Size: px
Start display at page:

Download ""

Transcription

1

2

3

4

5 α α

6 λ α = = λ λ α ψ = = α α α λ λ ψ α = + β = > θ θ β > β β θ θ θ β θ β

7 γ θ β = γ θ > β > γ θ β γ = θ β = θ β = θ β = β θ = β β θ = = = β β θ

8 = +

9 α α

10 α

11

12

13

14 α α = = λ λ λ λ λ λ λ = λ λ α α α α λ ψ + α = α =

15 = = β θ = θ θ β β

16

17

18

it = α + β i + γ 1 t + γ 2 t + γ 3 t +λ 1 ( i ) + λ 2 ( i ) + λ 3 ( i ) +δx i + ϵ it, it i i t t t i λ 1 λ 3 t t t i = α + β i + δx i + ϵ i i i i 12 Harrison Cleveland McKinley Roosevelt 10 8 6

More information

University of Maryland Fraternity & Sorority Life Spring 2015 Academic Report

University of Maryland Fraternity & Sorority Life Spring 2015 Academic Report University of Maryland Fraternity & Sorority Life Academic Report Academic and Population Statistics Population: # of Students: # of New Members: Avg. Size: Avg. GPA: % of the Undergraduate Population

More information

2. Illustration of the Nikkei 225 option data

2. Illustration of the Nikkei 225 option data 1. Introduction 2. Illustration of the Nikkei 225 option data 2.1 A brief outline of the Nikkei 225 options market τ 2.2 Estimation of the theoretical price τ = + ε ε = = + ε + = + + + = + ε + ε + ε =

More information

(k 1)! e (m 1)/N v(k). (k 1)!

(k 1)! e (m 1)/N v(k). (k 1)! m N 1/N k v : N R m k 1 k B(k 1, m 1; 1/N) = ( ) ( m 1 1 k 1 N ) k 1 ( ) m k N 1. N m N (m 1)/N P ((m 1)/N; k 1) = 1 (k 1)! m EV (m) = k=1 1 (k 1)! ( ) k 1 m 1 e (m 1)/N. N ( ) k 1 m 1 e (m 1)/N v(k).

More information

x o R n a π(a, x o ) A R n π(a, x o ) π(a, x o ) A R n a a x o x o x n X R n δ(x n, x o ) d(a, x n ) d(, ) δ(, ) R n x n X d(a, x n ) δ(x n, x o ) a = a A π(a, xo ) a a A = X = R π(a, x o ) = (x o + ρ)

More information

PRESENTATION OF DATA AVAILABLE

PRESENTATION OF DATA AVAILABLE Statistical analysis and definition of blockages-prediction formulae for the wastewater network of Oslo by evolutionary computing ABSTRACT KEYWORDS INTRODUCTION PRESENTATION OF DATA AVAILABLE Figure 1

More information

1 Sufficient statistics

1 Sufficient statistics 1 Sufficient statistics A statistic is a function T = rx 1, X 2,, X n of the random sample X 1, X 2,, X n. Examples are X n = 1 n s 2 = = X i, 1 n 1 the sample mean X i X n 2, the sample variance T 1 =

More information

VISUALIZATION OF DENSITY FUNCTIONS WITH GEOGEBRA

VISUALIZATION OF DENSITY FUNCTIONS WITH GEOGEBRA VISUALIZATION OF DENSITY FUNCTIONS WITH GEOGEBRA Csilla Csendes University of Miskolc, Hungary Department of Applied Mathematics ICAM 2010 Probability density functions A random variable X has density

More information

M1 in Economics and Economics and Statistics Applied multivariate Analysis - Big data analytics Worksheet 1 - Bootstrap

M1 in Economics and Economics and Statistics Applied multivariate Analysis - Big data analytics Worksheet 1 - Bootstrap Nathalie Villa-Vialanei Année 2015/2016 M1 in Economics and Economics and Statistics Applied multivariate Analsis - Big data analtics Worksheet 1 - Bootstrap This worksheet illustrates the use of nonparametric

More information

Maximum Likelihood Estimation

Maximum Likelihood Estimation Math 541: Statistical Theory II Lecturer: Songfeng Zheng Maximum Likelihood Estimation 1 Maximum Likelihood Estimation Maximum likelihood is a relatively simple method of constructing an estimator for

More information

Stochastic Models for Inventory Management at Service Facilities

Stochastic Models for Inventory Management at Service Facilities Stochastic Models for Inventory Management at Service Facilities O. Berman, E. Kim Presented by F. Zoghalchi University of Toronto Rotman School of Management Dec, 2012 Agenda 1 Problem description Deterministic

More information

Lecture 3 SU(2) January 26, 2011. Lecture 3

Lecture 3 SU(2) January 26, 2011. Lecture 3 Lecture 3 SU(2) January 26, 2 Lecture 3 A Little Group Theory A group is a set of elements plus a compostion rule, such that:. Combining two elements under the rule gives another element of the group.

More information

OHIO REGION PHI THETA KAPPA 2012-13

OHIO REGION PHI THETA KAPPA 2012-13 OHIO REGION PHI THETA KAPPA REGION HALLMARK AWARDS HONORS IN ACTION HALLMARK WINNER Alpha Rho Epsilon Columbus State Community College HONORS IN ACTION HALLMARK FIRST RUNNER-UP Washington State Community

More information

Department of Mathematics, Indian Institute of Technology, Kharagpur Assignment 2-3, Probability and Statistics, March 2015. Due:-March 25, 2015.

Department of Mathematics, Indian Institute of Technology, Kharagpur Assignment 2-3, Probability and Statistics, March 2015. Due:-March 25, 2015. Department of Mathematics, Indian Institute of Technology, Kharagpur Assignment -3, Probability and Statistics, March 05. Due:-March 5, 05.. Show that the function 0 for x < x+ F (x) = 4 for x < for x

More information

1.3. DOT PRODUCT 19. 6. If θ is the angle (between 0 and π) between two non-zero vectors u and v,

1.3. DOT PRODUCT 19. 6. If θ is the angle (between 0 and π) between two non-zero vectors u and v, 1.3. DOT PRODUCT 19 1.3 Dot Product 1.3.1 Definitions and Properties The dot product is the first way to multiply two vectors. The definition we will give below may appear arbitrary. But it is not. It

More information

Errata and updates for ASM Exam C/Exam 4 Manual (Sixteenth Edition) sorted by page

Errata and updates for ASM Exam C/Exam 4 Manual (Sixteenth Edition) sorted by page Errata for ASM Exam C/4 Study Manual (Sixteenth Edition) Sorted by Page 1 Errata and updates for ASM Exam C/Exam 4 Manual (Sixteenth Edition) sorted by page Practice exam 1:9, 1:22, 1:29, 9:5, and 10:8

More information

6.2 Permutations continued

6.2 Permutations continued 6.2 Permutations continued Theorem A permutation on a finite set A is either a cycle or can be expressed as a product (composition of disjoint cycles. Proof is by (strong induction on the number, r, of

More information

Modelling spousal mortality dependence: evidence of heterogeneities and implications

Modelling spousal mortality dependence: evidence of heterogeneities and implications 1/23 Modelling spousal mortality dependence: evidence of heterogeneities and implications Yang Lu Scor and Aix-Marseille School of Economics Lyon, September 2015 2/23 INTRODUCTION 3/23 Motivation It has

More information

WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM

WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM WORKED EXAMPLES 1 TOTAL PROBABILITY AND BAYES THEOREM EXAMPLE 1. A biased coin (with probability of obtaining a Head equal to p > 0) is tossed repeatedly and independently until the first head is observed.

More information

Notes on the Negative Binomial Distribution

Notes on the Negative Binomial Distribution Notes on the Negative Binomial Distribution John D. Cook October 28, 2009 Abstract These notes give several properties of the negative binomial distribution. 1. Parameterizations 2. The connection between

More information

Charles Jones: US Economic Growth in a World of Ideas and other Jones Papers. January 22, 2014

Charles Jones: US Economic Growth in a World of Ideas and other Jones Papers. January 22, 2014 Charles Jones: US Economic Growth in a World of Ideas and other Jones Papers January 22, 2014 U.S. GDP per capita, log scale Old view: therefore the US is in some kind of Solow steady state (i.e. Balanced

More information

ASCII CODES WITH GREEK CHARACTERS

ASCII CODES WITH GREEK CHARACTERS ASCII CODES WITH GREEK CHARACTERS Dec Hex Char Description 0 0 NUL (Null) 1 1 SOH (Start of Header) 2 2 STX (Start of Text) 3 3 ETX (End of Text) 4 4 EOT (End of Transmission) 5 5 ENQ (Enquiry) 6 6 ACK

More information

INSURANCE RISK THEORY (Problems)

INSURANCE RISK THEORY (Problems) INSURANCE RISK THEORY (Problems) 1 Counting random variables 1. (Lack of memory property) Let X be a geometric distributed random variable with parameter p (, 1), (X Ge (p)). Show that for all n, m =,

More information

Towards a Structuralist Interpretation of Saving, Investment and Current Account in Turkey

Towards a Structuralist Interpretation of Saving, Investment and Current Account in Turkey Towards a Structuralist Interpretation of Saving, Investment and Current Account in Turkey MURAT ÜNGÖR Central Bank of the Republic of Turkey http://www.muratungor.com/ April 2012 We live in the age of

More information

Mathematics. (www.tiwariacademy.com : Focus on free Education) (Chapter 5) (Complex Numbers and Quadratic Equations) (Class XI)

Mathematics. (www.tiwariacademy.com : Focus on free Education) (Chapter 5) (Complex Numbers and Quadratic Equations) (Class XI) ( : Focus on free Education) Miscellaneous Exercise on chapter 5 Question 1: Evaluate: Answer 1: 1 ( : Focus on free Education) Question 2: For any two complex numbers z1 and z2, prove that Re (z1z2) =

More information

Table of Contents Appendix 4-9

Table of Contents Appendix 4-9 Table of Contents Appendix 4-9 Appendix Multi-Input Thermometer & Datalogger Software Manual v1.0 4-8 Table of Contents 1. Introduction...1-1 1.1 Operation Environment...1-1 1.2 Hardware...1-1 1.3 Connecting

More information

The epistemic structure of de Finetti s betting problem

The epistemic structure of de Finetti s betting problem The epistemic structure of de Finetti s betting problem Tommaso Flaminio 1 Hykel Hosni 2 1 IIIA - CSIC Universitat Autonoma de Barcelona (Spain) tommaso@iiia.csic.es www.iiia.csic.es/ tommaso 2 SNS Scuola

More information

! # %!&% ( % )% & % + %, )./0 12 +3

! # %!&% ( % )% & % + %, )./0 12 +3 ! # %!&% ( % )% & % + %, )./0 12 +3 & 4 5 1( & 6 6 7 &.67 &2% /0 1 6 7 &.67 &2% 01 08, /0 1% 9 6 % : + 0 08 67 & /0 1 8;118 < Energy Efficient Network Function Virtualization in 5G Networks A. Al-Quzweeni,

More information

U = x 1 2. 1 x 1 4. 2 x 1 4. What are the equilibrium relative prices of the three goods? traders has members who are best off?

U = x 1 2. 1 x 1 4. 2 x 1 4. What are the equilibrium relative prices of the three goods? traders has members who are best off? Chapter 7 General Equilibrium Exercise 7. Suppose there are 00 traders in a market all of whom behave as price takers. Suppose there are three goods and the traders own initially the following quantities:

More information

Exact Confidence Intervals

Exact Confidence Intervals Math 541: Statistical Theory II Instructor: Songfeng Zheng Exact Confidence Intervals Confidence intervals provide an alternative to using an estimator ˆθ when we wish to estimate an unknown parameter

More information

Transmission Lines. Smith Chart

Transmission Lines. Smith Chart Smith Chart The Smith chart is one of the most useful graphical tools for high frequency circuit applications. The chart provides a clever way to visualize complex functions and it continues to endure

More information

Techniques algébriques en calcul quantique

Techniques algébriques en calcul quantique Techniques algébriques en calcul quantique E. Jeandel Laboratoire de l Informatique du Parallélisme LIP, ENS Lyon, CNRS, INRIA, UCB Lyon 8 Avril 25 E. Jeandel, LIP, ENS Lyon Techniques algébriques en calcul

More information

Imprecise probabilities, bets and functional analytic methods in Łukasiewicz logic.

Imprecise probabilities, bets and functional analytic methods in Łukasiewicz logic. Imprecise probabilities, bets and functional analytic methods in Łukasiewicz logic. Martina Fedel joint work with K.Keimel,F.Montagna,W.Roth Martina Fedel (UNISI) 1 / 32 Goal The goal of this talk is to

More information

Cyber-Security Analysis of State Estimators in Power Systems

Cyber-Security Analysis of State Estimators in Power Systems Cyber-Security Analysis of State Estimators in Electric Power Systems André Teixeira 1, Saurabh Amin 2, Henrik Sandberg 1, Karl H. Johansson 1, and Shankar Sastry 2 ACCESS Linnaeus Centre, KTH-Royal Institute

More information

Introduction to Basic Reliability Statistics. James Wheeler, CMRP

Introduction to Basic Reliability Statistics. James Wheeler, CMRP James Wheeler, CMRP Objectives Introduction to Basic Reliability Statistics Arithmetic Mean Standard Deviation Correlation Coefficient Estimating MTBF Type I Censoring Type II Censoring Eponential Distribution

More information

How To Volunteer At The Big Event At Uni

How To Volunteer At The Big Event At Uni BIG Event Volunteer Registration Come volunteer your time on April 11th & 12th to say "Thank You" to the Conway community! To view the schedule and additional information go to our website! http://ucaofficeofstudentlife.orgsync.com/org/sga/big_event

More information

Total Degrees and Nonsplitting Properties of Σ 0 2 Enumeration Degrees

Total Degrees and Nonsplitting Properties of Σ 0 2 Enumeration Degrees Total Degrees and Nonsplitting Properties of Σ 0 2 Enumeration Degrees M. M. Arslanov, S. B. Cooper, I. Sh. Kalimullin and M. I. Soskova Kazan State University, Russia University of Leeds, U.K. This paper

More information

VI. Real Business Cycles Models

VI. Real Business Cycles Models VI. Real Business Cycles Models Introduction Business cycle research studies the causes and consequences of the recurrent expansions and contractions in aggregate economic activity that occur in most industrialized

More information

MAT 242 Test 3 SOLUTIONS, FORM A

MAT 242 Test 3 SOLUTIONS, FORM A MAT Test SOLUTIONS, FORM A. Let v =, v =, and v =. Note that B = { v, v, v } is an orthogonal set. Also, let W be the subspace spanned by { v, v, v }. A = 8 a. [5 points] Find the orthogonal projection

More information

Section 4.4 Inner Product Spaces

Section 4.4 Inner Product Spaces Section 4.4 Inner Product Spaces In our discussion of vector spaces the specific nature of F as a field, other than the fact that it is a field, has played virtually no role. In this section we no longer

More information

Differentiated Pricing of Urban Transportation Networks. Networks with Vehicle-Tracking Technologies

Differentiated Pricing of Urban Transportation Networks. Networks with Vehicle-Tracking Technologies of Urban Transportation Networks with Vehicle-Tracking Technologies Mahmood Zangui Yafeng Yin* Siriphong Lawphongpanich Shigang Chen Department of Civil and Coastal Engineering University of Florida July

More information

Statistical Machine Learning from Data

Statistical Machine Learning from Data Samy Bengio Statistical Machine Learning from Data 1 Statistical Machine Learning from Data Gaussian Mixture Models Samy Bengio IDIAP Research Institute, Martigny, Switzerland, and Ecole Polytechnique

More information

Distributed Detection Systems. Hamidreza Ahmadi

Distributed Detection Systems. Hamidreza Ahmadi Channel Estimation Error in Distributed Detection Systems Hamidreza Ahmadi Outline Detection Theory Neyman-Pearson Method Classical l Distributed ib t Detection ti Fusion and local sensor rules Channel

More information

A Theory of Capital Controls As Dynamic Terms of Trade Manipulation

A Theory of Capital Controls As Dynamic Terms of Trade Manipulation A Theory of Capital Controls As Dynamic Terms of Trade Manipulation Arnaud Costinot Guido Lorenzoni Iván Werning Central Bank of Chile, November 2013 Tariffs and capital controls Tariffs: Intratemporal

More information

AGGREGATE CLAIMS, SOLVENCY AND REINSURANCE. David Dickson, Centre for Actuarial Studies, University of Melbourne. Cherry Bud Workshop

AGGREGATE CLAIMS, SOLVENCY AND REINSURANCE. David Dickson, Centre for Actuarial Studies, University of Melbourne. Cherry Bud Workshop AGGREGATE CLAIMS, SOLVENCY AND REINSURANCE David Dickson, Centre for Actuarial Studies, University of Melbourne Cherry Bud Workshop Keio University, 27 March 2006 Basic General Insurance Risk Model where

More information

Deriving Demand Functions - Examples 1

Deriving Demand Functions - Examples 1 Deriving Demand Functions - Examples 1 What follows are some examples of different preference relations and their respective demand functions. In all the following examples, assume we have two goods x

More information

Addition and Subtraction of Vectors

Addition and Subtraction of Vectors ddition and Subtraction of Vectors 1 ppendi ddition and Subtraction of Vectors In this appendi the basic elements of vector algebra are eplored. Vectors are treated as geometric entities represented b

More information

RISK SHARING AND EFFICIENCY IMPLICATIONS

RISK SHARING AND EFFICIENCY IMPLICATIONS IMPLICATIONS OF PROGRESSIVE PENSION ARRANGEMENTS UNIVERSITY OF WUERZBURG CONTENTS 1/18 CONTENTS 1. MOTIVATION 2. THE NUMERICAL GENERAL EQUILIBRIUM MODEL 3. SIMULATION RESULTS 4. CONCLUSIONS MOTIVATION

More information

User Guide LabelManager 420P

User Guide LabelManager 420P User Guide LabelManager 420P 17 18 19 20 21 22 16 1 15 2 14 13 3 4, - + 5 % Shift 6 12 7 8 11 10 9 Figure 1DYMO LabelManager 420P label maker 1 Print 9 Accented characters 17 Format 2 Preview 10 Space

More information

What Are the segments of a Judicial Board Meeting?

What Are the segments of a Judicial Board Meeting? American Criminal Justice Association Lambda Alpha Epsilon Psi Omega Judicial Board Guidelines Created Submitted by: Sergeant- At- Arms Anthony Bouchard 2 The Sergeant-at-Arms shall be the chairperson

More information

Please contact HQ with any questions about this information.

Please contact HQ with any questions about this information. The chapters listed below took in their full complement (3% of FSL community), or more than 75 new members during the 2014-2015 academic year, and are eligible to have 3 members apply for our Fall Please

More information

Dot Product. Academic Resource Center

Dot Product. Academic Resource Center Dot Product Academic Resource Center In This Presentation We will give a definition Look at properties See the relationship in projections Look at vectors in different coordinate systems Do example problems

More information

Gaussian Conjugate Prior Cheat Sheet

Gaussian Conjugate Prior Cheat Sheet Gaussian Conjugate Prior Cheat Sheet Tom SF Haines 1 Purpose This document contains notes on how to handle the multivariate Gaussian 1 in a Bayesian setting. It focuses on the conjugate prior, its Bayesian

More information

Technology adoption in health care

Technology adoption in health care Technology adoption in health care Pedro Pita Barros Universidade Nova de Lisboa and CEPR ppbarros@fe.unl.pt and Xavier Martinez-Giralt Universitat Autònoma de Barcelona and MOVE xavier.martinez.giralt@uab.eu

More information

WASHINGTON STATE UNIVERSITY Payroll Services COMPOSED ADDRESSES FOR RESIDENCE HALLS RM NO. RESIDENCE HALL NAME CITY STATE ZIP + 4

WASHINGTON STATE UNIVERSITY Payroll Services COMPOSED ADDRESSES FOR RESIDENCE HALLS RM NO. RESIDENCE HALL NAME CITY STATE ZIP + 4 COMPOSED ADDRESSES FOR RESIDENCE HALLS CODE RM NO. RESIDENCE HALL NAME CITY STATE ZIP + 4 79 COMAN HALL -5281 71 COMMUNITY / DUNCAN DUNN HALL -5282 68 GANNON HALL -5286 69 GOLDSWORTHY HALL -5287 67 HONORS

More information

The US dollar exchange rate and the demand for oil

The US dollar exchange rate and the demand for oil The US dollar exchange rate and the demand for oil Selien De Schryder Ghent University Gert Peersman Ghent University Norges Bank/ECB workshop on "Monetary Policy and Commodity Prices" 19-20 November 2012

More information

The Notebook Series. The solution of cubic and quartic equations. R.S. Johnson. Professor of Applied Mathematics

The Notebook Series. The solution of cubic and quartic equations. R.S. Johnson. Professor of Applied Mathematics The Notebook Series The solution of cubic and quartic equations by R.S. Johnson Professor of Applied Mathematics School of Mathematics & Statistics University of Newcastle upon Tyne R.S.Johnson 006 CONTENTS

More information

Powers of Two in Generalized Fibonacci Sequences

Powers of Two in Generalized Fibonacci Sequences Revista Colombiana de Matemáticas Volumen 462012)1, páginas 67-79 Powers of Two in Generalized Fibonacci Sequences Potencias de dos en sucesiones generalizadas de Fibonacci Jhon J. Bravo 1,a,B, Florian

More information

Tension Development and Lap Splice Lengths of Reinforcing Bars under ACI 318-02

Tension Development and Lap Splice Lengths of Reinforcing Bars under ACI 318-02 ENGINEERING DATA REPORT NUMBER 51 Tension Development and Lap Splice Lengths of Reinforcing Bars under ACI 318-02 A SERVICE OF THE CONCRETE REINFORCING STEEL INSTITUTE Introduction Section 1.2.1 in the

More information

Math Placement Test Practice Problems

Math Placement Test Practice Problems Math Placement Test Practice Problems The following problems cover material that is used on the math placement test to place students into Math 1111 College Algebra, Math 1113 Precalculus, and Math 2211

More information

Lecture 8: More Continuous Random Variables

Lecture 8: More Continuous Random Variables Lecture 8: More Continuous Random Variables 26 September 2005 Last time: the eponential. Going from saying the density e λ, to f() λe λ, to the CDF F () e λ. Pictures of the pdf and CDF. Today: the Gaussian

More information

Parabolic Equations. Chapter 5. Contents. 5.1.2 Well-Posed Initial-Boundary Value Problem. 5.1.3 Time Irreversibility of the Heat Equation

Parabolic Equations. Chapter 5. Contents. 5.1.2 Well-Posed Initial-Boundary Value Problem. 5.1.3 Time Irreversibility of the Heat Equation 7 5.1 Definitions Properties Chapter 5 Parabolic Equations Note that we require the solution u(, t bounded in R n for all t. In particular we assume that the boundedness of the smooth function u at infinity

More information

Fertility, Female Labor Force Participation, and the Demographic Dividend

Fertility, Female Labor Force Participation, and the Demographic Dividend Fertility, Female Labor Force Participation, and the Demographic Dividend David E. Bloom David Canning Günther Fink Jocelyn E. Finlay Program on the Global Demography of Aging Harvard School of Public

More information

Quantum Algorithms. Peter Høyer

Quantum Algorithms. Peter Høyer Quantum Algorithms Peter Høyer University of Calgary CSSQI 2015 Canadian Summer School on Quantum Information Toronto, August 11, 2015 QUERY MODEL x1 x2 xn x1 0 1 0 0 0 1 0 1 0 0 0 0 xn You can ask questions

More information

Chapter 4 Statistical Inference in Quality Control and Improvement. Statistical Quality Control (D. C. Montgomery)

Chapter 4 Statistical Inference in Quality Control and Improvement. Statistical Quality Control (D. C. Montgomery) Chapter 4 Statistical Inference in Quality Control and Improvement 許 湘 伶 Statistical Quality Control (D. C. Montgomery) Sampling distribution I a random sample of size n: if it is selected so that the

More information

Topic 5: Stochastic Growth and Real Business Cycles

Topic 5: Stochastic Growth and Real Business Cycles Topic 5: Stochastic Growth and Real Business Cycles Yulei Luo SEF of HKU October 1, 2015 Luo, Y. (SEF of HKU) Macro Theory October 1, 2015 1 / 45 Lag Operators The lag operator (L) is de ned as Similar

More information

Sharing Online Advertising Revenue with Consumers

Sharing Online Advertising Revenue with Consumers Sharing Online Advertising Revenue with Consumers Yiling Chen 2,, Arpita Ghosh 1, Preston McAfee 1, and David Pennock 1 1 Yahoo! Research. Email: arpita, mcafee, pennockd@yahoo-inc.com 2 Harvard University.

More information

Final Mathematics 5010, Section 1, Fall 2004 Instructor: D.A. Levin

Final Mathematics 5010, Section 1, Fall 2004 Instructor: D.A. Levin Final Mathematics 51, Section 1, Fall 24 Instructor: D.A. Levin Name YOU MUST SHOW YOUR WORK TO RECEIVE CREDIT. A CORRECT ANSWER WITHOUT SHOWING YOUR REASONING WILL NOT RECEIVE CREDIT. Problem Points Possible

More information

Exploratory Factor Analysis and Principal Components. Pekka Malo & Anton Frantsev 30E00500 Quantitative Empirical Research Spring 2016

Exploratory Factor Analysis and Principal Components. Pekka Malo & Anton Frantsev 30E00500 Quantitative Empirical Research Spring 2016 and Principal Components Pekka Malo & Anton Frantsev 30E00500 Quantitative Empirical Research Spring 2016 Agenda Brief History and Introductory Example Factor Model Factor Equation Estimation of Loadings

More information

Using the Delta Method to Construct Confidence Intervals for Predicted Probabilities, Rates, and Discrete Changes

Using the Delta Method to Construct Confidence Intervals for Predicted Probabilities, Rates, and Discrete Changes Using the Delta Method to Construct Confidence Intervals for Predicted Probabilities, Rates, Discrete Changes JunXuJ.ScottLong Indiana University August 22, 2005 The paper provides technical details on

More information

Online Appendix for. Poultry in Motion: A Study of International Trade Finance Practices

Online Appendix for. Poultry in Motion: A Study of International Trade Finance Practices Online Appendix for Poultry in Motion: A Study of International Trade Finance Practices P A C. F F May 30, 2014 This Online Appendix documents some theoretical extensions discussed in Poultry in Motion:

More information

Supplement to Call Centers with Delay Information: Models and Insights

Supplement to Call Centers with Delay Information: Models and Insights Supplement to Call Centers with Delay Information: Models and Insights Oualid Jouini 1 Zeynep Akşin 2 Yves Dallery 1 1 Laboratoire Genie Industriel, Ecole Centrale Paris, Grande Voie des Vignes, 92290

More information

L stub Z A = Z 0 Z R Z 0S. Single stub impedance matching

L stub Z A = Z 0 Z R Z 0S. Single stub impedance matching Single stub impedance matching Impedance matching can be achieved by inserting another transmission line (stub) as shown in the diagram below Z A = Z 0 Z 0 Z R Z 0S d stub L stub Amanogawa, 006 Digital

More information

Spectrum Trading with Insurance in Cognitive Radio Networks

Spectrum Trading with Insurance in Cognitive Radio Networks Spectrum Trading with Insurance in Cognitive Radio Networks 1/46 Spectrum Trading with Insurance in Cognitive Radio Networks Haiming Jin 1, Gaofei Sun 1, Xinbing Wang 1 and Qian Zhang 2 1 Department of

More information

Survey Questionnaire for IT Applications. General instructions for filling the forms of survey questionnaire:

Survey Questionnaire for IT Applications. General instructions for filling the forms of survey questionnaire: Survey Questionnaire for IT Applications General instructions for filling the forms of survey questionnaire: There are three forms in the survey questionnaire. For each IT Application all the forms of

More information

XMGrace Fancy characters and stuff

XMGrace Fancy characters and stuff XMGrace Fancy characters and stuff In XMGrace it is possible to write Greek letters, do superscripts and subscripts and the like. This tex-file/pdf will hopefully keep a list of what I have learnt (starting

More information

The Honors Program is under review, and these terms may be modified for the 2012-13 Academic Year.

The Honors Program is under review, and these terms may be modified for the 2012-13 Academic Year. The Honors Program is under review, and these terms may be modified for the 2012-13 Academic Year. HONORS PROGRAMS In 1957 the faculty of the University of Miami established the General Honors Program

More information

Hedging Options In The Incomplete Market With Stochastic Volatility. Rituparna Sen Sunday, Nov 15

Hedging Options In The Incomplete Market With Stochastic Volatility. Rituparna Sen Sunday, Nov 15 Hedging Options In The Incomplete Market With Stochastic Volatility Rituparna Sen Sunday, Nov 15 1. Motivation This is a pure jump model and hence avoids the theoretical drawbacks of continuous path models.

More information

Web-based Supplementary Materials for. Modeling of Hormone Secretion-Generating. Mechanisms With Splines: A Pseudo-Likelihood.

Web-based Supplementary Materials for. Modeling of Hormone Secretion-Generating. Mechanisms With Splines: A Pseudo-Likelihood. Web-based Supplementary Materials for Modeling of Hormone Secretion-Generating Mechanisms With Splines: A Pseudo-Likelihood Approach by Anna Liu and Yuedong Wang Web Appendix A This appendix computes mean

More information

t := maxγ ν subject to ν {0,1,2,...} and f(x c +γ ν d) f(x c )+cγ ν f (x c ;d).

t := maxγ ν subject to ν {0,1,2,...} and f(x c +γ ν d) f(x c )+cγ ν f (x c ;d). 1. Line Search Methods Let f : R n R be given and suppose that x c is our current best estimate of a solution to P min x R nf(x). A standard method for improving the estimate x c is to choose a direction

More information

AN EXPLANATION OF JOINT DIAGRAMS

AN EXPLANATION OF JOINT DIAGRAMS AN EXPLANATION OF JOINT DIAGRAMS When bolted joints are subjected to external tensile loads, what forces and elastic deformation really exist? The majority of engineers in both the fastener manufacturing

More information

Optimal Insurance Coverage of a Durable Consumption Good with a Premium Loading in a Continuous Time Economy

Optimal Insurance Coverage of a Durable Consumption Good with a Premium Loading in a Continuous Time Economy Optimal Insurance Coverage of a Durable Consumption Good with a Premium Loading in a Continuous Time Economy Masaaki Kijima 1 Teruyoshi Suzuki 2 1 Tokyo Metropolitan University and Daiwa Securities Group

More information

Math 333 - Practice Exam 2 with Some Solutions

Math 333 - Practice Exam 2 with Some Solutions Math 333 - Practice Exam 2 with Some Solutions (Note that the exam will NOT be this long) Definitions (0 points) Let T : V W be a transformation Let A be a square matrix (a) Define T is linear (b) Define

More information

5 VECTOR GEOMETRY. 5.0 Introduction. Objectives. Activity 1

5 VECTOR GEOMETRY. 5.0 Introduction. Objectives. Activity 1 5 VECTOR GEOMETRY Chapter 5 Vector Geometry Objectives After studying this chapter you should be able to find and use the vector equation of a straight line; be able to find the equation of a plane in

More information

I = 0 1. 1 ad bc. be the set of A in GL(2, C) with real entries and with determinant equal to 1, 1, respectively. Note that A = T A : S S

I = 0 1. 1 ad bc. be the set of A in GL(2, C) with real entries and with determinant equal to 1, 1, respectively. Note that A = T A : S S Fractional linear transformations. Definition. GL(, C) be the set of invertible matrices [ ] a b c d with complex entries. Note that (i) The identity matrix is in GL(, C). [ ] 1 0 I 0 1 (ii) If A and B

More information

Chapter 4. Linear Second Order Equations. ay + by + cy = 0, (1) where a, b, c are constants. The associated auxiliary equation is., r 2 = b b 2 4ac 2a

Chapter 4. Linear Second Order Equations. ay + by + cy = 0, (1) where a, b, c are constants. The associated auxiliary equation is., r 2 = b b 2 4ac 2a Chapter 4. Linear Second Order Equations ay + by + cy = 0, (1) where a, b, c are constants. ar 2 + br + c = 0. (2) Consequently, y = e rx is a solution to (1) if an only if r satisfies (2). So, the equation

More information

Standard Model of Particle Physics

Standard Model of Particle Physics Standard Model of Particle Physics Chris Sachrajda School of Physics and Astronomy University of Southampton Southampton SO17 1BJ UK SUSSP61, St Andrews August 8th 3rd 006 Contents 1. Spontaneous Symmetry

More information

Modern Algebra Lecture Notes: Rings and fields set 4 (Revision 2)

Modern Algebra Lecture Notes: Rings and fields set 4 (Revision 2) Modern Algebra Lecture Notes: Rings and fields set 4 (Revision 2) Kevin Broughan University of Waikato, Hamilton, New Zealand May 13, 2010 Remainder and Factor Theorem 15 Definition of factor If f (x)

More information

Part 2: One-parameter models

Part 2: One-parameter models Part 2: One-parameter models Bernoilli/binomial models Return to iid Y 1,...,Y n Bin(1, θ). The sampling model/likelihood is p(y 1,...,y n θ) =θ P y i (1 θ) n P y i When combined with a prior p(θ), Bayes

More information

Graduate Studies in Mathematics. The Author Author Two

Graduate Studies in Mathematics. The Author Author Two Graduate Studies in Mathematics The Author Author Two (A. U. Thor) A 1, A 2 Current address, A. U. Thor: Author current address line 1, Author current address line 2 E-mail address, A. U. Thor: author@institute.edu

More information

Financial Market Microstructure Theory

Financial Market Microstructure Theory The Microstructure of Financial Markets, de Jong and Rindi (2009) Financial Market Microstructure Theory Based on de Jong and Rindi, Chapters 2 5 Frank de Jong Tilburg University 1 Determinants of the

More information

POINT OF INTERSECTION OF TWO STRAIGHT LINES

POINT OF INTERSECTION OF TWO STRAIGHT LINES POINT OF INTERSECTION OF TWO STRAIGHT LINES THEOREM The point of intersection of the two non parallel lines bc bc ca ca a x + b y + c = 0, a x + b y + c = 0 is,. ab ab ab ab Proof: The lines are not parallel

More information

MODELLING CRITICAL ILLNESS INSURANCE DATA

MODELLING CRITICAL ILLNESS INSURANCE DATA MODELLING CRITICAL ILLNESS INSURANCE DATA Howard Waters Joint work with: Erengul Dodd (Ozkok), George Streftaris, David Wilkie University of Piraeus, October 2014 1 Plan: 1. Critical Illness Insurance

More information

Production Functions and Cost of Production

Production Functions and Cost of Production 1 Returns to Scale 1 14.01 Principles of Microeconomics, Fall 2007 Chia-Hui Chen October, 2007 Lecture 12 Production Functions and Cost of Production Outline 1. Chap 6: Returns to Scale 2. Chap 6: Production

More information

Stock Price Dynamics, Dividends and Option Prices with Volatility Feedback

Stock Price Dynamics, Dividends and Option Prices with Volatility Feedback Stock Price Dynamics, Dividends and Option Prices with Volatility Feedback Juho Kanniainen Tampere University of Technology New Thinking in Finance 12 Feb. 2014, London Based on J. Kanniainen and R. Piche,

More information