Technical Notes for Discussion of Eggertsson, What Fiscal Policy Is Effective at Zero Interest Rates? Lawrence J. Christiano
|
|
- Ξένα Γερμανού
- 5 χρόνια πριν
- Προβολές:
Transcript
1 Tecnical Noes for Discussion of Eggersson Wa Fiscal Policy Is Effecive a Zero Ineres Raes? Larence J Crisiano Te model a as simulaed for e discussion is presened in e firs secion Te simulaion sraegy is described in e nex secion Houseold Te uiliy funcion of e j ouseold is: Tebudgeconsrainis: U (C j )logc A φ j φ P C B R B W j j Π j ere Π j denoes lump sum profis and lump sum axes Ineremporal Condiion Te discoun rae from o as e folloing represenaion: or β r µ βˆβ dr r ˆβ βdr Te firs order condiion associaed i bonds is: β C ( R ) C π Linearizing around a zero inflaion seady sae: Ĉ C βdr \ ( R ) ˆπ or Ĉ C βdr βdr ˆπ Ĉ Ĉ β (R r )ˆπ
2 Houseold Wage/Employmen Decision Te ouseold selecs e age rae o opimize: " # E ( ) i υ i W ji ji A φ ji φ ere υ i denoes e muliplier on e ouseold budge consrain in e Lagrangian represenaion of is problem Te ouseold reas is objec as an exogenous consan Eac ouseold a opimizes is age cooses e same age rae W : " E ( ) i φ # υ i W i A i ( φ) υ i ere i denoes e level of employmen in period i of a ouseold a opimizes is age in period : Ã! λ W λ i H i W i and H i denoes aggregae employmen Also W denoes e aggregae age rae Imposing e requiremen a e ouseold is alays on e labor demand curve implies: Ã! ³ λ λ W λ (φ) E ( ) i υ i W λ W W i H φ i H i A W i ( φ) υ i Differeniae i respec o W : µ E ( ) i υ i λ λ E µ ( ) i υ i λ λ µ W λ λ λ λ Hi λ A W i λ W λ λ λ λ (φ) µ W i W λ λ (φ) λ λ Hi λ A λ ³ ³ λ λ (φ) W i H φ i υ i λ λ (φ) W i H φ i υ i E ( ) i υ i W λ λ φ µ W i λ λ Hi λ A ³ λ W i λ (φ) H φ i υ i
3 E ( ) i υ i W λ λ φ Ã W λ λ W W i! λ λ H i λ A W λ λ (φ) ³ W W i λ υ i λ (φ) H φ i E Ã ( ) i υ i W W W i! ³ λ λ W λ W i H i λ A λ (φ) H φ i υ i or or E E " ( ) i φ # υ i W i λ A i υ i " W ( ) i υ i φ # ip i λ A i P i P i υ i " W E ( ) i φ # υ i ip i λ A i P i P i υ i Given our uiliy funcion e ave υ i U ci P i P i C i Noe a φ MRSi A i AC i φ P i υ i i ere MRSi denoes e marginal rae of subsiuion beeen consumpion and leisure in period i for a person a reopimizes in period and does no reopimize beeen and i Subsiue is ino e firs order condiion: " # E ( ) i i W λ MRSi C i P i No consider e folloing scaling: W W ½ π i π i i W P i Noe a i is definiion i P P i all i 3
4 Ten e firs order condiion reduces o: E ( ) i i i λ MRSi C i Noe ˆ i ˆπ ˆπ i We are ineresed in e case ere β is ime varying Aloug in e end e ime varying β as no impac on e reduced form age equaion i is useful o esablis is Tus β βˆβ r µ dr r β dr ˆβ βdr We rie ou e firs order condiion like is: β λ MRS C β β ξ λ MRS C β β β ξ λ MRS C β β β β 3 ξ λ MRS3 C 3 Log-linearly expanding is expression and aking ino accoun a e objec in square brackes is zero in seady sae: β b ŵ (λ MRS) \MRS i C β ³ ³ ξ b ŵ ˆ λ MRS MRS \ i C ³ ³ b ŵ ˆ MRS \ i β 3 ξ C β 4 ξ 3 C λ MRS ³ b ŵ 3 ˆ ³ λ MRS MRS \ 3 i 4
5 (noeoeimevaryingβ disappeared) noing λ MRS β b C ŵ \MRS i β ξ C b ŵ ˆ \MRS i β 3 ξ C b ŵ ˆ \MRS i β 4 ξ 3 C b ŵ ˆ 3 \MRS i 3 dividing roug by β : C Ten b ŵ \MRS b ŵ ˆ \MRS β ξ b ŵ ˆ \MRS i β 3 ξ 3 b ŵ ˆ 3 \MRS i i 3 b ŵ \MRS b ŵ ˆπ \MRS β ξ b ŵ ˆπ ˆπ \MRS i β 3 ξ 3 b ŵ ˆπ ˆπ ˆπ 3 \MRS i 3 i and b ŵ \MRS ˆπ \MRS i β ξ ˆπ ˆπ \MRS i β 3 ξ 3 ˆπ ˆπ ˆπ 3 \MRS i 3 5
6 b ŵ ˆπ ( ) ˆπ () MRS \ \MRS ( ) \MRS i Noe \MRS i Ĉ i φĥ i Ĉ i φĥ i φ ³ĥ i Ĥ i Recall i à µ µ µ W W i W W i W! λ λ H i λ λ Hi W W Wi W W i π π i λ λ Hi λ λ Hi for i : so a Ten Subsiuing Ã! λ λ W H ( ) λ λ H i H i ½ ĥ i Ĥi W ³ λ λ π π i i> ( ) λ λ i λ λ (ŵ ˆπ ˆπ i ) i> λ \MRS i Ĉi φĥi φ ³ĥ i Ĥi λ ŵ i Ĉi φĥi φ λ λ (ŵ ˆπ ˆπ i ) 6
7 for i> Ten \MRS \MRS ( ) \MRS Ĉ φĥ φ λ ŵ λ Ĉ φĥ φ λ (ŵ ˆπ ) λ ( ) Ĉ φĥ φ λ (ŵ ˆπ ˆπ ) λ ( ) 3 Ĉ 3 φĥ3 φ λ (ŵ ˆπ ˆπ ˆπ 3 ) λ \MRS \MRS ( ) \MRS i ( ) i Ĉ i φĥ i φ λ ŵ φ λ λ λ ( ) i ˆπ i i Subsiuing e previous expression ino () e conclude a e firs order condiion for ages looks as follos: b ŵ ( ) i ³ Ĉ i φĥ i ( ) i ˆπ i () i φ λ λ ŵ φ λ λ We no deduce e implicaions of e aggregae resricions across ages: ³ λ W ( ξ ) W λ ξ (W ) λ Divide by W and use e scaling noaion: µ ( ξ )( ) λ ξ π λ Log-linearize is abou seady sae: ( ξ ) () λ ŵ ξ λ λ (π ) λ π ˆπ aking ino accoun π : ŵ ξ ξ ˆπ 7 ( ) i ˆπ i i
8 Subsiuing is ino (): ξ ξ ˆπ b ³ ( ) i Ĉ i φĥi ( ) i ˆπ i i φ λ λ ξ ξ ˆπ φ λ λ ( ) i ˆπ i i Muliply by κ ( )( ξ ) ξ κ ξ ξ b ˆπ ξ ξ ( ) i ˆπ i i ³ ( ) i Ĉ i φĥi φ λ λ ˆπ ξ ξ φ λ λ ( ) i ˆπ i i Noe S ( ) i ˆπ i (3) i ˆπ ( ) ˆπ ( ) 3 ˆπ 3 ˆπ ˆπ ( ) ˆπ 3 ˆπ S S ( ) i ˆπ i ˆπ S S o i ³ ( ) i Ĉ i φĥi Ĉ φĥ S o So e expression for e age can be rien Lead and muliply by : ξ ξ b ˆπ ξ S ξ κs o φ λ λ ˆπ ξ ξ φ λ λ S ξ ξ b ˆπ ξ ξ S κ S o φ λ λ ˆπ ξ ξ φ λ λ S 8
9 Subrac e second from e firs and make use of (3) Collecing erms: ξ b ξ Noe ξ ξ b ξ ξ b ˆπ ˆπ ξ ξ ˆπ κ ³Ĉ φĥ φ λ ˆπ φ λ λ λ ˆπ ξ ξ φ λ λ ˆπ ξ ξ b ξ ξ b ˆπ ˆπ ξ ξ ˆπ κ ³Ĉ φĥ φ λ ˆπ φ λ λ ξ λ ˆπ κ ³Ĉ φĥ φ λ λ ˆπ ξ ξ ˆπ b b b ˆπ ˆπ b b ˆπ ˆπ λ φ λ ξ ˆπ so a en ξ b ξ κ ³Ĉ φĥ φ λ λ κb φ λ λ κ ³Ĉ φĥ φ λ ˆπ λ ³ κ b Ĉ φĥ ˆπ ξ ξ b ˆπ ˆπ ξ ξ ˆπ λ φ λ ξ ˆπ λ φ λ ξ ˆπ ξ ξ ˆπ φ λ λ ξ ˆπ 9
10 or No divide by e erm on ˆπ : φ λ ˆπ λ ³ µ κ b Ĉ φĥ φ λ ξ λ φ λ ˆπ λ ³ κ b Ĉ φĥ ˆπ κ φ λ λ 3 Goods Producion and Price Seing ξ ˆπ µ φ λ βˆπ λ ³ b Ĉ φĥ βˆπ Suppose a a final good Y is produced using a coninuum of inpus as follos: Z λ Y Y f diλf i λ f < (4) Te good is produced by a compeiive represenaive firm ic akes e price of oupu P and e price of inpus P i as given Te firs order necessary condiion associaed i opimizaion is: µ λ f P λ f Y Y i (5) A useful resul is obained by subsiuing ou for Y i in (4) from (5): P i Z P (λ f ) (P i ) λ f di (6) Eac inermediae good is produced by a monopolis using e folloing producion funcion: Y i A i Te equilibrium condiion associaed i price seing is afer log-linearizing abou seady sae: p ξp ˆπ βˆπ ŝ ξ p Marginal cos in is model is s W P
11 so a ŝ b Te resource consrain is: C p H ere p denoes e Tak Yun disorion ic is uniy o a firs order approximaion 4 Equilibrium Condiions Te sysem as 6 unknons: ˆπ b Ĥ ˆπ R Z and e folloing equaions Te equaions a caracerize e privae economy are: b b ˆπ ˆπ p ξp ˆπ βˆπ b ξ p κ ˆπ b φ λ λ dτ τ Ĥ Ĥ β (dz dr )ˆπ ( φ) Ĥ βˆπ and moneary policy: dz ρ R dr ( ρ R ) i r πˆπ r y Ĥ β ³ dz dz β dr zero bound no binding ³ oerise zero bound binding β Te laer capures e fac a R ic means R R /β We rie is in marix form as follos Supppose e zero bound is no binding so a dr dz (7)
12 Tisgivesussixequaionsinesixunknons: dr β ˆπ ( p)( ξ p ) ξ p β Ĥ b κ(φ) κ φ λ φ λ λ λ ˆπ β β ( ρ dz R ) r β y ( ρ R ) r β π dr ˆπ µ Ĥ b dr κ φ λ τ λ dτ ρ R ˆπ β dz α z α z α z β s β s ere e definiions of e marices are obvious and Le dr ˆπ µ z Ĥ dr b s dτ ˆπ dz ere Te linearized sysem en e zero bound is binding is as follos: d α z α z α z β s β s d β and α is α i is 6 6 elemen replaced by zero Tis sysem is simply e previous one i (7) replaced by: µ dr β
13 Simulaing e Model Te general algorim appears in e ird subsecion belo I capures e feaure of our seing a e equaions a caracerize equilibrium cange during e simulaion Before e discuss e algorim in is full generaliy e provide o examples o illusrae feaures of e algorim no relaed o e equaion sicing Simple Example We use a slig perurbaion on a sandard sooing algorim Te perurbaion is designed so a e algorim is required o i a specific argeaaspecific dae as opposed o e usual sooing in ic a arge is reaced asympoically Because e general algorim involves oer complicaions i is useful o poin ou e perurbaion a e use in isolaion from e oer complicaions Suppose a e sysem obeys e folloing scalar difference equaion: α z α z α z d for T Here z is given For T Wriing e equaions ou explicily: z Az α z α z α z d α z T α z T α z T d T Given α 6 and given an arbirary z R e can use ese equaions o compue z z T Bu i as o be e case a z T Az T So e algorim is o adjus z unil e above equaion is saisfied Algorim Based on QZ Decomposiion Te problem e ave o confron in applying e simple algorim in e previous secion is a α is no inverible One ay o adap e algorim applies e QZ decomposiion Tus le Muliply (??) byq : Qα Z H Q α Z H Z z γ Qα ZZ z Q α ZZ z Qα ZZ z Qd Qβ s Qβ s 3
14 Summarizing for T Wrie H G H H D Q [d α z ] z } { H γ H γ Qα Zγ Q[d β s β s ] H H γ H γ D G H H d γ µ γ γ Z z µ L z L z ere H and H are upper riangular and e diagonal elemens of G are non-zero ile e l diagonal elemens of H are all zero I is necessary o verify numerically a all e elemens of H are zero We assume a e diagonal elemens of H are all non-zero Also d d β s β s Ten e sysem is rien G H γ γ G H γ 3 γ 3 G H γ T γ T G H γ T γ T G H H G H H G H H G H H γ γ γ γ γ T γ T γ T γ T D D D D D T D T D T D T ereeaveimposedh We ave found a numerically is is a propery of our model To simulae is sysem forard noe firs a D is deermined because γ Fix avalueforγ and compue: γ H D For : For T : D Q (d Qα Zγ ) γ H D γ G H γ G γ H γ D D Q (d α Zγ ) γ H D γ G H γ G γ H γ D 4
15 We no ave γ T γ T D T Recall a in period T so a afer muliplying by Z : z T Az T γ T Ãγ T Ã Z AZ µ γ T γ T Ã Ã γ T We mus sill saisfy e T equilibrium condiions: G H γ T G H γ γ T T H γ T D T D T Noe oever a e boom se of equaions are saisfied because of e ay γ T as cosen and because γ T does no ener ese equaions Te firs se of equaions need no be saisfied oever and so e use e requiremen a ese be saisfied o pin don γ In paricular e adjus γ unil e folloing expression is saisfied: G γ T H γ T G γ T H γ T D T Noe a is is a number of equaions equal o e dimension of γ 3 Exending e Algorim We no address e possibiliy a and T Ta is e loer bound sars o bind in some period afer e discoun rae goes negaive and before i urns posiive again Tus e loer bound is no binding for i is binding for and i is no binding for > Because e assume T e can apply a sraigforard adapaion of e algorim in e previous secion Firs e d sequence needs o be adjused so a e consan vec d in (??) is only urned on for Second e require e QZ decomposiion of e sysem bo for e ime en e loer bound is binding and e ime en i is binding: Qα Z H Qα Z H Qα Z H Q α Z H γ Z z γ Z z 3Te Iniial Non-Binding Regime For : α z α z [α z β s β s ] 5
16 To solve ese equaions proceed as before Afer applying e QZ decomposiion: G H γ G H γ γ D H γ D G H γ 3 G H γ γ D 3 H γ D G H γ G H γ γ H D γ D G H γ G H γ γ H D γ D Te basic idea of e simulaion is a e sar a given period i (γ γ ) and use e period equaion o solve forard o obain γ γ Tis ould be compleely sraigforard and sandard ifeleadmarixineqzdecomposiion ofedynamic equaion ere inverible I is no So o do e simulaion e compue γ using e equaion Ten ere is only γ o compue using e period equaion Tis compuaion is possible because e relevan block in e lead marix is inverible To begin e simulaion noe firs a D is deermined because z Fix a value for γ and compue: For : γ H D D Q (d α Zγ ) (consan erm in period equaion) γ H D (solving period equaion for γ ) γ G H γ G γ H γ D (using period equaion o find γ ) Weproceedinisayineacperiod : D Q (d α Zγ ) γ H D γ G H γ G γ H γ D Period requires special reamen because e subsequen period s equaion belongs o a differen regime We firs solve for γ using e equaion Te consan erm in e equaion is: µ µ γ D Q d α Z γ Noe a e Q ere belongs o e binding regime ile Z belongs o e non-binding regime We require e Z from e non-binding regime because a is needed o consruc e consan erm is z andaeacuallyaveinandaispoinisγ Z z Wi D in and e compue γ : ³ γ H D 6
17 We no reurn o e equaion o seek γ Te equaion is: α z α z [α z β s β s ] α Z γ α z [α z β s β s ] No apply e QZ decomposiion relevan for e non-binding regime: Qα ZZ Z γ Qα ZZ z D D [α z β s β s ] Le H Z Z γ H γ D Z Z M M {z} (m l) (m l) M {z} l (m l) M {z} (m l) l M {z} l l ere m denoes e leng of z and m l is e rank of α Ten e previous sysem can be rien: G H {z} M {z} M {z} γ {z} (m l) (m l) (m l) l (m l) (m l) (m l) l {z} (m l) {z} {z} M {z} M {z} γ {z} G H γ H D γ D l (m l) l l l (m l) l l l G M H M G M H M γ γ G H H γ γ D D We are no in a posiion o solve for γ Wriing ou e firs of e above equaions: G M H M γ G M H M γ G γ H γ D so a γ G M H M G M H M γ G γ H γ D 3Te Binding Regime We no urn o e period en e loer bound consrain on e ineres rae is binding Teequaionobesolvedis: α z α z [α z d β s β s ] Muliply by Q H γ H γ D 7
18 G H γ γ G H γ γ G H γ γ G H γ γ G H H G H H G H H G H H γ γ γ γ γ 3 γ 3 γ γ D D D D D 3 D 3 D D We ave γ in and Consider firs Asbeforeemuscompue γ using e period equaion Tus D Q ³d α Z γ γ ³ H D Ten using e period equaion: γ G H γ G γ H γ D i We proceed in is ay in eac period : D Q ³d α Z γ γ γ ³ H G D H γ G γ H γ D i Te equaion requires special adjusmens analogous o e ones used a e end of e non-binding regime because solving e equaion requires orking i e equaion firs Te consan erm in e equaion is: µ µ γ D Q d α Z γ As before Q is par of e QZ decomposiion relevan o e non-binding regime bu Z belongs o e binding regime because e ave γ in and and is mus be convered o z Wi D in and e compue γ as follos: γ H D We no reurn o e equaion: α z α Z γ α Z γ d β s β s i 8
19 afer muliplying by Q : H Z Zγ H γ D ere D is available from e previous compuaions Wriing is ou more carefully G H M M γ G M M γ H γ D H γ D ere M M M Z M Z ( M ) M Wriing ou e firs of e above equaions: G M H M i γ G M H M i γ G γ H γ D γ G M H M i ³ G M H M γ G γ H γ D i 33Te Final Non-Binding Regime Given γ γ e no solve e equaions in e non-binding regime T Consider period firs: α z α z [α z β s β s ] Muliplying by Q and applying e QZ decomposiion: Qα ZZ z Qα ZZ z Q [α z β s β s ] H γ H γ D G H γ γ G H H γ γ D D To solve for γ γ e firs obain γ using e equaion: D Q d α Zγ (consan erm in period equaion) γ H D (solving period equaion for γ ) Ten γ G H γ G γ H γ D For T : D Q (d α Zγ ) γ H D γ G H γ G γ H γ D 9
20 We no ave γ T γ T D T Recall a s for T so a afer muliplying by Z : z T Az T γ T Ãγ T Ã Z AZ µ γ T γ T Ã Ã γ T We mus sill saisfy e T equilibrium condiions: G H γ T G H γ γ T T H γ T D T D T Noe oever a e boom se of equaions are saisfied because of e ay γ T as cosen and because γ T does no ener ese equaions Te firs se of equaions need nobesaisfied oever and so e use e requiremen a ese be saisfied o pin don γ T In paricular e adjus γ unil e folloing expression is saisfied: G γ T H γ T G γ T H γ T D T Noe a is is a number of equaions equal o e dimension of γ
Technical Appendix for DSGE Models for Monetary Policy Analysis
Technical Appendix for DSGE Models for Moneary Policy Analysis by Larence J Chrisiano, Mahias Traband, Karl Walenin A Daa Appendix A Daa Sources FRED2: Daabase of he Federal Reserve Bank of S Louis available
Διαβάστε περισσότεραA note on deriving the New Keynesian Phillips Curve under positive steady state inflation
A noe on deriving he New Keynesian Phillips Curve under posiive seady sae inflaion Hashma Khan Carleon Univerisiy Barbara Rudolf Swiss Naional Bank Firs version: February 2005 This version: July 2005 Absrac
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 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 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 περισσότεραA Suite of Models for Dynare Description of Models
A Suie of Models for Dynare Descripion of Models F. Collard, H. Dellas and B. Diba Version. Deparmen of Economics Universiy of Bern A REAL BUSINESS CYCLE MODEL A real Business Cycle Model The problem of
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 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 περισσότεραAppendix. 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 περισσότεραA Simple Version of the Lucas Model
Aricle non publié May 11, 2007 A Simple Version of he Lucas Model Mazamba Tédie Absrac This discree-ime version of he Lucas model do no include he physical capial. We inregrae in he uiliy funcion he leisure
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 περισσότεραThe Euler Equations! λ 1. λ 2. λ 3. ρ ρu. E = e + u 2 /2. E + p ρ. = de /dt. = dh / dt; h = h( T ); c p. / c v. ; γ = c p. p = ( γ 1)ρe. c v.
hp://www.nd.ed/~gryggva/cfd-corse/ The Eler Eqaions The Eler Eqaions The Eler eqaions for D flow: + + p = x E E + p where Define E = e + / H = h + /; h = e + p/ Gréar Tryggvason Spring 3 Ideal Gas: p =
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 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 περισσότεραLecture 6. Goals: Determine the optimal threshold, filter, signals for a binary communications problem VI-1
Lecue 6 Goals: Deemine e opimal esold, file, signals fo a binay communicaions poblem VI- Minimum Aveage Eo Pobabiliy Poblem: Find e opimum file, esold and signals o minimize e aveage eo pobabiliy. s s
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 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 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 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 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 περισσότεραMark-up Fluctuations and Fiscal Policy Stabilization in a Monetary Union: Technical appendices not for publication
Mark-up lucuaions and iscal Policy Sabilizaion in a Moneary Union: Technical appendices no for publicaion M. W. J. B Universiy of Amserdam and CEP J Universiy of Copenhagen, CEP and EPU July, 003 Mailing
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 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 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 περισσότεραPARTIAL NOTES for 6.1 Trigonometric Identities
PARTIAL NOTES for 6.1 Trigonometric Identities tanθ = sinθ cosθ cotθ = cosθ sinθ BASIC IDENTITIES cscθ = 1 sinθ secθ = 1 cosθ cotθ = 1 tanθ PYTHAGOREAN IDENTITIES sin θ + cos θ =1 tan θ +1= sec θ 1 + cot
Διαβάστε περισσότεραNumerical Analysis FMN011
Numerical Analysis FMN011 Carmen Arévalo Lund University carmen@maths.lth.se Lecture 12 Periodic data A function g has period P if g(x + P ) = g(x) Model: Trigonometric polynomial of order M T M (x) =
Διαβάστε περισσότεραis the home less foreign interest rate differential (expressed as it
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
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 περισσότεραNotes on New-Keynesian Models
Noes on New-Keynesian Models Marco Del Negro, Frank Schorfheide, FRBNY DSGE Group Sepember 4, 202 Please do no circulae Smes & Wouers Chrisiano, Eichenbaum, & Evans. Define he problem, FOCs, and equilibrium
Διαβάστε περισσότεραOscillation Criteria for Nonlinear Damped Dynamic Equations on Time Scales
Oscillaion Crieria for Nonlinear Damped Dynamic Equaions on ime Scales Lynn Erbe, aher S Hassan, and Allan Peerson Absrac We presen new oscillaion crieria for he second order nonlinear damped delay dynamic
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 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 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 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 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 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 περισσότεραMonetary Policy Design in the Basic New Keynesian Model
Monetary Policy Design in the Basic New Keynesian Model Jordi Galí CREI, UPF and Barcelona GSE June 216 Jordi Galí (CREI, UPF and Barcelona GSE) Monetary Policy Design June 216 1 / 12 The Basic New Keynesian
Διαβάστε περισσότεραProduct Innovation and Optimal Capital Investment under Uncertainty. by Chia-Yu Liao Advisor Ching-Tang Wu
Produc Innovaion and Opimal Capial Invesmen under Uncerainy by Chia-Yu Liao Advisor Ching-Tang Wu Insiue of Saisics, Naional Universiy of Kaohsiung Kaohsiung, Taiwan 8 R.O.C. July 2006 Conens Z`Š zz`š
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 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 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 περισσότεραLifting Entry (continued)
ifting Entry (continued) Basic planar dynamics of motion, again Yet another equilibrium glide Hypersonic phugoid motion Planar state equations MARYAN 1 01 avid. Akin - All rights reserved http://spacecraft.ssl.umd.edu
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 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 περισσότεραChapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
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 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 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 περισσότεραLecture 2. Soundness and completeness of propositional logic
Lecture 2 Soundness and completeness of propositional logic February 9, 2004 1 Overview Review of natural deduction. Soundness and completeness. Semantics of propositional formulas. Soundness proof. Completeness
Διαβάστε περισσότεραLecture 34 Bootstrap confidence intervals
Lecture 34 Bootstrap confidence intervals Confidence Intervals θ: an unknown parameter of interest We want to find limits θ and θ such that Gt = P nˆθ θ t If G 1 1 α is known, then P θ θ = P θ θ = 1 α
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 περισσότεραΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ. Ψηφιακή Οικονομία. Διάλεξη 7η: Consumer Behavior Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Ψηφιακή Οικονομία Διάλεξη 7η: Consumer Behavior Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών Τέλος Ενότητας Χρηματοδότηση Το παρόν εκπαιδευτικό υλικό έχει αναπτυχθεί
Διαβάστε περισσότεραParametrized Surfaces
Parametrized Surfaces Recall from our unit on vector-valued functions at the beginning of the semester that an R 3 -valued function c(t) in one parameter is a mapping of the form c : I R 3 where I is some
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 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 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 περισσότεραHigher Derivative Gravity Theories
Higher Derivative Gravity Theories Black Holes in AdS space-times James Mashiyane Supervisor: Prof Kevin Goldstein University of the Witwatersrand Second Mandelstam, 20 January 2018 James Mashiyane WITS)
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 περισσότεραTrigonometric Formula Sheet
Trigonometric Formula Sheet Definition of the Trig Functions Right Triangle Definition Assume that: 0 < θ < or 0 < θ < 90 Unit Circle Definition Assume θ can be any angle. y x, y hypotenuse opposite θ
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 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 περισσότεραΣυστήματα Διαχείρισης Βάσεων Δεδομένων
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Συστήματα Διαχείρισης Βάσεων Δεδομένων Φροντιστήριο 9: Transactions - part 1 Δημήτρης Πλεξουσάκης Τμήμα Επιστήμης Υπολογιστών Tutorial on Undo, Redo and Undo/Redo
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 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 περισσότεραThe challenges of non-stable predicates
The challenges of non-stable predicates Consider a non-stable predicate Φ encoding, say, a safety property. We want to determine whether Φ holds for our program. The challenges of non-stable predicates
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 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 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 περισσότεραECON 381 SC ASSIGNMENT 2
ECON 8 SC ASSIGNMENT 2 JOHN HILLAS UNIVERSITY OF AUCKLAND Problem Consider a consmer with wealth w who consmes two goods which we shall call goods and 2 Let the amont of good l that the consmer consmes
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 περισσότεραThe canonical 2nd order transfer function is expressed as. (ω n
Second order ransfer funcions nd Order ransfer funcion - Summary of resuls The canonical nd order ransfer funcion is expressed as H(s) s + ζ s + is he naural frequency; ζ is he damping coefficien. The
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 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 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 περισσότεραDémographie spatiale/spatial Demography
ΠΑΝΕΠΙΣΤΗΜΙΟ ΘΕΣΣΑΛΙΑΣ Démographie spatiale/spatial Demography Session 1: Introduction to spatial demography Basic concepts Michail Agorastakis Department of Planning & Regional Development Άδειες Χρήσης
Διαβάστε περισσότεραforms 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 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 περισσότεραIntegrals in cylindrical, spherical coordinates (Sect. 15.7)
Integrals in clindrical, spherical coordinates (Sect. 5.7 Integration in spherical coordinates. Review: Clindrical coordinates. Spherical coordinates in space. Triple integral in spherical coordinates.
Διαβάστε περισσότεραEvery set of first-order formulas is equivalent to an independent set
Every set of first-order formulas is equivalent to an independent set May 6, 2008 Abstract A set of first-order formulas, whatever the cardinality of the set of symbols, is equivalent to an independent
Διαβάστε περισσότεραSecond Order RLC Filters
ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor
Διαβάστε περισσότεραPartial 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 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 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 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 περισσότεραChapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
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 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 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 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 περισσότεραRight Rear Door. Let's now finish the door hinge saga with the right rear door
Right Rear Door Let's now finish the door hinge saga with the right rear door You may have been already guessed my steps, so there is not much to describe in detail. Old upper one file:///c /Documents
Διαβάστε περισσότερα( 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 περισσότεραInternet Appendix for Uncertainty about Government Policy and Stock Prices
Inerne Appendix for Uncerainy abou Governmen Policy and Sock Prices ĽUBOŠ PÁSTOR and PIETRO VERONESI This Inerne Appendix provides proofs and addiional heoreical resuls in suppor of he analysis presened
Διαβάστε περισσότεραFractional Colorings and Zykov Products of graphs
Fractional Colorings and Zykov Products of graphs Who? Nichole Schimanski When? July 27, 2011 Graphs A graph, G, consists of a vertex set, V (G), and an edge set, E(G). V (G) is any finite set E(G) is
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 περισσότεραES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems
ES440/ES911: CFD Chapter 5. Solution of Linear Equation Systems Dr Yongmann M. Chung http://www.eng.warwick.ac.uk/staff/ymc/es440.html Y.M.Chung@warwick.ac.uk School of Engineering & Centre for Scientific
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 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 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 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 περισσότερα