EconoQuantum ISSN: Universidad de Guadalajara México
|
|
- Branden Quinn
- 5 years ago
- Views:
Transcription
1 EooQuatum ISSN: Uiversidad de Guadalajara Méxio Plata Pérez, Leobardo; Calderó, Eduardo A modified versio of Solow-Ramsey model usig Rihard's growth futio EooQuatum, vol. 6, úm. 1, 2009, pp Uiversidad de Guadalajara Zapopa, Jaliso, Méxio Dispoible e: Cómo itar el artíulo Número ompleto Más iformaió del artíulo Págia de la revista e redaly.org Sistema de Iformaió Cietífia Red de Revistas Cietífias de Améria Latia, el Caribe, España y Portugal Proyeto aadémio si fies de luro, desarrollado bajo la iiiativa de aeso abierto
2 A modified versio of Solow-Ramsey model usig Rihard s growth futio Leobardo Plata Pérez Eduardo Calderó 1 Abstrat: We ivestigate the osequees of itroduig Rihard s Growth futio as a produtio futio i Solow-Swa ad Ramsey models. Poverty traps appear i a atural maer. jel lassifiatio: O41, C61. Itrodutio I this paper, we modify two of the foudatioal models of eoomi growth theory: the Solow-Swa model ad the Ramsey model. We mae the same assumptios that appeared i the origial wors, exept the oe that refers to the eolassial produtio tehology. Istead, we itrodue a Rihard s growth futio. This hage permits us to model the growig proess with ireasig returs whe the use of apital per apita is low ad dereasig returs whe the produtio fator is used i large quatities. Rihard s futio has bee used to model growth proesses i biology. This futio geeralizes Logisti futio ad permits to hage the iflexio poit. Our approah is osistet with the miroeoomi oept the three steps of produtio, whih appears i well ow textboos lie Call & Holaha (1983) or Pidy & Rubifeld (1992). The existee of poverty traps is obtaied with tehologies begiig with ireasig returs. The steady-state preseted i Solow (1956) ad Swa (1956) models are obtaied as a speial ase of this approah. We preset four types of equilibrium i the ase of the Solow- Swa model. We itrodue Rihards s futio i the model of Ramsey (1928) too. The typial saddle poit appears as equilibrium i this ase. 1 Faultad de Eoomía de la Uiversidad Autóoma de Sa Luis Potosí. lplata@ uaslp.mx; jealdero@olmex.mx. We tha the fiaial support provided through the CONACYT Projet from the Mexia Govermet ad C09-FRC from UASLP.
3 66 Mesa 1: Eoomía iteraioal y desarrollo Vol. 6. Núm. 1 Geeralized Solow s model Let us assume the Solow model (Barro ad Sala-i-Marti, 2004, preset the stadard formalizatio of this framewor). We itrodue Rihard s produtio futio as follows. A (1) f () ( 1 + e β σ ) 1 λ All parameters are greater tha ero, f(0)>0 meas that there is some free produtio, A is the limit of f() whe goes to ifiity. The futio is always ireasig i, it is ovex whe if ad oave whe if. The poit if is the ifletio poit whih represets the hage from ireasig returs to dereasig returs. Istead of the lassial Iada oditios lim f () 0, lim f () we ow have that the first 0 oditio is the same but the seod beomes f (0)>0. The fudametal equatio is ow: (2) sa ( 1 + e β σ ) 1 λ ( δ + η) From equatio (2) we a obtai four ases of equilibrium. Case 1: Solow s model ( if 0) This ase appears whe the fudametal equatio has oly oe equilibrium poit. This a our whe the tehology always presets dereasig returs. The equilibrium is a stable poit. Oe example of this is obtaied i the ase of A 100; s 0.3; β l3; σ 2; λ 3; δ 0.1; η f() sf() 240
4 A modified versio of Solow-Ramsey model Case 2: Equilibrium with flutuatios i the eoomi growth rate ( if > 0, good equilibrium) The ifletio poit is greater tha zero, eoomi growth rate presets flutuatios before reahig the uique stable steady state, whih is obtaied at high level of produtio. Oe example is obtaied with the followig values of parameters: A 100; s 0.3; β 25; σ 2; λ 5; δ 0.1; η f() sf() * 240 Case 3: Poverty traps ( if > 0, multiple equilibriums) The ifletio poit is greater tha ero but the eoomy presets several equilibriums. It is easy to he that uder our assumptios there are oly three equilibrium poits. Two of them are loally stable ad the oe i the middle is loally ustable. The first equilibrium that is greater tha zero is a poverty trap. Oly ireasig the output ould allow to leave the poverty trap. I this ase, the followig values a give this result, A 150; s 0.3; β 25; σ 0.1; λ 10; δ 0.1; η 0.05 f() 0.15 sf() 41.3q
5 68 Mesa 1: Eoomía iteraioal y desarrollo Vol. 6. Núm. 1 Case 4: Third world i the third world: ( if > 0, bad equilibrium) This ase appears whe we have oly oe equilibrium but δ+η is very large ompared to margial returs of f(). The eoomy reahes a stable state but produtio level is very low. I this ase, the depreiatio rate is destroyig produtio. f() 0.15 sf() * Geeralized Ramsey s model The model of Ramsey (1928) provides the miroeoomi foudatios to moder eoomi growth theory. As it is well ow, the osumer problem is as follows 1 θ Max U(0) e (ρ η)t t 1 1 θ dt s.t. & f () (δ + η) Usig Rihard s futio, it is easy to he that the eessary oditios produe the followig dyamial system & A ( 1 + e β σ ) 1 λ Cosumptio growth rate is therefore, (δ + η) γ & 1 ( θ A 1 + eβ σ ) 1+λ λ σ e β σ δ ρ λ
6 A modified versio of Solow-Ramsey model There are three solutios. I the first two ases, we have the typial saddle poit equilibrium. I the first ase (ase I), we have the Ramsey model beause the margial produtivity of apital is dereasig for all amout of. I the seod ase (ase II), the margial produtivity of apital is ireasig for small quatities of ad deeasig for large values of. Case I: A 100; β l3; σ 2; λ 3; δ 0.1; η 0.025; ρ Case II: A 100; β 25; σ 2; λ 5; δ 0.1; η 0.025; ρ I the last ase, as i ase III, the margial produtivity of apital is ireasig for small values of ad dereasig for large, but ow we fid that there are two steady states. The first equilibrium, as show i the graph below, is a ustable equilibrium. The seod oe is a saddle poit. The stable trajetory is show i the graph for the followig parameters. 2 2 The other trajetories are disarded for violatig the optimality oditios.
7 70 Mesa 1: Eoomía iteraioal y desarrollo Vol. 6. Núm. 1 Case III: A 150; β 25; σ 0.1; λ 10; δ 0.20; η 0.05; ρ Coludig remar The ilusio of heterogeeous agets i this framewor will be importat for future researh. Relatio betwee iome distributio ad growth rates a be explored i this model. Referees Barro, Robert J., Sala-i-Marti Xavier (2004). Eoomi Growth, New Yor; M Graw Hill. Call, Steve ad William Holaha (1983). Mireoeoomía 2ª Ediió, Editorial Iterameriaa. Pidy, Robert ad Daiel Rubifeld (1992). Miroeoomis 2d. Editio, New Yor: MMilla. Ramsey, Fra (1928). A Mathematial Theory of Savig, Eoomi Joural, Deember 1928 No. 38, pp Solow, Robert (1956). A otributio to the theory of Eoomi Growth, Quarterly Joural of Eoomis, Vol. 70, pp Swa, T. W. (1956). Eoomi Growth ad Capital Aumulatio, Eoomi Reord 32 (November) pp
Bernoulli Numbers. n(n+1) = n(n+1)(2n+1) = n(n 1) 2
Beroulli Numbers Beroulli umbers are amed after the great Swiss mathematiia Jaob Beroulli5-705 who used these umbers i the power-sum problem. The power-sum problem is to fid a formula for the sum of the
More informationANOTHER PROOF FOR FERMAT S LAST THEOREM 1. INTRODUCTION
ANOTHER PROOF FOR FERMAT S LAST THEOREM Mugur B. RĂUŢ Correspodig author: Mugur B. RĂUŢ, E-mail: m_b_raut@yahoo.om Abstrat I this paper we propose aother proof for Fermat s Last Theorem (FLT). We foud
More informationFluids Lecture 2 Notes
Fluids Leture Notes. Airfoil orte Sheet Models. Thi-Airfoil Aalysis Problem Readig: Aderso.,.7 Airfoil orte Sheet Models Surfae orte Sheet Model A aurate meas of represetig the flow about a airfoil i a
More informationConstruction of Control Chart for Random Queue Length for (M / M / c): ( / FCFS) Queueing Model Using Skewness
Iteratioal Joural of Sietifi ad Researh Publiatios, Volume, Issue, Deember ISSN 5-5 Costrutio of Cotrol Chart for Radom Queue Legth for (M / M / ): ( / FCFS) Queueig Model Usig Skewess Dr.(Mrs.) A.R. Sudamai
More informationThe beta density, Bayes, Laplace, and Pólya
The beta desity, Bayes, Laplae, ad Pólya Saad Meimeh The beta desity as a ojugate form Suppose that is a biomial radom variable with idex ad parameter p, i.e. ( ) P ( p) p ( p) Applyig Bayes s rule, we
More informationOptimal Management of the Spare Parts Stock at Their Regular Distribution
Joural of Evirometal Siee ad Egieerig 7 (018) 55-60 doi:10.1765/16-598/018.06.005 D DVID PUBLISHING Optimal Maagemet of the Spare Parts Stok at Their Regular Distributio Svetozar Madzhov Forest Researh
More informationNoah Williams Economics 312. University of Wisconsin Spring Midterm Examination Solutions 1 FOR GRADUATE STUDENTS ONLY
Noah Williams Ecoomics 32 Departmet of Ecoomics Macroecoomics Uiversity of Wiscosi Sprig 204 Midterm Examiatio Solutios FOR GRADUATE STUDENTS ONLY Istructios: This is a 75 miute examiatio worth 00 total
More informationCertain inclusion properties of subclass of starlike and convex functions of positive order involving Hohlov operator
Iteratioal Joural of Pure ad Applied Mathematial Siees. ISSN 0972-9828 Volume 0, Number (207), pp. 85-97 Researh Idia Publiatios http://www.ripubliatio.om Certai ilusio properties of sublass of starlike
More informationSx [ ] = x must yield a
Math -b Leture #5 Notes This wee we start with a remider about oordiates of a vetor relative to a basis for a subspae ad the importat speial ase where the subspae is all of R. This freedom to desribe vetors
More informationNonstandard Lorentz-Einstein transformations
Nostadard Loretz-istei trasformatios Berhard Rothestei 1 ad Stefa Popesu 1) Politehia Uiversity of Timisoara, Physis Departmet, Timisoara, Romaia brothestei@gmail.om ) Siemes AG, rlage, Germay stefa.popesu@siemes.om
More informationLesson 4. Thermomechanical Measurements for Energy Systems (MENR) Measurements for Mechanical Systems and Production (MMER)
Lesso 4 Thermomehaial Measuremets for Eergy Systems (MENR) Measuremets for Mehaial Systems ad Produtio (MMER) A.Y. 15-16 Zaaria (Rio ) Del Prete RAPIDITY (Dyami Respose) So far the measurad (the physial
More informationAbstract. Fermat's Last Theorem Proved on a Single Page. "The simplest solution is usually the best solution"---albert Einstein
Copyright A. A. Frempog Fermat's Last Theorem Proved o a Sigle Page "5% of the people thik; 0% of the people thik that they thik; ad the other 85% would rather die tha thik."----thomas Ediso "The simplest
More informationSYNTHESIS OF SIGNAL USING THE EXPONENTIAL FOURIER SERIES
SYNTHESIS OF SIGNAL USING THE EXPONENTIAL FOURIER SERIES Sadro Adriao Fasolo ad Luiao Leoel Medes Abstrat I 748, i Itrodutio i Aalysi Ifiitorum, Leohard Euler (707-783) stated the formula exp( jω = os(
More informationTHE MEASUREMENT OF THE SPEED OF THE LIGHT
THE MEASUREMENT OF THE SPEED OF THE LIGHT Nyamjav, Dorjderem Abstrat The oe of the physis fudametal issues is a ature of the light. I this experimet we measured the speed of the light usig MihelsoÕs lassial
More informationSummation Method for Some Special Series Exactly
The Iteratioal Joural of Mathematis, Siee, Tehology ad Maagemet (ISSN : 39-85) Vol. Issue Summatio Method for Some Speial Series Eatly D.A.Gismalla Deptt. Of Mathematis & omputer Studies Faulty of Siee
More informationDigital Signal Processing. Homework 2 Solution. Due Monday 4 October Following the method on page 38, the difference equation
Digital Sigal Proessig Homework Solutio Due Moda 4 Otober 00. Problem.4 Followig the method o page, the differee equatio [] (/4[-] + (/[-] x[-] has oeffiiets a0, a -/4, a /, ad b. For these oeffiiets A(z
More informationSociété de Calcul Mathématique SA Mathematical Modelling Company, Corp.
oiété de Calul Mathéatique A Matheatial Modellig Copay, Corp. Deisio-aig tools, sie 995 iple Rado Wals Part V Khihi's Law of the Iterated Logarith: Quatitative versios by Berard Beauzay August 8 I this
More informationSOME NOTES ON INEQUALITIES
SOME NOTES ON INEQUALITIES Rihard Hoshio Here are four theorems that might really be useful whe you re workig o a Olympiad problem that ivolves iequalities There are a buh of obsure oes Chebyheff, Holder,
More informationTopic 1 2: Sequences and Series. A sequence is an ordered list of numbers, e.g. 1, 2, 4, 8, 16, or
Topic : Sequeces ad Series A sequece is a ordered list of umbers, e.g.,,, 8, 6, or,,,.... A series is a sum of the terms of a sequece, e.g. + + + 8 + 6 + or... Sigma Notatio b The otatio f ( k) is shorthad
More informationLecture 8. Dirac and Weierstrass
Leture 8. Dira ad Weierstrass Audrey Terras May 5, 9 A New Kid of Produt of Futios You are familiar with the poitwise produt of futios de ed by f g(x) f(x) g(x): You just tae the produt of the real umbers
More informationObserver Design with Reduced Measurement Information
Observer Desig with Redued Measuremet Iformatio I pratie all the states aot be measured so that SVF aot be used Istead oly a redued set of measuremets give by y = x + Du p is available where y( R We assume
More informationUniform Strict Practical Stability Criteria for Impulsive Functional Differential Equations
Global Joural of Sciece Frotier Research Mathematics ad Decisio Scieces Volume 3 Issue Versio 0 Year 03 Type : Double Blid Peer Reviewed Iteratioal Research Joural Publisher: Global Jourals Ic (USA Olie
More informationKeeping Up with the Joneses: Who Loses Out? School of Economics & Finance Discussion Papers. David Ulph
Shool of Eoomis & Fiae Olie Disussio Paper Series iss 2055-303X http://ideas.repe.org/s/sa/wpeo.html ifo: eo@st-adrews.a.uk Shool of Eoomis & Fiae Disussio Papers Keepig Up with the Joeses: Who Loses Out?
More informationChapter 8 Hypothesis Testing
Chapter 8 for BST 695: Speial Topis i Statistial Theory Kui Zhag, Chapter 8 Hypothesis Testig Setio 8 Itrodutio Defiitio 8 A hypothesis is a statemet about a populatio parameter Defiitio 8 The two omplemetary
More informationLocal Estimates for the Koornwinder Jacobi-Type Polynomials
Available at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 93-9466 Vol. 6 Issue (Jue 0) pp. 6 70 (reviously Vol. 6 Issue pp. 90 90) Appliatios ad Applied Mathematis: A Iteratioal Joural (AAM) Loal Estimates
More informationCertain Aspects of Univalent Function with Negative Coefficients Defined by Bessel Function
Egieerig, Tehology ad Tehiques Vol59: e66044, Jauary-Deember 06 http://dxdoiorg/0590/678-434-066044 ISSN 678-434 Olie Editio BRAZILIAN ARCHIVES OF BIOLOGY AND TECHNOLOGY A N I N T E R N A T I O N A L J
More informationε > 0 N N n N a n < ε. Now notice that a n = a n.
4 Sequees.5. Null sequees..5.. Defiitio. A ull sequee is a sequee (a ) N that overges to 0. Hee, by defiitio of (a ) N overges to 0, a sequee (a ) N is a ull sequee if ad oly if ( ) ε > 0 N N N a < ε..5..
More informationSolutions 3.2-Page 215
Solutios.-Page Problem Fid the geeral solutios i powers of of the differetial equatios. State the reurree relatios ad the guarateed radius of overgee i eah ase. ) Substitutig,, ad ito the differetial equatio
More informationFINALTERM EXAMINATION Fall 9 Calculus & Aalytical Geometry-I Questio No: ( Mars: ) - Please choose oe Let f ( x) is a fuctio such that as x approaches a real umber a, either from left or right-had-side,
More informationAfter the completion of this section the student. V.4.2. Power Series Solution. V.4.3. The Method of Frobenius. V.4.4. Taylor Series Solution
Chapter V ODE V.4 Power Series Solutio Otober, 8 385 V.4 Power Series Solutio Objetives: After the ompletio of this setio the studet - should reall the power series solutio of a liear ODE with variable
More informationMicron School of Materials Science and Engineering. Problem Set 7 Solutions
Problem Set 7 Solutios 1. I class, we reviewed several dispersio relatios (i.e., E- diagrams or E-vs- diagrams) of electros i various semicoductors ad a metal. Fid a dispersio relatio that differs from
More informationExplicit and closed formed solution of a differential equation. Closed form: since finite algebraic combination of. converges for x x0
Chapter 4 Series Solutios Epliit ad losed formed solutio of a differetial equatio y' y ; y() 3 ( ) ( 5 e ) y Closed form: sie fiite algebrai ombiatio of elemetary futios Series solutio: givig y ( ) as
More informationCHAPTER 5 SOME MINIMAX AND SADDLE POINT THEOREMS
CHAPTR 5 SOM MINIMA AND SADDL POINT THORMS 5. INTRODUCTION Fied poit theorems provide importat tools i game theory which are used to prove the equilibrium ad eistece theorems. For istace, the fied poit
More informationNonparametric Goodness-of-Fit Tests for Discrete, Grouped or Censored Data 1
Noparametri Goodess-of-Fit Tests for Disrete, Grouped or Cesored Data Boris Yu. Lemeshko, Ekateria V. Chimitova ad Stepa S. Kolesikov Novosibirsk State Tehial Uiversity Departmet of Applied Mathematis
More information1.3 Convergence Theorems of Fourier Series. k k k k. N N k 1. With this in mind, we state (without proof) the convergence of Fourier series.
.3 Covergece Theorems of Fourier Series I this sectio, we preset the covergece of Fourier series. A ifiite sum is, by defiitio, a limit of partial sums, that is, a cos( kx) b si( kx) lim a cos( kx) b si(
More informationChapter 4. Fourier Series
Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,
More informationSection 1.1. Calculus: Areas And Tangents. Difference Equations to Differential Equations
Differece Equatios to Differetial Equatios Sectio. Calculus: Areas Ad Tagets The study of calculus begis with questios about chage. What happes to the velocity of a swigig pedulum as its positio chages?
More informationSection 13.3 Area and the Definite Integral
Sectio 3.3 Area ad the Defiite Itegral We ca easily fid areas of certai geometric figures usig well-kow formulas: However, it is t easy to fid the area of a regio with curved sides: METHOD: To evaluate
More informationChapter 1. Complex Numbers. Dr. Pulak Sahoo
Chapter 1 Complex Numbers BY Dr. Pulak Sahoo Assistat Professor Departmet of Mathematics Uiversity Of Kalyai West Begal, Idia E-mail : sahoopulak1@gmail.com 1 Module-2: Stereographic Projectio 1 Euler
More informationCOMP26120: Introducing Complexity Analysis (2018/19) Lucas Cordeiro
COMP60: Itroduig Complexity Aalysis (08/9) Luas Cordeiro luas.ordeiro@mahester.a.uk Itroduig Complexity Aalysis Textbook: Algorithm Desig ad Appliatios, Goodrih, Mihael T. ad Roberto Tamassia (hapter )
More informationChapter 5: Take Home Test
Chapter : Take Home Test AB Calulus - Hardtke Name Date: Tuesday, / MAY USE YOUR CALCULATOR FOR THIS PAGE. Roud aswers to three plaes. Sore: / Show diagrams ad work to justify eah aswer.. Approimate the
More informationAppendix: The Laplace Transform
Appedix: The Laplace Trasform The Laplace trasform is a powerful method that ca be used to solve differetial equatio, ad other mathematical problems. Its stregth lies i the fact that it allows the trasformatio
More informationExample: Find the SD of the set {x j } = {2, 4, 5, 8, 5, 11, 7}.
1 (*) If a lot of the data is far from the mea, the may of the (x j x) 2 terms will be quite large, so the mea of these terms will be large ad the SD of the data will be large. (*) I particular, outliers
More informationWRITTEN ASSIGNMENT 1 ANSWER KEY
CISC 65 Itrodutio Desig ad Aalysis of Algorithms WRITTEN ASSIGNMENT ANSWER KEY. Problem -) I geeral, this problem requires f() = some time period be solve for a value. This a be doe for all ase expet lg
More informationKeeping Up with the Joneses: Who Loses Out? School of Economics & Finance Discussion Papers. David Ulph
Shool of Eoomis & Fiae Olie Disussio Paper Series iss 2055-303X http://ideas.repe.org/s/sa/wpeo.html ifo: eo@st-adrews.a.uk Shool of Eoomis & Fiae Disussio Papers Keepig Up with the Joeses: Who Loses Out?
More informationPrincipal Component Analysis. Nuno Vasconcelos ECE Department, UCSD
Priipal Compoet Aalysis Nuo Vasoelos ECE Departmet, UCSD Curse of dimesioality typial observatio i Bayes deisio theory: error ireases whe umber of features is large problem: eve for simple models (e.g.
More informationHomework 6: Forced Vibrations Due Friday April 6, 2018
EN40: Dyais ad Vibratios Hoework 6: Fored Vibratios Due Friday April 6, 018 Shool of Egieerig Brow Uiversity 1. The vibratio isolatio syste show i the figure has 0kg, k 19.8 kn / 1.59 kns / If the base
More informationAnalog Filter Synthesis
6 Aalog Filter Sythesis Nam Pham Aubur Uiversity Bogda M. Wilamowsi Aubur Uiversity 6. Itrodutio...6-6. Methods to Sythesize Low-Pass Filter...6- Butterworth Low-Pass Filter Chebyshev Low-Pass Filter Iverse
More informationFermat s Little Theorem. mod 13 = 0, = }{{} mod 13 = 0. = a a a }{{} mod 13 = a 12 mod 13 = 1, mod 13 = a 13 mod 13 = a.
Departmet of Mathematical Scieces Istructor: Daiva Puciskaite Discrete Mathematics Fermat s Little Theorem 43.. For all a Z 3, calculate a 2 ad a 3. Case a = 0. 0 0 2-times Case a 0. 0 0 3-times a a 2-times
More informationMODEL TEST PAPER II Time : hours Maximum Marks : 00 Geeral Istructios : (i) (iii) (iv) All questios are compulsory. The questio paper cosists of 9 questios divided ito three Sectios A, B ad C. Sectio A
More informationRecurrence Relations
Recurrece Relatios Aalysis of recursive algorithms, such as: it factorial (it ) { if (==0) retur ; else retur ( * factorial(-)); } Let t be the umber of multiplicatios eeded to calculate factorial(). The
More informationME260W Mid-Term Exam Instructor: Xinyu Huang Date: Mar
ME60W Mid-Term Exam Istrutor: Xiyu Huag Date: Mar-03-005 Name: Grade: /00 Problem. A atilever beam is to be used as a sale. The bedig momet M at the gage loatio is P*L ad the strais o the top ad the bottom
More informationA NOTE ON THE TOTAL LEAST SQUARES FIT TO COPLANAR POINTS
A NOTE ON THE TOTAL LEAST SQUARES FIT TO COPLANAR POINTS STEVEN L. LEE Abstract. The Total Least Squares (TLS) fit to the poits (x,y ), =1,,, miimizes the sum of the squares of the perpedicular distaces
More information62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +
62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of
More information6.3 Testing Series With Positive Terms
6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial
More informationDETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS.
ICSV4 Cairs Australia 9- July 7 DTRMINATION OF MCHANICAL PROPRTIS OF A NON- UNIFORM BAM USING TH MASURMNT OF TH XCITD LONGITUDINAL LASTIC VIBRATIONS Pavel Aokhi ad Vladimir Gordo Departmet of the mathematics
More informationBangi 43600, Selangor Darul Ehsan, Malaysia (Received 12 February 2010, accepted 21 April 2010)
O Cesáro Meas of Order μ for Outer Fuctios ISSN 1749-3889 (prit), 1749-3897 (olie) Iteratioal Joural of Noliear Sciece Vol9(2010) No4,pp455-460 Maslia Darus 1, Rabha W Ibrahim 2 1,2 School of Mathematical
More informationExponential and Trigonometric Functions Lesson #1
Epoetial ad Trigoometric Fuctios Lesso # Itroductio To Epoetial Fuctios Cosider a populatio of 00 mice which is growig uder plague coditios. If the mouse populatio doubles each week we ca costruct a table
More information3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,
3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [
More informationCOMPUTING SUMS AND THE AVERAGE VALUE OF THE DIVISOR FUNCTION (x 1) + x = n = n.
COMPUTING SUMS AND THE AVERAGE VALUE OF THE DIVISOR FUNCTION Abstract. We itroduce a method for computig sums of the form f( where f( is ice. We apply this method to study the average value of d(, where
More informationPhysics 116A Solutions to Homework Set #1 Winter Boas, problem Use equation 1.8 to find a fraction describing
Physics 6A Solutios to Homework Set # Witer 0. Boas, problem. 8 Use equatio.8 to fid a fractio describig 0.694444444... Start with the formula S = a, ad otice that we ca remove ay umber of r fiite decimals
More informationSpectral Partitioning in the Planted Partition Model
Spectral Graph Theory Lecture 21 Spectral Partitioig i the Plated Partitio Model Daiel A. Spielma November 11, 2009 21.1 Itroductio I this lecture, we will perform a crude aalysis of the performace of
More informationYou may work in pairs or purely individually for this assignment.
CS 04 Problem Solvig i Computer Sciece OOC Assigmet 6: Recurreces You may work i pairs or purely idividually for this assigmet. Prepare your aswers to the followig questios i a plai ASCII text file or
More informationClass #25 Wednesday, April 19, 2018
Cla # Wedesday, April 9, 8 PDE: More Heat Equatio with Derivative Boudary Coditios Let s do aother heat equatio problem similar to the previous oe. For this oe, I ll use a square plate (N = ), but I m
More information16th International Symposium on Ballistics San Francisco, CA, September 1996
16th Iteratioal Symposium o Ballistis Sa Fraiso, CA, 3-8 September 1996 GURNEY FORULAS FOR EXPLOSIVE CHARGES SURROUNDING RIGID CORES William J. Flis, Dya East Corporatio, 36 Horizo Drive, Kig of Prussia,
More informationSabotage in a Fishery
Sabotage i a Fishery Ngo Va Log Departmet of Eoomis, MGill Uiversity, Motreal H3A 2T7, Caada ad Stephaie F. MWhiie Shool of Eoomis, Uiversity of Adelaide, SA 5005, Australia Prelimiary ad Iomplete - Commets
More informationGeneral IxJ Contingency Tables
page1 Geeral x Cotigecy Tables We ow geeralize our previous results from the prospective, retrospective ad cross-sectioal studies ad the Poisso samplig case to x cotigecy tables. For such tables, the test
More informationLecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting
Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would
More informationChapter 2 The Monte Carlo Method
Chapter 2 The Mote Carlo Method The Mote Carlo Method stads for a broad class of computatioal algorithms that rely o radom sampligs. It is ofte used i physical ad mathematical problems ad is most useful
More informationMonotonic redistribution of non-negative allocations: a case for proportional taxation revisited
Mootoi redistributio of o-egative alloatios: a ase for proportioal taxatio revisited Adré Casajus a a Eoomis ad Iformatio Systems, HHL Leipzig Graduate Shool of Maagemet Jahallee 59, 0409 Leipzig, Germay
More informationBecause it tests for differences between multiple pairs of means in one test, it is called an omnibus test.
Math 308 Sprig 018 Classes 19 ad 0: Aalysis of Variace (ANOVA) Page 1 of 6 Itroductio ANOVA is a statistical procedure for determiig whether three or more sample meas were draw from populatios with equal
More informationOn generalized Simes critical constants
Biometrial Joural 56 04 6, 035 054 DOI: 0.00/bimj.030058 035 O geeralized Simes ritial ostats Jiagtao Gou ad Ajit C. Tamhae, Departmet of Statistis, Northwester Uiversity, 006 Sherida Road, Evasto, IL
More informationMATH CALCULUS II Objectives and Notes for Test 4
MATH 44 - CALCULUS II Objectives ad Notes for Test 4 To do well o this test, ou should be able to work the followig tpes of problems. Fid a power series represetatio for a fuctio ad determie the radius
More informationFixed Point Approximation of Weakly Commuting Mappings in Banach Space
BULLETIN of the Bull. Malaysia Math. S. So. (Seod Series) 3 (000) 8-85 MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Fied Poit Approimatio of Weakly Commutig Mappigs i Baah Spae ZAHEER AHMAD AND ABDALLA J. ASAD
More informationLecture 2 Long paths in random graphs
Lecture Log paths i radom graphs 1 Itroductio I this lecture we treat the appearace of log paths ad cycles i sparse radom graphs. will wor with the probability space G(, p) of biomial radom graphs, aalogous
More informationMeasurement uncertainty of the sound absorption
Measuremet ucertaity of the soud absorptio coefficiet Aa Izewska Buildig Research Istitute, Filtrowa Str., 00-6 Warsaw, Polad a.izewska@itb.pl 6887 The stadard ISO/IEC 705:005 o the competece of testig
More informationWhat is a Hypothesis? Hypothesis is a statement about a population parameter developed for the purpose of testing.
What is a ypothesis? ypothesis is a statemet about a populatio parameter developed for the purpose of testig. What is ypothesis Testig? ypothesis testig is a proedure, based o sample evidee ad probability
More informationLecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting
Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would
More informationNumber of fatalities X Sunday 4 Monday 6 Tuesday 2 Wednesday 0 Thursday 3 Friday 5 Saturday 8 Total 28. Day
LECTURE # 8 Mea Deviatio, Stadard Deviatio ad Variace & Coefficiet of variatio Mea Deviatio Stadard Deviatio ad Variace Coefficiet of variatio First, we will discuss it for the case of raw data, ad the
More informationEstimation for Complete Data
Estimatio for Complete Data complete data: there is o loss of iformatio durig study. complete idividual complete data= grouped data A complete idividual data is the oe i which the complete iformatio of
More informationCost arrangement and welfare in a multi-product Cournot oligopoly
Eoomis Worig Papers (00 016) Eoomis 10-3-004 Cost arragemet ad welfare i a multi-produt Courot oligopol Harve E. Lapa Iowa State Uiversit, hlapa@iastate.edu David A. Heess Iowa State Uiversit Follow this
More informationBio-Systems Modeling and Control
Bio-Sytem Modelig ad otrol Leture Ezyme ooperatio i Ezyme Dr. Zvi Roth FAU Ezyme with Multiple Bidig Site May ezyme have more tha oe bidig ite for ubtrate moleule. Example: Hemoglobi Hb, the oxygearryig
More informationHow to Maximize a Function without Really Trying
How to Maximize a Fuctio without Really Tryig MARK FLANAGAN School of Electrical, Electroic ad Commuicatios Egieerig Uiversity College Dubli We will prove a famous elemetary iequality called The Rearragemet
More information1 Approximating Integrals using Taylor Polynomials
Seughee Ye Ma 8: Week 7 Nov Week 7 Summary This week, we will lear how we ca approximate itegrals usig Taylor series ad umerical methods. Topics Page Approximatig Itegrals usig Taylor Polyomials. Defiitios................................................
More informationLinear regression. Daniel Hsu (COMS 4771) (y i x T i β)2 2πσ. 2 2σ 2. 1 n. (x T i β y i ) 2. 1 ˆβ arg min. β R n d
Liear regressio Daiel Hsu (COMS 477) Maximum likelihood estimatio Oe of the simplest liear regressio models is the followig: (X, Y ),..., (X, Y ), (X, Y ) are iid radom pairs takig values i R d R, ad Y
More informationOptimal design of N-Policy batch arrival queueing system with server's single vacation, setup time, second optional service and break down
Ameria. Jr. of Mathematis ad Siees Vol., o.,(jauary Copyright Mid Reader Publiatios www.jouralshub.om Optimal desig of -Poliy bath arrival queueig system with server's sigle vaatio, setup time, seod optioal
More informationInfinite Sequences and Series
Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet
More informationPrinciple Of Superposition
ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give
More informationNUMERICAL METHODS FOR SOLVING EQUATIONS
Mathematics Revisio Guides Numerical Methods for Solvig Equatios Page 1 of 11 M.K. HOME TUITION Mathematics Revisio Guides Level: GCSE Higher Tier NUMERICAL METHODS FOR SOLVING EQUATIONS Versio:. Date:
More informationLecture 7: Properties of Random Samples
Lecture 7: Properties of Radom Samples 1 Cotiued From Last Class Theorem 1.1. Let X 1, X,...X be a radom sample from a populatio with mea µ ad variace σ
More informationAPPENDIX F Complex Numbers
APPENDIX F Complex Numbers Operatios with Complex Numbers Complex Solutios of Quadratic Equatios Polar Form of a Complex Number Powers ad Roots of Complex Numbers Operatios with Complex Numbers Some equatios
More informationImplicit function theorem
Jovo Jaric Implicit fuctio theorem The reader kows that the equatio of a curve i the x - plae ca be expressed F x, =., this does ot ecessaril represet a fuctio. Take, for example F x, = 2x x =. (1 either
More informationβ COMPACT SPACES IN FUZZIFYING TOPOLOGY *
Iraia Joural of Siee & Tehology, Trasatio A, Vol 30, No A3 Prited i The Islami Republi of Ira, 2006 Shiraz Uiversity FUZZ IRRESOLUTE FUNCTIONS AND FUZZ COMPACT SPACES IN FUZZIFING TOPOLOG * O R SAED **
More information(Figure 2.9), we observe x. and we write. (b) as x, x 1. and we write. We say that the line y 0 is a horizontal asymptote of the graph of f.
The symbol for ifiity ( ) does ot represet a real umber. We use to describe the behavior of a fuctio whe the values i its domai or rage outgrow all fiite bouds. For eample, whe we say the limit of f as
More informationHonors Calculus Homework 13 Solutions, due 12/8/5
Hoors Calculus Homework Solutios, due /8/5 Questio Let a regio R i the plae be bouded by the curves y = 5 ad = 5y y. Sketch the regio R. The two curves meet where both equatios hold at oce, so where: y
More informationMatsubara-Green s Functions
Matsubara-Gree s Fuctios Time Orderig : Cosider the followig operator If H = H the we ca trivially factorise this as, E(s = e s(h+ E(s = e sh e s I geeral this is ot true. However for practical applicatio
More informationRiemann Sums y = f (x)
Riema Sums Recall that we have previously discussed the area problem I its simplest form we ca state it this way: The Area Problem Let f be a cotiuous, o-egative fuctio o the closed iterval [a, b] Fid
More informationSolutions to Odd Numbered End of Chapter Exercises: Chapter 4
Itroductio to Ecoometrics (3 rd Updated Editio) by James H. Stock ad Mark W. Watso Solutios to Odd Numbered Ed of Chapter Exercises: Chapter 4 (This versio July 2, 24) Stock/Watso - Itroductio to Ecoometrics
More informationComparison Study of Series Approximation. and Convergence between Chebyshev. and Legendre Series
Applied Mathematical Scieces, Vol. 7, 03, o. 6, 3-337 HIKARI Ltd, www.m-hikari.com http://d.doi.org/0.988/ams.03.3430 Compariso Study of Series Approimatio ad Covergece betwee Chebyshev ad Legedre Series
More informationAreas and Distances. We can easily find areas of certain geometric figures using well-known formulas:
Areas ad Distaces We ca easily fid areas of certai geometric figures usig well-kow formulas: However, it is t easy to fid the area of a regio with curved sides: METHOD: To evaluate the area of the regio
More information