is the home less foreign interest rate differential (expressed as it
|
|
- Συντύχη Γιάνναρης
- 6 χρόνια πριν
- Προβολές:
Transcript
1 The model is solved algebraically, excep for a cubic roo which is solved numerically The mehod of soluion is undeermined coefficiens The noaion in his noe corresponds o he noaion in he program The model is given by: () λ = αγ + η Here, λ is he ex ane excess reurn on he foreign deposi (relaive o he home deposi) * as in he paper γ + is he home less foreign ineres rae differenial (expressed as i i in he paper The + subscrip is useful because we can hink of his as a predeermined iable if we were o use he Blanchard-Kahn soluion echnique) (2) λ = Eq + q γ+ + Eπ+ This is he definiion of he excess reurn π + is home less foreign inflaion π = δ q q + βeπ + (3) ( ) This is he (home less foreign) Phillips curve (4) γ = π + + ργ This is he (home less foreign) Taylor rule The following equaions are he sochasic processes for he exogenous iables: (5) q = ξq + ε (6) η = µη + u The program akes as inpu he values of he parameers α, δ, β,, ρ, ξ, µ, and he iances of q and η, which are enered in lines 8 hrough 26 in he program We posi an undeermined coefficiens soluion for he ineres differenial, he real exchange rae and he relaive inflaion raes: (7) γ = aq + bη + + cγ
2 (8) q = dq + eη + f γ (9) π = gq + hη + kγ Using equaions (5)-(9), we have: (0) q = dξq + dε + eµη + eu + faq + fbη + fcγ Taking expecaions: Eq = dξ + fa q + eµ + + fb η + fcγ () ( ) ( ) Then again using equaions (5)-(9), we have: (2) π + = gξq + gε + + hµη + hu+ + kaq + kbη + kcγ Taking expecaions: E π = gξ + ka q + hµ + + kb η + kcγ (3) ( ) ( ) Now use (7) and (9) o make subsiuions ino equaion (4): ( ) aq + bη + cγ = gq + hη + kγ + ργ Maching coefficiens, we have: (4) a= g (5) b= h (6) c= k+ ρ Nex use (7), (9) and (3) o make subsiuions ino equaion (3): ( ) (( ) ( ) ) gq + hη + kγ = δ dq + eη + f γ δq + β gξ + ka q + hµ + kb η + kcγ Maching coefficiens, we have: (7) g = δ ( d ) + β( gξ + ka) (8) h = δe + β ( hµ + kb) (9) k = δ f + βkc 2
3 Eliminae λ by equaing () and (2), hen use equaions (7), (8), () and (3): (20) ( ) (2) ( ) (22) ( α ) ( aq + b + c ) = ( d + fa) q + ( e + fb) + fc ( dq + e + f ) ( aq + bη + cγ ) + ( gξ + ka) q + ( hµ + kb) η + kcγ α η γ η ξ µ η γ η γ Maching coefficiens, we have: + α a = ξd + fa d + gξ + ka + α b = µ e + fb e + µ h + kb + c = fc f + kc Equaions (4)-(22) are nine equaions ha allow for us o solve for he nine undeermined coefficiens: a, b, c, d, e, f, g, h and k Equaions (6), (9) and (22) allow us o solve for c, f, and k Firs, solve for k from (6): c ρ k = Then subsiue his ino (9): c ρ = δ f ( βc), and solve for f: f c ρ = ( βc) δ Then subsiue his ino equaion (22) o ge: c ρ c ρ + c= c c + c δ ( α) ( β ) ( ) This gives us he equaion: ( βc)( c ρ )( c) δ c( α ) δ c( c ρ ) 0= + + 3
4 The program solves his equaion in line 3 There are hree roos o his cubic equaion We use he soluion ha is less han one in absolue value, which is given in line 34 c ρ Then from above, he program solves for k in line 39 using k = And in line 40, he program c ρ k solves for f using f = ( βc) = ( βc) δ δ We have solved for c, f, and k Then equaions (4), (7) and (20) le us solve for a, d and a g From (4) we have g = From (20), we have: ξ d = f + + k+ a, so ( ξ ) ( α) ( f k) ( ξ ) + α ξ d = a Subsiuing hese expressions for g and d ino (7), we ge: a = ( ξ ) ( ) ( ) δ ξ β ξ + + δ + α ξ ( k ) ( ( f k) ) This is he soluion for a in line 4 of he program Then line 42 gives us d as ( + α f k) ξ a d = a, and line 43 gives us g as g = ξ ( ) Nex, equaions (5), (8), and (2) will allow us o solve for b, h and e From equaion b (5), we have h = From (2) we ge ( f + k α ) b+ + µ h= ( µ ) e, so e = ( ( ) ) ( µ ) f + k α + µ b+ Subsiuing hese ino (8) we ge: ( ( ) ) ( ) b f + k α + µ b+ b = δ + β µ + kb µ, or b = δ k f k ( µ )( β ( µ + )) δ ( ( + α ) + µ ) which is line 44 of he program 4
5 b Line 45 gives us h as h =, and line 46 gives us e as from (8) as ( βµ ) h βkb ( βµ βk ) b e = = δ δ Nex we solve for he real ineres rae differenial We posulae a soluion of he form r = mq + nη + pγ (23) We can use he fac ha r = γ+ Eπ+ and equaions (7) and (3) o wrie: (( ) ( ) ) mq + nη + pγ = aq + bη + cγ gξ + ka q + hµ + kb η + kcγ Maching coefficiens, we have: ( ξ ) m = a g + ka, which is line 47 of he program ( µ ) n = b h + kb, which is line 48 of he program ( ) p = c k, which is line 49 of he program Then we posi a soluion for he ex ane excess reurn: (24) λ = qq + rη + sγ From equaion (), we have λ = αγ η We can hen subsiue from (7) o ge: + qq + rη + sγ = αaq + αη b + αγ c η Maching coefficiens, we have q = αa, which is line 50 of he program r = αb, which is line 5 of he program s = αc, which is line 52 of he program So we have λ = αaq + rη + αγ c Eλ = αaξ q + α b µη + αcγ Then, ( ) + + 5
6 E λ = αaξ q + rµη + αce γ, and so on We have: αa r Λ = q + η + se( γ + γ+ + γ+ 2 + ) ξ µ Now, γ = aq + bη + + cγ ec Then ( ) E γ = E aq + bη + cγ = aξ q + bµη + cγ ( ) ( ) ( ) E γ = E aq + bη + cγ = aξ + caξ q + bµ + cbµη+ c γ ( ) ( ) ( ) E γ = E aq + bη + cγ = aξ + caξ + c aξ q + bµ + cbµ + c bµη+ c γ E We see ha ( γ γ ) + + = ( + ξ + ξ + ξ + ξ + ( ξ + ξ) + ξ + ( ξ + ( ξ + ξ) ) + ) b c c( c ) c c( c ) a c c c c c c q ( ( ) ) + + µ + µ + µ + µ + µ + µ + µ + µ + µ + µ + η c + ( + c) γ + γ c ( ) ( ( )) ( ) E ( γ + γ + ) = a + ξ ( c+ c + ) q + b + µ c+ c + η + + c γ + c γ ξ µ c + + which can be wrien as: 6
7 a c b c c E( γ + γ+ + ) = + ξ q + + µ η + ( + c) γ + γ+ ξ c µ c c a c b c c = + ξ q + + µ η + + c γ + aq + bη + cγ ξ c µ c c a b = q + η + γ c c c ( ξ )( ) ( µ )( ) ( ) ( ) Then we ge: αa r a b Λ = q + η + αc q + η + γ ξ µ ( ξ )( c) ( µ )( c) c αa αcb αc = q + r+ η + γ ξ c µ c c ( )( ) αa r+ c = q + η + αc γ c c c ( ξ )( ) ( µ )( ) So we can wrie (25) vq wη xγ Λ = + +, where v = w = αa ( ξ )( c) r+ c ( µ )( c), which is line 53 of he program, which is line 54 of he program αc x =, which is line 55 of he program c Nex, we calculae some iances and coiances ( γ q ) ( aq bη cγ ξq ε ) aξ ( q ) cξ ( γ q ) cov, = cov + +, + = + cov, Hence, cov ( γ, q ) ( q ) aξ =, which is line 56 of he program cξ 7
8 = = + Then, cov ( γ, η ) cov ( aq bη cγ, µη u ) bµ ( η ) cµ cov ( γ, η ) Hence, cov ( γ, η ) ( η ) bµ =, which is line 57 of he program cµ ( γ+ ) = ( aq + bη + cγ) = c ( γ ) + a ( q ) + b ( η ) + 2ac cov ( q, γ ) + 2bc cov ( η, γ ) This is line 58 of he program 2 2 a b 2ac 2bc cov, cov, ( q ) ( η ) ( q γ ) ( η γ ) = c c c c ( λ r) = ( qq + rη + sγ mq + nη + pγ) ( ) ( η ) ( γ ) ( ) cov (, γ ) ( ) cov ( η, γ ) cov, cov, = qm q + rn + ps + pq + ms q + pr + ns which is line 59 of he program ( Λ r) = ( vq + wη + xγ mq + nη + pγ) ( ) ( η ) ( γ ) ( ) cov (, γ ) ( ) cov ( η, γ ) cov, cov, = vm q + wn + xp + pv + mx q + pw + nx which is line 60 of he program ( r) = ( mq + nη + pγ) 2 ( ) 2 ( η ) 2 ( γ ) 2 cov (, γ ) 2 cov ( η, γ ) = m q + n + p + mp q + np which is line 6 of he program ( λ) = ( qq + rη + sγ) 2 ( ) 2 ( η ) 2 ( γ ) 2 cov (, γ ) 2 cov ( η, γ ) = q q + r + s + qs q + rs \ which is line 62 of he program Then he regression coefficien for regressing λ on r is given by line 63 of he program The regression coefficien for regressing which is line 64 of he program ( λ r) ( r ) cov, Λ on r is given by, which is ( Λ r) ( r ) cov, 8
9 Nex, we have: ( π) = ( gq + hη + kγ) 2 ( ) 2 ( η ) 2 ( γ ) 2 cov (, γ ) 2 cov ( η, γ ) = g q + h + k + gk q + hk which is line 65 of he program cov( π+ π) = cov ( gq+ + hη+ + kγ+, gq + hη + kγ) = cov ( gξq + gε + + hµη + hu+ + kaq + kbη + kcγ, gq + hη + kγ ) = cov (( gξ + ka) q + ( hµ + kb) η + kcγ, gq + hη + kγ) 2 = g ( gξ + ka) ( q) + h( hµ + kb) ( η) + k c ( γ) + ( k ( gξ + ka) + gkc) cov ( q, γ ) + ( h( hµ + kb) + hkc) cov ( η, γ ) which is line 66 of he program The serial correlaion of inflaion is given by cov ( π+ π) ( π ), which is line 67 of he program Then, cov ( γ+, γ) = cov ( aq + bη + cγ, γ) = c ( γ) + a cov ( γ, q) + bcov ( γ, η), which is line 68 of he program The serial correlaion of he nominal ineres rae is given by of he program cov ( γ+ γ) ( γ ), which is line 69 ( γ+ r) = ( aq + bη + cγ mq + nη + pγ) ( ) ( η ) ( γ ) ( ) cov (, γ ) ( ) cov ( η, γ ) cov, cov, = am q + bn + cp + pa + mc q + pb + nc which is line 70 of he program 9
Appendix. The solution begins with Eq. (2.15) from the text, which we repeat here for 1, (A.1)
Aenix Aenix A: The equaion o he sock rice. The soluion egins wih Eq..5 rom he ex, which we reea here or convenience as Eq.A.: [ [ E E X, A. c α where X u ε, α γ, an c α y AR. Take execaions o Eq. A. as
Διαβάστε περισσότεραCHAPTER 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( ) ( t) ( 0) ( ) dw w. = = β. Then the solution of (1.1) is easily found to. wt = t+ t. We generalize this to the following nonlinear differential
Periodic oluion of van der Pol differenial equaion. by A. Arimoo Deparmen of Mahemaic Muahi Iniue of Technology Tokyo Japan in Seminar a Kiami Iniue of Technology January 8 9. Inroducion Le u conider a
Διαβάστε περισσότερα= e 6t. = t 1 = t. 5 t 8L 1[ 1 = 3L 1 [ 1. L 1 [ π. = 3 π. = L 1 3s = L. = 3L 1 s t. = 3 cos(5t) sin(5t).
Worked Soluion 95 Chaper 25: The Invere Laplace Tranform 25 a From he able: L ] e 6 6 25 c L 2 ] ] L! + 25 e L 5 2 + 25] ] L 5 2 + 5 2 in(5) 252 a L 6 + 2] L 6 ( 2)] 6L ( 2)] 6e 2 252 c L 3 8 4] 3L ] 8L
Διαβάστε περισσότεραMatrices 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 περισσότερα4.6 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 περισσότεραSecond 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 περισσότεραMath221: 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 περισσότεραSection 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 περισσότεραNotes on the Open Economy
Notes on the Open Econom Ben J. Heijdra Universit of Groningen April 24 Introduction In this note we stud the two-countr model of Table.4 in more detail. restated here for convenience. The model is Table.4.
Διαβάστε περισσότεραCHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS
CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS EXERCISE 01 Page 545 1. Use matrices to solve: 3x + 4y x + 5y + 7 3x + 4y x + 5y 7 Hence, 3 4 x 0 5 y 7 The inverse of 3 4 5 is: 1 5 4 1 5 4 15 8 3
Διαβάστε περισσότεραExample 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 περισσότερα6.1. 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 περισσότεραHOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:
HOMEWORK 4 Problem a For the fast loading case, we want to derive the relationship between P zz and λ z. We know that the nominal stress is expressed as: P zz = ψ λ z where λ z = λ λ z. Therefore, applying
Διαβάστε περισσότεραApproximation of distance between locations on earth given by latitude and longitude
Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth
Διαβάστε περισσότεραHomework 3 Solutions
Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For
Διαβάστε περισσότεραAreas 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 περισσότεραAreas 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 περισσότεραΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Αν κάπου κάνετε κάποιες υποθέσεις να αναφερθούν στη σχετική ερώτηση. Όλα τα αρχεία που αναφέρονται στα προβλήματα βρίσκονται στον ίδιο φάκελο με το εκτελέσιμο
Διαβάστε περισσότερα16. 17. r t te 2t i t 1. 18 19 Find the derivative of the vector function. 19. r t e t cos t i e t sin t j ln t k. 31 33 Evaluate the integral.
SECTION.7 VECTOR FUNCTIONS AND SPACE CURVES.7 VECTOR FUNCTIONS AND SPACE CURVES A Click here for answers. S Click here for soluions. Copyrigh Cengage Learning. All righs reserved.. Find he domain of he
Διαβάστε περισσότερα2 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 περισσότεραSCHOOL 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 περισσότεραLecture 12 Modulation and Sampling
EE 2 spring 2-22 Handou #25 Lecure 2 Modulaion and Sampling The Fourier ransform of he produc of wo signals Modulaion of a signal wih a sinusoid Sampling wih an impulse rain The sampling heorem 2 Convoluion
Διαβάστε περισσότεραSection 9.2 Polar Equations and Graphs
180 Section 9. Polar Equations and Graphs In this section, we will be graphing polar equations on a polar grid. In the first few examples, we will write the polar equation in rectangular form to help identify
Διαβάστε περισσότερα6.3 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 περισσότεραb. 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 περισσότεραECE Spring Prof. David R. Jackson ECE Dept. Notes 2
ECE 634 Spring 6 Prof. David R. Jackson ECE Dept. Notes Fields in a Source-Free Region Example: Radiation from an aperture y PEC E t x Aperture Assume the following choice of vector potentials: A F = =
Διαβάστε περισσότεραANSWERSHEET (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 περισσότεραTRM +4!5"2# 6!#!-!2&'!5$27!842//22&'9&2:1*;832<
TRM!"#$%& ' *,-./ *!#!!%!&!3,&!$-!$./!!"#$%&'*" 4!5"# 6!#!-!&'!5$7!84//&'9&:*;83< #:4
Διαβάστε περισσότεραk 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 περισσότεραderivation 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 περισσότεραFinite 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 περισσότεραPractice Exam 2. Conceptual Questions. 1. State a Basic identity and then verify it. (a) Identity: Solution: One identity is csc(θ) = 1
Conceptual Questions. State a Basic identity and then verify it. a) Identity: Solution: One identity is cscθ) = sinθ) Practice Exam b) Verification: Solution: Given the point of intersection x, y) of the
Διαβάστε περισσότεραExercises 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 περισσότερα2. 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 περισσότεραSrednicki Chapter 55
Srednicki Chapter 55 QFT Problems & Solutions A. George August 3, 03 Srednicki 55.. Use equations 55.3-55.0 and A i, A j ] = Π i, Π j ] = 0 (at equal times) to verify equations 55.-55.3. This is our third
Διαβάστε περισσότεραC.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 περισσότεραMATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)
1. MATH43 String Theory Solutions 4 x = 0 τ = fs). 1) = = f s) ) x = x [f s)] + f s) 3) equation of motion is x = 0 if an only if f s) = 0 i.e. fs) = As + B with A, B constants. i.e. allowe reparametrisations
Διαβάστε περισσότερα2. Μηχανικό Μαύρο Κουτί: κύλινδρος με μια μπάλα μέσα σε αυτόν.
Experiental Copetition: 14 July 011 Proble Page 1 of. Μηχανικό Μαύρο Κουτί: κύλινδρος με μια μπάλα μέσα σε αυτόν. Ένα μικρό σωματίδιο μάζας (μπάλα) βρίσκεται σε σταθερή απόσταση z από το πάνω μέρος ενός
Διαβάστε περισσότεραΕΡΓΑΣΙΑ ΜΑΘΗΜΑΤΟΣ: ΘΕΩΡΙΑ ΒΕΛΤΙΣΤΟΥ ΕΛΕΓΧΟΥ ΦΙΛΤΡΟ KALMAN ΜΩΥΣΗΣ ΛΑΖΑΡΟΣ
ΑΡΙΣΤΟΤΕΛΕΙΟ ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΟΝΙΚΗΣ ΤΜΗΜΑ ΜΑΘΗΜΑΤΙΚΩΝ ΜΕΤΑΠΤΥΧΙΑΚΟ ΠΡΟΓΡΑΜΜΑ ΣΠΟΥΔΩΝ ΘΕΩΡΗΤΙΚΗ ΠΛΗΡΟΦΟΡΙΚΗ ΚΑΙ ΘΕΩΡΙΑ ΣΥΣΤΗΜΑΤΩΝ & ΕΛΕΓΧΟΥ ΕΡΓΑΣΙΑ ΜΑΘΗΜΑΤΟΣ: ΘΕΩΡΙΑ ΒΕΛΤΙΣΤΟΥ ΕΛΕΓΧΟΥ ΦΙΛΤΡΟ KALMAN ΜΩΥΣΗΣ
Διαβάστε περισσότερα3.4 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 περισσότεραOrdinal 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 περισσότεραUniform Convergence of Fourier Series Michael Taylor
Uniform Convergence of Fourier Series Michael Taylor Given f L 1 T 1 ), we consider the partial sums of the Fourier series of f: N 1) S N fθ) = ˆfk)e ikθ. k= N A calculation gives the Dirichlet formula
Διαβάστε περισσότεραSolutions 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 περισσότεραInverse 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 περισσότεραEcon Spring 2004 Instructor: Prof. Kiefer Solution to Problem set # 5. γ (0)
Cornell University Department of Economics Econ 60 - Spring 004 Instructor: Prof. Kiefer Solution to Problem set # 5. Autocorrelation function is defined as ρ h = γ h γ 0 where γ h =Cov X t,x t h =E[X
Διαβάστε περισσότεραQuadratic 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 περισσότεραProblem Set 3: Solutions
CMPSCI 69GG Applied Information Theory Fall 006 Problem Set 3: Solutions. [Cover and Thomas 7.] a Define the following notation, C I p xx; Y max X; Y C I p xx; Ỹ max I X; Ỹ We would like to show that C
Διαβάστε περισσότεραΧρονοσειρές Μάθημα 3
Χρονοσειρές Μάθημα 3 Ασυσχέτιστες (λευκός θόρυβος) και ανεξάρτητες (iid) παρατηρήσεις Chafield C., The Analysis of Time Series, An Inroducion, 6 h ediion,. 38 (Chaer 3): Some auhors refer o make he weaker
Διαβάστε περισσότεραMathematical model for HIV spreads control program with ART treatment
Journal of Physics: Conference Series PAPER OPEN ACCESS Mathematical model for HIV spreads control program with ART treatment To cite this article: Maimunah and Dipo Aldila 208 J. Phys.: Conf. Ser. 974
Διαβάστε περισσότεραThe 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 περισσότεραHomework 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 περισσότεραReview Exercises for Chapter 7
8 Chapter 7 Integration Techniques, L Hôpital s Rule, and Improper Integrals 8. For n, I d b For n >, I n n u n, du n n d, dv (a) d b 6 b 6 (b) (c) n d 5 d b n n b n n n d, v d 6 5 5 6 d 5 5 b d 6. b 6
Διαβάστε περισσότεραJesse Maassen and Mark Lundstrom Purdue University November 25, 2013
Notes on Average Scattering imes and Hall Factors Jesse Maassen and Mar Lundstrom Purdue University November 5, 13 I. Introduction 1 II. Solution of the BE 1 III. Exercises: Woring out average scattering
Διαβάστε περισσότεραUniversity of Washington Department of Chemistry Chemistry 553 Spring Quarter 2010 Homework Assignment 3 Due 04/26/10
Universiy of Washingon Deparmen of Chemisry Chemisry 553 Spring Quarer 1 Homework Assignmen 3 Due 4/6/1 v e v e A s ds: a) Show ha for large 1 and, (i.e. 1 >> and >>) he velociy auocorrelaion funcion 1)
Διαβάστε περισσότεραLecture 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 περισσότεραCRASH COURSE IN PRECALCULUS
CRASH COURSE IN PRECALCULUS Shiah-Sen Wang The graphs are prepared by Chien-Lun Lai Based on : Precalculus: Mathematics for Calculus by J. Stuwart, L. Redin & S. Watson, 6th edition, 01, Brooks/Cole Chapter
Διαβάστε περισσότεραManaging Production-Inventory Systems with Scarce Resources
Managing Producion-Invenory Sysems wih Scarce Resources Online Supplemen Proof of Lemma 1: Consider he following dynamic program: where ḡ (x, z) = max { cy + E f (y, z, D)}, (7) x y min(x+u,z) f (y, z,
Διαβάστε περισσότεραDESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.
DESIGN OF MACHINERY SOLUTION MANUAL -7-1! PROBLEM -7 Statement: Design a double-dwell cam to move a follower from to 25 6, dwell for 12, fall 25 and dwell for the remader The total cycle must take 4 sec
Διαβάστε περισσότεραMathCity.org Merging man and maths
MathCity.org Merging man and maths Exercise 10. (s) Page Textbook of Algebra and Trigonometry for Class XI Available online @, Version:.0 Question # 1 Find the values of sin, and tan when: 1 π (i) (ii)
Διαβάστε περισσότερα9.09. # 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 περισσότεραOther 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 περισσότεραTrigonometry 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 περισσότεραDurbin-Levinson recursive method
Durbin-Levinson recursive method A recursive method for computing ϕ n is useful because it avoids inverting large matrices; when new data are acquired, one can update predictions, instead of starting again
Διαβάστε περισσότεραNecessary and sufficient conditions for oscillation of first order nonlinear neutral differential equations
J. Mah. Anal. Appl. 321 (2006) 553 568 www.elsevier.com/locae/jmaa Necessary sufficien condiions for oscillaion of firs order nonlinear neural differenial equaions X.H. ang a,, Xiaoyan Lin b a School of
Διαβάστε περισσότεραFourier Series. Fourier Series
ECE 37 Z. Aliyazicioglu Elecrical & Compuer Egieerig Dep. Cal Poly Pomoa Periodic sigal is a fucio ha repeas iself every secods. x() x( ± ) : period of a fucio, : ieger,,3, x() 3 x() x() Periodic sigal
Διαβάστε περισσότερα1 1 1 2 1 2 2 1 43 123 5 122 3 1 312 1 1 122 1 1 1 1 6 1 7 1 6 1 7 1 3 4 2 312 43 4 3 3 1 1 4 1 1 52 122 54 124 8 1 3 1 1 1 1 1 152 1 1 1 1 1 1 152 1 5 1 152 152 1 1 3 9 1 159 9 13 4 5 1 122 1 4 122 5
Διαβάστε περισσότεραPhys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)
Phys460.nb 81 ψ n (t) is still the (same) eigenstate of H But for tdependent H. The answer is NO. 5.5.5. Solution for the tdependent Schrodinger s equation If we assume that at time t 0, the electron starts
Διαβάστε περισσότεραMath 6 SL Probability Distributions Practice Test Mark Scheme
Math 6 SL Probability Distributions Practice Test Mark Scheme. (a) Note: Award A for vertical line to right of mean, A for shading to right of their vertical line. AA N (b) evidence of recognizing symmetry
Διαβάστε περισσότεραReservoir modeling. Reservoir modelling Linear reservoirs. The linear reservoir, no input. Starting up reservoir modeling
Reservoir modeling Reservoir modelling Linear reservoirs Paul Torfs Basic equaion for one reservoir:) change in sorage = sum of inflows minus ouflows = Q in,n Q ou,n n n jus an ordinary differenial equaion
Διαβάστε περισσότεραDifferentiation 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 περισσότεραMock Exam 7. 1 Hong Kong Educational Publishing Company. Section A 1. Reference: HKDSE Math M Q2 (a) (1 + kx) n 1M + 1A = (1) =
Mock Eam 7 Mock Eam 7 Section A. Reference: HKDSE Math M 0 Q (a) ( + k) n nn ( )( k) + nk ( ) + + nn ( ) k + nk + + + A nk... () nn ( ) k... () From (), k...() n Substituting () into (), nn ( ) n 76n 76n
Διαβάστε περισσότεραΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 6/5/2006
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Ολοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα είναι μικρότεροι το 1000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Διάρκεια: 3,5 ώρες Καλή
Διαβάστε περισσότεραEcon 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 περισσότεραd dt S = (t)si d dt R = (t)i d dt I = (t)si (t)i
d d S = ()SI d d I = ()SI ()I d d R = ()I d d S = ()SI μs + fi + hr d d I = + ()SI (μ + + f + ())I d d R = ()I (μ + h)r d d P(S,I,) = ()(S +1)(I 1)P(S +1, I 1, ) +()(I +1)P(S,I +1, ) (()SI + ()I)P(S,I,)
Διαβάστε περισσότερα6. MAXIMUM LIKELIHOOD ESTIMATION
6 MAXIMUM LIKELIHOOD ESIMAION [1] Maximum Likelihood Estimator (1) Cases in which θ (unknown parameter) is scalar Notational Clarification: From now on, we denote the true value of θ as θ o hen, view θ
Διαβάστε περισσότεραSolution 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 περισσότεραTridiagonal matrices. Gérard MEURANT. October, 2008
Tridiagonal matrices Gérard MEURANT October, 2008 1 Similarity 2 Cholesy factorizations 3 Eigenvalues 4 Inverse Similarity Let α 1 ω 1 β 1 α 2 ω 2 T =......... β 2 α 1 ω 1 β 1 α and β i ω i, i = 1,...,
Διαβάστε περισσότερα6.003: Signals and Systems
6.3: Signals and Sysems Modulaion December 6, 2 Communicaions Sysems Signals are no always well mached o he media hrough which we wish o ransmi hem. signal audio video inerne applicaions elephone, radio,
Διαβάστε περισσότεραSection 7.6 Double and Half Angle Formulas
09 Section 7. Double and Half Angle Fmulas To derive the double-angles fmulas, we will use the sum of two angles fmulas that we developed in the last section. We will let α θ and β θ: cos(θ) cos(θ + θ)
Διαβάστε περισσότεραConcrete Mathematics Exercises from 30 September 2016
Concrete Mathematics Exercises from 30 September 2016 Silvio Capobianco Exercise 1.7 Let H(n) = J(n + 1) J(n). Equation (1.8) tells us that H(2n) = 2, and H(2n+1) = J(2n+2) J(2n+1) = (2J(n+1) 1) (2J(n)+1)
Διαβάστε περισσότεραCyclic or elementary abelian Covers of K 4
Cyclic or elementary abelian Covers of K 4 Yan-Quan Feng Mathematics, Beijing Jiaotong University Beijing 100044, P.R. China Summer School, Rogla, Slovenian 2011-06 Outline 1 Question 2 Main results 3
Διαβάστε περισσότερα6.003: Signals and Systems. Modulation
6.3: Signals and Sysems Modulaion December 6, 2 Subjec Evaluaions Your feedback is imporan o us! Please give feedback o he saff and fuure 6.3 sudens: hp://web.mi.edu/subjecevaluaion Evaluaions are open
Διαβάστε περισσότεραHOMEWORK#1. t E(x) = 1 λ = (b) Find the median lifetime of a randomly selected light bulb. Answer:
HOMEWORK# 52258 李亞晟 Eercise 2. The lifetime of light bulbs follows an eponential distribution with a hazard rate of. failures per hour of use (a) Find the mean lifetime of a randomly selected light bulb.
Διαβάστε περισσότεραThe choice of an optimal LCSCR contract involves the choice of an x L. such that the supplier chooses the LCS option when x xl
EHNIA APPENDIX AMPANY SIMPE S SHARIN NRAS Proof of emma. he choice of an opimal SR conrac involves he choice of an such ha he supplier chooses he S opion hen and he R opion hen >. When he selecs he S opion
Διαβάστε περισσότεραOverview. Transition Semantics. Configurations and the transition relation. Executions and computation
Overview Transition Semantics Configurations and the transition relation Executions and computation Inference rules for small-step structural operational semantics for the simple imperative language Transition
Διαβάστε περισσότεραw o = R 1 p. (1) R = p =. = 1
Πανεπιστήµιο Κρήτης - Τµήµα Επιστήµης Υπολογιστών ΗΥ-570: Στατιστική Επεξεργασία Σήµατος 205 ιδάσκων : Α. Μουχτάρης Τριτη Σειρά Ασκήσεων Λύσεις Ασκηση 3. 5.2 (a) From the Wiener-Hopf equation we have:
Διαβάστε περισσότεραKey Formulas From Larson/Farber Elementary Statistics: Picturing the World, Second Edition 2002 Prentice Hall
64_INS.qxd /6/0 :56 AM Page Key Formulas From Larson/Farber Elemenary Saisics: Picuring he World, Second Ediion 00 Prenice Hall CHAPTER Class Widh = round up o nex convenien number Maximum daa enry - Minimum
Διαβάστε περισσότεραD Alembert s Solution to the Wave Equation
D Alembert s Solution to the Wave Equation MATH 467 Partial Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Objectives In this lesson we will learn: a change of variable technique
Διαβάστε περισσότεραFigure A.2: MPC and MPCP Age Profiles (estimating ρ, ρ = 2, φ = 0.03)..
Supplemental Material (not for publication) Persistent vs. Permanent Income Shocks in the Buffer-Stock Model Jeppe Druedahl Thomas H. Jørgensen May, A Additional Figures and Tables Figure A.: Wealth and
Διαβάστε περισσότεραEE512: 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 περισσότεραA 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 περισσότεραStrain gauge and rosettes
Strain gauge and rosettes Introduction A strain gauge is a device which is used to measure strain (deformation) on an object subjected to forces. Strain can be measured using various types of devices classified
Διαβάστε περισσότεραStatistical 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 περισσότερα9.1 Introduction 9.2 Lags in the Error Term: Autocorrelation 9.3 Estimating an AR(1) Error Model 9.4 Testing for Autocorrelation 9.
9.1 Inroducion 9.2 Lags in he Error Term: Auocorrelaion 9.3 Esimaing an AR(1) Error Model 9.4 Tesing for Auocorrelaion 9.5 An Inroducion o Forecasing: Auoregressive Models 9.6 Finie Disribued Lags 9.7
Διαβάστε περισσότερα( ) 2 and compare to M.
Problems and Solutions for Section 4.2 4.9 through 4.33) 4.9 Calculate the square root of the matrix 3!0 M!0 8 Hint: Let M / 2 a!b ; calculate M / 2!b c ) 2 and compare to M. Solution: Given: 3!0 M!0 8
Διαβάστε περισσότερα1) Formulation of the Problem as a Linear Programming Model
1) Formulation of the Problem as a Linear Programming Model Let xi = the amount of money invested in each of the potential investments in, where (i=1,2, ) x1 = the amount of money invested in Savings Account
Διαβάστε περισσότεραω = radians per sec, t = 3 sec
Secion. Linear and Angular Speed 7. From exercise, =. A= r A = ( 00 ) (. ) = 7,00 in 7. Since 7 is in quadran IV, he reference 7 8 7 angle is = =. In quadran IV, he cosine is posiive. Thus, 7 cos = cos
Διαβάστε περισσότεραLanczos and biorthogonalization methods for eigenvalues and eigenvectors of matrices
Lanzos and iorthogonalization methods for eigenvalues and eigenvetors of matries rolem formulation Many prolems are redued to solving the following system: x x where is an unknown numer А a matrix n n
Διαβάστε περισσότερα( ) ( ) ( ) Fourier series. ; m is an integer. r(t) is periodic (T>0), r(t+t) = r(t), t Fundamental period T 0 = smallest T. Fundamental frequency ω
Fourier series e jm when m d when m ; m is an ineger. jm jm jm jm e d e e e jm jm jm jm r( is periodi (>, r(+ r(, Fundamenal period smalles Fundamenal frequeny r ( + r ( is periodi hen M M e j M, e j,
Διαβάστε περισσότερα