless Systems Techncal Report: A Unfed Framework for Analyss of ath Selecton Based Decode-and-Forward DF Cooperaton n Wreless Systems Neeraj Varshney Student ember, IEEE and Adtya K. Jagannatham, ember, IEEE I. VALUES

Διαβάστε περισσότερα