Notes on Tobin s. Liquidity Preference as Behavior toward Risk

Μέγεθος: px
Εμφάνιση ξεκινά από τη σελίδα:

Download "Notes on Tobin s. Liquidity Preference as Behavior toward Risk"

Transcript

1 otes on Tobin s Liquidity Preference s Behvior towrd Risk By Richrd McMinn Revised June 987 Revised subsequently

2 Tobin (Tobin 958 considers portfolio model in which there is one sfe nd one risky sset. The net rte of return is X on the sfe sset nd X on the risky sset. A portfolio consists of dollr mount invested in the sfe sset nd n mount invested in the risky sset where + = w nd w is the investor s initil welth. Let be rndom vrible denoting the return on the portfolio. Then ( ( = + x + + x ( ( = w + x + x x ( nd E μ ( ( = w + x + μ x Vr ( = Vr x = The mount determines both μ nd. The terms on which n investor cn obtin greter expected return t the expense of more risk is μ x μ = w+ + ( x (3 where w. (3 is the investor s trding line. The investor holds the mount = / of the risky sset. Let = λ w. Then μ x μ w = wx + λ w μ w μ x = x + λ w (4 This is clled the cpitl mrket line where λ is the stndrd devition per unit of μ x welth held in the risky sset nd is sometimes clled mrket price of risk.

3 The investor is ssumed to hve preferences which rnk ll (, μ pirs nd these preferences cn be represented by indifference curves. Then the individul mximizes expected utility subect to selecting pir (, μ on the trding line. There re two rtionles for supposing tht ( ( Eμ = f μ, (5 The first is tht ( μ, Let g(y; μ, be the density function of. Then ( ( ( = f ( μ, Eμ = μ y g y; μ, dy (6 nd the shpe of the indifference curve cn be inferred from the shpe of μ. To demonstrte this we perform the following trnsformtion. Let ( = Φ z μ + z μ z =φ( (7 i.e. φ=φ. Then

4 ( ( ( = μ( Φ( z ( = f ( μ, Eμ = Eμ Φ z h z;, dz (8 where z (, nd h is the stndrd norml density. Let Df nd Df denote the prtil derivtives of f with respect to μ nd respectively. Then Df = μ'h Df = μ'zh (9 Since f is constnt on the indifference curve or equivlently = df = Dfdμ + Dfd ( d d μ = Df D f = ( Φ ( ( ( Φ ( ( zu' z h z u' z h z ( Clim: if u > nd u < then dμ d >. Proof. Since the denomintor is clerly positive, it suffices to show tht u < implies ( ( ( zu' Φ z h z < ( ote tht { } (3 = lim zu'h + zu'h where h is symmetric, i.e. h(t = h(-t. Let z = -t. Then nd ( ( ( zu' Φ z h z dz = ( ( ( tu' Φ t h t ( dt { ( ( ( ( ( ( } { ( ( ( ( ( } = lim tu' Φ t h t dt + tu' Φ t h t dt = lim t u' Φ t u' Φ t h t < (4 (5 Since u' ( ( t u' ( ( t Φ > Φ.

5 Comprtive Sttistics Suppose tht u is n incresing concve function nd tht X (, μ. ow suppose μ chnges. Then we wnt to determine wht effect this will hve on the investor s optiml choice of. Recll tht ( z z ( ( Φ = μ + = w + x + μ x +z (6 nd the investor s problem is to select condition is to mximize u( Φ ( z h( z ( ( ( (.The first order u' Φ z μ x + z h z = (7 or equivlently μ x = u'zh u'h (8 ow let the function F:D,D be defined by ( μ = [ μ + ] F, u' x z h (9 Since DF <, it follows by the Implicit Function Theorem tht there exists differentible function f: such tht ( ( ote tht f' < > s DF > <. F μ,f μ = nd f = DF DF. { [ ]} D F = u' + u" μ x + z h [ ] = u'h + u" μ x + z h > ( if the second integrl on the RHS is non-negtive. To determine the sign let u'' u' denote the mesure of bsolute risk version. Assume tht ' nd let z be implicitly defined by Then μ x + z = (i.e. z μ x =. ( Φ ( z ( Φ ( z u'' ( Φ( z,z z u' ( or

6 ( ( ( ( ( ( u'' Φ z Φ z u' Φ z ( which in turn yields ( ( ( ( ( ( ( ( u'' Φ z μ x + z Φ z u' Φ z μ x + z (3 for z z. A similr rgument shows tht (3 holds for z < z. Hence, given ', u'' ( Φ( z ( μ x + z h ( Φ( z u' ( Φ( z ( μ x z + h (4 but the RHS is zero t the optiml. Hence, DF f' μ >. ote tht in Tobin s model (i.e. where x nd so the sfe sset is money f' ( μ > lso implies tht the demnd for money is decresing function of the expected return on the risky sset, which he clls the rte of interest. or equivlently ( ext consider chnge in the riskness of sset one. Let defined s G:D,D, be ( = ( Φ( ( μ + G, u' z x z h (5 Then s bove there exist function g such tht ( ( s DG > <. DG G,g = nd g' = < > DG ( DG = u'z+u''z μ x + z h ( = u'zh + u''z μ x + z h (6 Recll tht the first integrl on the RHS is negtive nd so DG < if the second integrl on the RHS is non-positive. Since u''z( μ x + z h = u'' z ( μ x + z h = u'' ( μ x + z ( μ x ( μ x + z h = u'' ( μ x + z h ( μ x u'' ( μ x +z h (7 It follows tht ' nd μ x suffice to show DG <.

7 Model with Mny Risky Assets Suppose there re risky ssets. Let (,..., = where,,..., = is the dollr mount held of risky sset nd is defined s before. Let x denote the rndom rte of return on sset. Then ( ( = + x + + x ( ( = w + x + x x (8 since w = Let E( x x Then nd = Ex Ex i i i ( ( μ = w + x + μ x (9 = Vr x = i= i i (3 In the specil cse = Vr ( x x E( x x ( E( ( x ( x ( ( ( ( + = + μ + μ = μ + μ = E x μ + E x μ x μ + E x μ = + + The set of points (3 for which μ is constnt is hyperplne. In the cse = { } the w ( + x +( μ ex =μ where e = (,..., nd (,..., shown μ = μ μ is

8 Let denote the vrince-covrince mtrix. Then T =. For = the { ( ( w+ x + μ ex =μ } where e = (,..., nd μ = ( μ,..., μ is shown Let denote the vrince-covrince mtrix. Then T =. For = = (3 ote is rel symmetric mtrix nd so there exists n orthogonl mtrix U such T tht U U is digonl mtrix whose digonl elements re the chrcteristic roots of. Since is rel symmetric mtrix, ll its chrcteristic roots re T n rel. Let U U = D( λ λ is the vector of chrcteristic roots, e. g. where Let D λ λ = ( = Uδ. Then we obtin the eqution λ (33 U U D( (34 = δ δ =δ λ δ = T T T T In sclr form we hve the fmilir eqution (i.e. for the liner opertor in We interpret the trnsformtion so the grph of λδ +λδ = (35 = Uδs trnsformtion of the coordinte system

9 T = (36 is not chnged. However the ltertion mkes the eqution so simple tht the nture of its grph my be determined by inspection. If λ, λ, nd then δ δ + = λ λ / / (37 If / λ > for, then (38 is the eqution of n ellipse. If λ =λ then (39 is circle. If λ nd λ re opposite in sign then (4 is hyperbol. n The chrcteristic roots λ of re ll positive if nd only if the qudrtic T form is positive definite nd the qudrtic form is positive definite if nd only if the leding principl minors of the mtrix of the form re ll positive, i.e. 3 K n >, >, 3 >,..., M O M > n L nn The dominnt re those which minimize subect to fixed vlue of μ. Hence, we hve the problem Minimize T Subect to w ( + x + ( μ + ex = μ

10 Or the LGrnge function ( T L ( δ, = δ w( + x +( μ ex μ (4 The first order conditions re ( ( ( ( DL= + δ μ x = DL= + δ μ x = DL= w + x + μ ex μ = δ (4 In mtrix nottion the first two conditions my be rewritten s = δ( μ ex (43 These conditions my s be expressed s + μ x = + μ x (44 which is the fmilir tngency condition. The LHS is the slope of the ellipse nd the T RHS is the slope of the constnt men line. Since f ( = is homogeneous of degree two the set of points which stisfy (45 or (46 is the liner function L. This result my lso be noted by observing tht t + t + = t + t + (47 Hence the investor holds the risky ssets in fixed proportions, i.e. = k. Thus we my form composite risky sset by letting x = IxI (48 where

11 x I = x (49 I nd = (5 I defines I. Then since = k we obtin x = x + k x + k + k I (5 Then ( ( = w + x + x x (5 I I nd it follows tht μ x μ = w+ + I ( x I (53 is the trding line. References Tobin, J. (958. "Liquidity Preference s Behvior Towrd Risk." Review of Economic Studies 5(:

Oscillatory integrals

Oscillatory integrals Oscilltory integrls Jordn Bell jordn.bell@gmil.com Deprtment of Mthemtics, University of Toronto August, 0 Oscilltory integrls Suppose tht Φ C R d ), ψ DR d ), nd tht Φ is rel-vlued. I : 0, ) C by Iλ)

Διαβάστε περισσότερα

2 Composition. Invertible Mappings

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

Διαβάστε περισσότερα

Solutions 3. February 2, Apply composite Simpson s rule with m = 1, 2, 4 panels to approximate the integrals:

Solutions 3. February 2, Apply composite Simpson s rule with m = 1, 2, 4 panels to approximate the integrals: s Februry 2, 216 1 Exercise 5.2. Apply composite Simpson s rule with m = 1, 2, 4 pnels to pproximte the integrls: () x 2 dx = 1 π/2, (b) cos(x) dx = 1, (c) e x dx = e 1, nd report the errors. () f(x) =

Διαβάστε περισσότερα

Σχολή Εφαρμοσμένων Μαθηματικών και Φυσικών Επιστημών. Εθνικό Μετσόβιο Πολυτεχνείο. Thales Workshop, 1-3 July 2015.

Σχολή Εφαρμοσμένων Μαθηματικών και Φυσικών Επιστημών. Εθνικό Μετσόβιο Πολυτεχνείο. Thales Workshop, 1-3 July 2015. Σχολή Εφαρμοσμένων Μαθηματικών και Φυσικών Επιστημών Εθνικό Μετσόβιο Πολυτεχνείο Thles Worksho, 1-3 July 015 The isomorhism function from S3(L(,1)) to the free module Boštjn Gbrovšek Άδεια Χρήσης Το παρόν

Διαβάστε περισσότερα

Reminders: linear functions

Reminders: linear functions Reminders: linear functions Let U and V be vector spaces over the same field F. Definition A function f : U V is linear if for every u 1, u 2 U, f (u 1 + u 2 ) = f (u 1 ) + f (u 2 ), and for every u U

Διαβάστε περισσότερα

EE512: Error Control Coding

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

Διαβάστε περισσότερα

Every set of first-order formulas is equivalent to an independent set

Every 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 περισσότερα

Example Sheet 3 Solutions

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

Διαβάστε περισσότερα

Ordinal Arithmetic: Addition, Multiplication, Exponentiation and Limit

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

Διαβάστε περισσότερα

ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ ΚΑΙ ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ

ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ ΚΑΙ ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ ΗΜΥ ΔΙΑΚΡΙΤΗ ΑΝΑΛΥΣΗ ΚΑΙ ΔΟΜΕΣ ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ ΚΑΙ ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ ΗΜΥ Διακριτή Ανάλυση και Δομές Χειμερινό Εξάμηνο 6 Σειρά Ασκήσεων Ακέραιοι και Διαίρεση, Πρώτοι Αριθμοί, GCD/LC, Συστήματα

Διαβάστε περισσότερα

INTEGRAL INEQUALITY REGARDING r-convex AND

INTEGRAL INEQUALITY REGARDING r-convex AND J Koren Mth Soc 47, No, pp 373 383 DOI 434/JKMS47373 INTEGRAL INEQUALITY REGARDING r-convex AND r-concave FUNCTIONS WdAllh T Sulimn Astrct New integrl inequlities concerning r-conve nd r-concve functions

Διαβάστε περισσότερα

5. Choice under Uncertainty

5. Choice under Uncertainty 5. Choice under Uncertainty Daisuke Oyama Microeconomics I May 23, 2018 Formulations von Neumann-Morgenstern (1944/1947) X: Set of prizes Π: Set of probability distributions on X : Preference relation

Διαβάστε περισσότερα

Solutions_3. 1 Exercise Exercise January 26, 2017

Solutions_3. 1 Exercise Exercise January 26, 2017 s_3 Jnury 26, 217 1 Exercise 5.2.3 Apply composite Simpson s rule with m = 1, 2, 4 pnels to pproximte the integrls: () x 2 dx = 1 π/2 3, (b) cos(x) dx = 1, (c) e x dx = e 1, nd report the errors. () f(x)

Διαβάστε περισσότερα

AMS 212B Perturbation Methods Lecture 14 Copyright by Hongyun Wang, UCSC. Example: Eigenvalue problem with a turning point inside the interval

AMS 212B Perturbation Methods Lecture 14 Copyright by Hongyun Wang, UCSC. Example: Eigenvalue problem with a turning point inside the interval AMS B Perturbtion Methods Lecture 4 Copyright by Hongyun Wng, UCSC Emple: Eigenvlue problem with turning point inside the intervl y + λ y y = =, y( ) = The ODE for y() hs the form y () + λ f() y() = with

Διαβάστε περισσότερα

CHAPTER (2) Electric Charges, Electric Charge Densities and Electric Field Intensity

CHAPTER (2) Electric Charges, Electric Charge Densities and Electric Field Intensity CHAPTE () Electric Chrges, Electric Chrge Densities nd Electric Field Intensity Chrge Configurtion ) Point Chrge: The concept of the point chrge is used when the dimensions of n electric chrge distriution

Διαβάστε περισσότερα

CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS

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

Διαβάστε περισσότερα

C.S. 430 Assignment 6, Sample Solutions

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

Διαβάστε περισσότερα

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in

Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in Nowhere-zero flows Let be a digraph, Abelian group. A Γ-circulation in is a mapping : such that, where, and : tail in X, head in : tail in X, head in A nowhere-zero Γ-flow is a Γ-circulation such that

Διαβάστε περισσότερα

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

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

Διαβάστε περισσότερα

ST5224: Advanced Statistical Theory II

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

Διαβάστε περισσότερα

HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:

HOMEWORK 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 περισσότερα

Pg The perimeter is P = 3x The area of a triangle is. where b is the base, h is the height. In our case b = x, then the area is

Pg The perimeter is P = 3x The area of a triangle is. where b is the base, h is the height. In our case b = x, then the area is Pg. 9. The perimeter is P = The area of a triangle is A = bh where b is the base, h is the height 0 h= btan 60 = b = b In our case b =, then the area is A = = 0. By Pythagorean theorem a + a = d a a =

Διαβάστε περισσότερα

Other Test Constructions: Likelihood Ratio & Bayes Tests

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

Διαβάστε περισσότερα

Risk! " #$%&'() *!'+,'''## -. / # $

Risk!  #$%&'() *!'+,'''## -. / # $ Risk! " #$%&'(!'+,'''## -. / 0! " # $ +/ #%&''&(+(( &'',$ #-&''&$ #(./0&'',$( ( (! #( &''/$ #$ 3 #4&'',$ #- &'',$ #5&''6(&''&7&'',$ / ( /8 9 :&' " 4; < # $ 3 " ( #$ = = #$ #$ ( 3 - > # $ 3 = = " 3 3, 6?3

Διαβάστε περισσότερα

Congruence Classes of Invertible Matrices of Order 3 over F 2

Congruence Classes of Invertible Matrices of Order 3 over F 2 International Journal of Algebra, Vol. 8, 24, no. 5, 239-246 HIKARI Ltd, www.m-hikari.com http://dx.doi.org/.2988/ija.24.422 Congruence Classes of Invertible Matrices of Order 3 over F 2 Ligong An and

Διαβάστε περισσότερα

SOLUTIONS TO PROBLEMS IN LIE ALGEBRAS IN PARTICLE PHYSICS BY HOWARD GEORGI STEPHEN HANCOCK

SOLUTIONS TO PROBLEMS IN LIE ALGEBRAS IN PARTICLE PHYSICS BY HOWARD GEORGI STEPHEN HANCOCK SOLUTIONS TO PROBLEMS IN LIE ALGEBRAS IN PARTICLE PHYSICS BY HOWARD GEORGI STEPHEN HANCOCK STEPHEN HANCOCK Chpter 6 Solutions 6.A. Clerly NE α+β hs root vector α+β since H i NE α+β = NH i E α+β = N(α+β)

Διαβάστε περισσότερα

Statistical Inference I Locally most powerful tests

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

Διαβάστε περισσότερα

Oscillation of Nonlinear Delay Partial Difference Equations. LIU Guanghui [a],*

Oscillation of Nonlinear Delay Partial Difference Equations. LIU Guanghui [a],* Studies in Mthemtil Sienes Vol. 5, No.,, pp. [9 97] DOI:.3968/j.sms.938455.58 ISSN 93-8444 [Print] ISSN 93-845 [Online] www.snd.net www.snd.org Osilltion of Nonliner Dely Prtil Differene Equtions LIU Gunghui

Διαβάστε περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

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

Διαβάστε περισσότερα

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Chapter 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 περισσότερα

Section 8.3 Trigonometric Equations

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

Διαβάστε περισσότερα

Matrices and Determinants

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

Διαβάστε περισσότερα

Tridiagonal matrices. Gérard MEURANT. October, 2008

Tridiagonal 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 περισσότερα

Problem Set 3: Solutions

Problem 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 περισσότερα

LAPLACE TYPE PROBLEMS FOR A DELONE LATTICE AND NON-UNIFORM DISTRIBUTIONS

LAPLACE TYPE PROBLEMS FOR A DELONE LATTICE AND NON-UNIFORM DISTRIBUTIONS Dedicted to Professor Octv Onicescu, founder of the Buchrest School of Probbility LAPLACE TYPE PROBLEMS FOR A DELONE LATTICE AND NON-UNIFORM DISTRIBUTIONS G CARISTI nd M STOKA Communicted by Mrius Iosifescu

Διαβάστε περισσότερα

Chapter 6: Systems of Linear Differential. be continuous functions on the interval

Chapter 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 περισσότερα

4.6 Autoregressive Moving Average Model ARMA(1,1)

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

Διαβάστε περισσότερα

Depth versus Rigidity in the Design of International Trade Agreements. Leslie Johns

Depth versus Rigidity in the Design of International Trade Agreements. Leslie Johns Depth versus Rigidity in the Design of International Trade Agreements Leslie Johns Supplemental Appendix September 3, 202 Alternative Punishment Mechanisms The one-period utility functions of the home

Διαβάστε περισσότερα

Probability theory STATISTICAL METHODS FOR SAFETY ANALYSIS FMS065 TABLE OF FORMULÆ (2016) Basic probability theory. One-dimensional random variables

Probability theory STATISTICAL METHODS FOR SAFETY ANALYSIS FMS065 TABLE OF FORMULÆ (2016) Basic probability theory. One-dimensional random variables Lund University Centre for Mthemticl Sciences Mthemticl Sttistics STATISTICAL METHODS FOR SAFETY ANALYSIS FMS065 TABLE OF FORMULÆ (06) Probbility theory Bsic probbility theory Let S be smple spce, nd let

Διαβάστε περισσότερα

Mock Exam 7. 1 Hong Kong Educational Publishing Company. Section A 1. Reference: HKDSE Math M Q2 (a) (1 + kx) n 1M + 1A = (1) =

Mock 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 περισσότερα

A Note on Intuitionistic Fuzzy. Equivalence Relation

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

Διαβάστε περισσότερα

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

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

Διαβάστε περισσότερα

Uniform Convergence of Fourier Series Michael Taylor

Uniform 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 περισσότερα

Chapter 7b, Torsion. τ = 0. τ T. T τ D'' A'' C'' B'' 180 -rotation around axis C'' B'' D'' A'' A'' D'' 180 -rotation upside-down C'' B''

Chapter 7b, Torsion. τ = 0. τ T. T τ D'' A'' C'' B'' 180 -rotation around axis C'' B'' D'' A'' A'' D'' 180 -rotation upside-down C'' B'' Chpter 7b, orsion τ τ τ ' D' B' C' '' B'' B'' D'' C'' 18 -rottion round xis C'' B'' '' D'' C'' '' 18 -rottion upside-down D'' stright lines in the cross section (cross sectionl projection) remin stright

Διαβάστε περισσότερα

The challenges of non-stable predicates

The 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 περισσότερα

( )( ) La Salle College Form Six Mock Examination 2013 Mathematics Compulsory Part Paper 2 Solution

( )( ) La Salle College Form Six Mock Examination 2013 Mathematics Compulsory Part Paper 2 Solution L Slle ollege Form Si Mock Emintion 0 Mthemtics ompulsor Prt Pper Solution 6 D 6 D 6 6 D D 7 D 7 7 7 8 8 8 8 D 9 9 D 9 D 9 D 5 0 5 0 5 0 5 0 D 5. = + + = + = = = + = =. D The selling price = $ ( 5 + 00)

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

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

Διαβάστε περισσότερα

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

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

Διαβάστε περισσότερα

Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequality for metrics: Let (X, d) be a metric space and let x, y, z X.

Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequality for metrics: Let (X, d) be a metric space and let x, y, z X. Math 446 Homework 3 Solutions. (1). (i): Reverse triangle inequalit for metrics: Let (X, d) be a metric space and let x,, z X. Prove that d(x, z) d(, z) d(x, ). (ii): Reverse triangle inequalit for norms:

Διαβάστε περισσότερα

Concrete Mathematics Exercises from 30 September 2016

Concrete 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 περισσότερα

SOLUTIONS TO MATH38181 EXTREME VALUES AND FINANCIAL RISK EXAM

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

Διαβάστε περισσότερα

Homework 8 Model Solution Section

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

Διαβάστε περισσότερα

Areas and Lengths in Polar Coordinates

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

Διαβάστε περισσότερα

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

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

Διαβάστε περισσότερα

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

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

Διαβάστε περισσότερα

ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007

ΚΥΠΡΙΑΚΗ 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 περισσότερα

( ) 2 and compare to M.

( ) 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 περισσότερα

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

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

Διαβάστε περισσότερα

ORDINAL ARITHMETIC JULIAN J. SCHLÖDER

ORDINAL ARITHMETIC JULIAN J. SCHLÖDER ORDINAL ARITHMETIC JULIAN J. SCHLÖDER Abstract. We define ordinal arithmetic and show laws of Left- Monotonicity, Associativity, Distributivity, some minor related properties and the Cantor Normal Form.

Διαβάστε περισσότερα

Lecture 21: Properties and robustness of LSE

Lecture 21: Properties and robustness of LSE Lecture 21: Properties and robustness of LSE BLUE: Robustness of LSE against normality We now study properties of l τ β and σ 2 under assumption A2, i.e., without the normality assumption on ε. From Theorem

Διαβάστε περισσότερα

12. Radon-Nikodym Theorem

12. Radon-Nikodym Theorem Tutorial 12: Radon-Nikodym Theorem 1 12. Radon-Nikodym Theorem In the following, (Ω, F) is an arbitrary measurable space. Definition 96 Let μ and ν be two (possibly complex) measures on (Ω, F). We say

Διαβάστε περισσότερα

Second Order Partial Differential Equations

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

Διαβάστε περισσότερα

Parametrized Surfaces

Parametrized 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 περισσότερα

Homework 3 Solutions

Homework 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 περισσότερα

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

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

Διαβάστε περισσότερα

ΕΛΛΗΝΙΚΗ 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 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 περισσότερα

2. Let H 1 and H 2 be Hilbert spaces and let T : H 1 H 2 be a bounded linear operator. Prove that [T (H 1 )] = N (T ). (6p)

2. Let H 1 and H 2 be Hilbert spaces and let T : H 1 H 2 be a bounded linear operator. Prove that [T (H 1 )] = N (T ). (6p) Uppsala Universitet Matematiska Institutionen Andreas Strömbergsson Prov i matematik Funktionalanalys Kurs: F3B, F4Sy, NVP 2005-03-08 Skrivtid: 9 14 Tillåtna hjälpmedel: Manuella skrivdon, Kreyszigs bok

Διαβάστε περισσότερα

Section 9.2 Polar Equations and Graphs

Section 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 περισσότερα

Lecture 15 - Root System Axiomatics

Lecture 15 - Root System Axiomatics Lecture 15 - Root System Axiomatics Nov 1, 01 In this lecture we examine root systems from an axiomatic point of view. 1 Reflections If v R n, then it determines a hyperplane, denoted P v, through the

Διαβάστε περισσότερα

Optimal Parameter in Hermitian and Skew-Hermitian Splitting Method for Certain Two-by-Two Block Matrices

Optimal Parameter in Hermitian and Skew-Hermitian Splitting Method for Certain Two-by-Two Block Matrices Optimal Parameter in Hermitian and Skew-Hermitian Splitting Method for Certain Two-by-Two Block Matrices Chi-Kwong Li Department of Mathematics The College of William and Mary Williamsburg, Virginia 23187-8795

Διαβάστε περισσότερα

Second Order RLC Filters

Second 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 περισσότερα

Fractional Colorings and Zykov Products of graphs

Fractional 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 περισσότερα

ω ω ω ω ω ω+2 ω ω+2 + ω ω ω ω+2 + ω ω+1 ω ω+2 2 ω ω ω ω ω ω ω ω+1 ω ω2 ω ω2 + ω ω ω2 + ω ω ω ω2 + ω ω+1 ω ω2 + ω ω+1 + ω ω ω ω2 + ω

ω ω ω ω ω ω+2 ω ω+2 + ω ω ω ω+2 + ω ω+1 ω ω+2 2 ω ω ω ω ω ω ω ω+1 ω ω2 ω ω2 + ω ω ω2 + ω ω ω ω2 + ω ω+1 ω ω2 + ω ω+1 + ω ω ω ω2 + ω 0 1 2 3 4 5 6 ω ω + 1 ω + 2 ω + 3 ω + 4 ω2 ω2 + 1 ω2 + 2 ω2 + 3 ω3 ω3 + 1 ω3 + 2 ω4 ω4 + 1 ω5 ω 2 ω 2 + 1 ω 2 + 2 ω 2 + ω ω 2 + ω + 1 ω 2 + ω2 ω 2 2 ω 2 2 + 1 ω 2 2 + ω ω 2 3 ω 3 ω 3 + 1 ω 3 + ω ω 3 +

Διαβάστε περισσότερα

Section 8.2 Graphs of Polar Equations

Section 8.2 Graphs of Polar Equations Section 8. Graphs of Polar Equations Graphing Polar Equations The graph of a polar equation r = f(θ), or more generally F(r,θ) = 0, consists of all points P that have at least one polar representation

Διαβάστε περισσότερα

ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2

ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2 ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ ΚΑΙ ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος 2007-08 -- Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2 Ημερομηνία Παραδόσεως: Παρασκευή

Διαβάστε περισσότερα

( y) Partial Differential Equations

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

Διαβάστε περισσότερα

Mean-Variance Analysis

Mean-Variance Analysis Mean-Variance Analysis Jan Schneider McCombs School of Business University of Texas at Austin Jan Schneider Mean-Variance Analysis Beta Representation of the Risk Premium risk premium E t [Rt t+τ ] R1

Διαβάστε περισσότερα

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

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

Διαβάστε περισσότερα

Optimal Fund Menus. joint work with. Julien Hugonnier (EPFL) 1 / 17

Optimal Fund Menus. joint work with. Julien Hugonnier (EPFL) 1 / 17 Optimal Fund Menus joint work with Julien Hugonnier (EPFL) 1 / 17 Motivation and overview The same firm offers many mutual funds Question: given the heterogeneity of investors, what is the optimal fund

Διαβάστε περισσότερα

6.3 Forecasting ARMA processes

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

Διαβάστε περισσότερα

w o = R 1 p. (1) R = p =. = 1

w 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 περισσότερα

Testing for Indeterminacy: An Application to U.S. Monetary Policy. Technical Appendix

Testing for Indeterminacy: An Application to U.S. Monetary Policy. Technical Appendix Testing for Indeterminacy: An Application to U.S. Monetary Policy Technical Appendix Thomas A. Lubik Department of Economics Johns Hopkins University Frank Schorfheide Department of Economics University

Διαβάστε περισσότερα

To find the relationships between the coefficients in the original equation and the roots, we have to use a different technique.

To find the relationships between the coefficients in the original equation and the roots, we have to use a different technique. Further Conepts for Avne Mthemtis - FP1 Unit Ientities n Roots of Equtions Cui, Qurti n Quinti Equtions Cui Equtions The three roots of the ui eqution x + x + x + 0 re lle α, β n γ (lph, et n gmm). The

Διαβάστε περισσότερα

Notes on the Open Economy

Notes 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 περισσότερα

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

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

Διαβάστε περισσότερα

Appendix S1 1. ( z) α βc. dβ β δ β

Appendix S1 1. ( z) α βc. dβ β δ β Appendix S1 1 Proof of Lemma 1. Taking first and second partial derivatives of the expected profit function, as expressed in Eq. (7), with respect to l: Π Π ( z, λ, l) l θ + s ( s + h ) g ( t) dt λ Ω(

Διαβάστε περισσότερα

Approximation of distance between locations on earth given by latitude and longitude

Approximation 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 περισσότερα

Section 7.6 Double and Half Angle Formulas

Section 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 περισσότερα

F19MC2 Solutions 9 Complex Analysis

F19MC2 Solutions 9 Complex Analysis F9MC Solutions 9 Complex Analysis. (i) Let f(z) = eaz +z. Then f is ifferentiable except at z = ±i an so by Cauchy s Resiue Theorem e az z = πi[res(f,i)+res(f, i)]. +z C(,) Since + has zeros of orer at

Διαβάστε περισσότερα

Coefficient Inequalities for a New Subclass of K-uniformly Convex Functions

Coefficient Inequalities for a New Subclass of K-uniformly Convex Functions International Journal of Computational Science and Mathematics. ISSN 0974-89 Volume, Number (00), pp. 67--75 International Research Publication House http://www.irphouse.com Coefficient Inequalities for

Διαβάστε περισσότερα

Quantum Field Theory Example Sheet 1, Michælmas 2005

Quantum Field Theory Example Sheet 1, Michælmas 2005 Quntum Field Theory Exmple Sheet 1, Michælms 25 Jcob Lewis Bourjily 1. A string of length with mss per unit length σ under tension T with fixed endpoints is described by the Lgrngin ( 2 1 y L = dx 2 σ

Διαβάστε περισσότερα

Solutions to Exercise Sheet 5

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

Διαβάστε περισσότερα

Econ Spring 2004 Instructor: Prof. Kiefer Solution to Problem set # 5. γ (0)

Econ 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 περισσότερα

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

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

Διαβάστε περισσότερα

CHAPTER 101 FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD

CHAPTER 101 FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD CHAPTER FOURIER SERIES FOR PERIODIC FUNCTIONS OF PERIOD EXERCISE 36 Page 66. Determine the Fourier series for the periodic function: f(x), when x +, when x which is periodic outside this rge of period.

Διαβάστε περισσότερα

Arithmetical applications of lagrangian interpolation. Tanguy Rivoal. Institut Fourier CNRS and Université de Grenoble 1

Arithmetical applications of lagrangian interpolation. Tanguy Rivoal. Institut Fourier CNRS and Université de Grenoble 1 Arithmetical applications of lagrangian interpolation Tanguy Rivoal Institut Fourier CNRS and Université de Grenoble Conference Diophantine and Analytic Problems in Number Theory, The 00th anniversary

Διαβάστε περισσότερα

Lecture 13 - Root Space Decomposition II

Lecture 13 - Root Space Decomposition II Lecture 13 - Root Space Decomposition II October 18, 2012 1 Review First let us recall the situation. Let g be a simple algebra, with maximal toral subalgebra h (which we are calling a CSA, or Cartan Subalgebra).

Διαβάστε περισσότερα

Homomorphism in Intuitionistic Fuzzy Automata

Homomorphism in Intuitionistic Fuzzy Automata International Journal of Fuzzy Mathematics Systems. ISSN 2248-9940 Volume 3, Number 1 (2013), pp. 39-45 Research India Publications http://www.ripublication.com/ijfms.htm Homomorphism in Intuitionistic

Διαβάστε περισσότερα

10.7 Performance of Second-Order System (Unit Step Response)

10.7 Performance of Second-Order System (Unit Step Response) Lecture Notes on Control Systems/D. Ghose/0 57 0.7 Performance of Second-Order System (Unit Step Response) Consider the second order system a ÿ + a ẏ + a 0 y = b 0 r So, Y (s) R(s) = b 0 a s + a s + a

Διαβάστε περισσότερα

New bounds for spherical two-distance sets and equiangular lines

New bounds for spherical two-distance sets and equiangular lines New bounds for spherical two-distance sets and equiangular lines Michigan State University Oct 8-31, 016 Anhui University Definition If X = {x 1, x,, x N } S n 1 (unit sphere in R n ) and x i, x j = a

Διαβάστε περισσότερα