Variable Selection for Health Care Demand in Germany

Package zic. September 4, 2015

Package zic September 4, 2015 Version 0.9 Date 2015-09-03 Title Bayesian Inference for Zero-Inflated Count Models Author Markus Jochmann Maintainer Markus Jochmann

Aileen Murphy, Department of Economics, UCC, Ireland. WORKING PAPER SERIES 07-10

AN ECONOMETRIC ANALYSIS OF SMOKING BEHAVIOUR IN IRELAND Aileen Murphy, Department of Economics, UCC, Ireland. DEPARTMENT OF ECONOMICS WORKING PAPER SERIES 07-10 1 AN ECONOMETRIC ANALYSIS OF SMOKING BEHAVIOUR

Building risk prediction models - with a focus on Genome-Wide Association Studies. Charles Kooperberg

Building risk prediction models - with a focus on Genome-Wide Association Studies Risk prediction models Based on data: (D i, X i1,..., X ip ) i = 1,..., n we like to fit a model P(D = 1 X 1,..., X p )

Joint models for classification and comparison of mortality in different countries.

Joint models for classification and comparison of mortality in different countries. Viani D. Biatat 1 and Iain D. Currie 1 1 Department of Actuarial Mathematics and Statistics, and the Maxwell Institute

Copayments for Ambulatory Care in Germany: A Natural Experiment Using a Difference-in-Difference Approach

Copayments for Ambulatory Care in Germany: A Natural Experiment Using a Difference-in-Difference Approach SOEP User Conference 2008, Berlin Jonas Schreyögg 1 and Markus Grabka 2 1) Dept. Health Care Management,

Regularized Logistic Regression for Mind Reading with Parallel Validation

Regularized Logistic Regression for Mind Reading with Parallel Validation Heikki Huttunen, Jukka-Pekka Kauppi, Jussi Tohka Tampere University of Technology Department of Signal Processing Tampere, Finland

A Handbook of Statistical Analyses Using R. Brian S. Everitt and Torsten Hothorn

A Handbook of Statistical Analyses Using R Brian S. Everitt and Torsten Hothorn CHAPTER 6 Logistic Regression and Generalised Linear Models: Blood Screening, Women s Role in Society, and Colonic Polyps

Package dsmodellingclient

Package dsmodellingclient Maintainer Author Version 4.1.0 License GPL-3 August 20, 2015 Title DataSHIELD client site functions for statistical modelling DataSHIELD

The frequency of visiting a doctor: is the decision to go independent of the frequency?

Discussion Paper: 2009/04 The frequency of visiting a doctor: is the decision to go independent of the frequency? Hans van Ophem www.feb.uva.nl/ke/uva-econometrics Amsterdam School of Economics Department

Section 6: Model Selection, Logistic Regression and more...

Section 6: Model Selection, Logistic Regression and more... Carlos M. Carvalho The University of Texas McCombs School of Business http://faculty.mccombs.utexas.edu/carlos.carvalho/teaching/ 1 Model Building

Integrating DNA Motif Discovery and Genome-Wide Expression Analysis. Erin M. Conlon

Integrating DNA Motif Discovery and Genome-Wide Expression Analysis Department of Mathematics and Statistics University of Massachusetts Amherst Statistics in Functional Genomics Workshop Ascona, Switzerland

Model selection in R featuring the lasso. Chris Franck LISA Short Course March 26, 2013

Model selection in R featuring the lasso Chris Franck LISA Short Course March 26, 2013 Goals Overview of LISA Classic data example: prostate data (Stamey et. al) Brief review of regression and model selection.

How Many People Visit YouTube? Imputing Missing Events in Panels With Excess Zeros

How Many People Visit YouTube? Imputing Missing Events in Panels With Excess Zeros Georg M. Goerg, Yuxue Jin, Nicolas Remy, Jim Koehler 1 1 Google, Inc.; United States E-mail for correspondence: gmg@google.com

STATISTICA Formula Guide: Logistic Regression. Table of Contents

: Table of Contents... 1 Overview of Model... 1 Dispersion... 2 Parameterization... 3 Sigma-Restricted Model... 3 Overparameterized Model... 4 Reference Coding... 4 Model Summary (Summary Tab)... 5 Summary

ECLT5810 E-Commerce Data Mining Technique SAS Enterprise Miner -- Regression Model I. Regression Node

Enterprise Miner - Regression 1 ECLT5810 E-Commerce Data Mining Technique SAS Enterprise Miner -- Regression Model I. Regression Node 1. Some background: Linear attempts to predict the value of a continuous

Package bigdata. R topics documented: February 19, 2015

Type Package Title Big Data Analytics Version 0.1 Date 2011-02-12 Author Han Liu, Tuo Zhao Maintainer Han Liu Depends glmnet, Matrix, lattice, Package bigdata February 19, 2015 The

Web-based Supplementary Materials for Bayesian Effect Estimation. Accounting for Adjustment Uncertainty by Chi Wang, Giovanni

1 Web-based Supplementary Materials for Bayesian Effect Estimation Accounting for Adjustment Uncertainty by Chi Wang, Giovanni Parmigiani, and Francesca Dominici In Web Appendix A, we provide detailed

Predictive Modeling Techniques in Insurance

Predictive Modeling Techniques in Insurance Tuesday May 5, 2015 JF. Breton Application Engineer 2014 The MathWorks, Inc. 1 Opening Presenter: JF. Breton: 13 years of experience in predictive analytics

Incentive Eects in the Demand for Health Care: A Bivariate Panel Count Data Estimation Regina T. Riphahn 1 2 3 Achim Wambach 1 2 Andreas Million 1 3 1 University of Munich, 2 CEPR, London, 3 IZA, Bonn

Point Biserial Correlation Tests

Chapter 807 Point Biserial Correlation Tests Introduction The point biserial correlation coefficient (ρ in this chapter) is the product-moment correlation calculated between a continuous random variable

Lab 13: Logistic Regression

Lab 13: Logistic Regression Spam Emails Today we will be working with a corpus of emails received by a single gmail account over the first three months of 2012. Just like any other email address this account

Publication List. Chen Zehua Department of Statistics & Applied Probability National University of Singapore

Publication List Chen Zehua Department of Statistics & Applied Probability National University of Singapore Publications Journal Papers 1. Y. He and Z. Chen (2014). A sequential procedure for feature selection

SAS Software to Fit the Generalized Linear Model

SAS Software to Fit the Generalized Linear Model Gordon Johnston, SAS Institute Inc., Cary, NC Abstract In recent years, the class of generalized linear models has gained popularity as a statistical modeling

EVALUATION OF PROBABILITY MODELS ON INSURANCE CLAIMS IN GHANA

EVALUATION OF PROBABILITY MODELS ON INSURANCE CLAIMS IN GHANA E. J. Dadey SSNIT, Research Department, Accra, Ghana S. Ankrah, PhD Student PGIA, University of Peradeniya, Sri Lanka Abstract This study investigates

TOWARD BIG DATA ANALYSIS WORKSHOP

TOWARD BIG DATA ANALYSIS WORKSHOP 邁 向 巨 量 資 料 分 析 研 討 會 摘 要 集 2015.06.05-06 巨 量 資 料 之 矩 陣 視 覺 化 陳 君 厚 中 央 研 究 院 統 計 科 學 研 究 所 摘 要 視 覺 化 (Visualization) 與 探 索 式 資 料 分 析 (Exploratory Data Analysis, EDA)

Discussion Papers. Copayments for Ambulatory Care in Germany: A Natural Experiment Using a Difference-in- Difference Approach

Deutsches Institut für Wirtschaftsforschung www.diw.de Discussion Papers 777 Jonas Schreyögg Markus M. Grabka Copayments for Ambulatory Care in Germany: A Natural Experiment Using a Difference-in- Difference

CHAPTER 3 EXAMPLES: REGRESSION AND PATH ANALYSIS

Examples: Regression And Path Analysis CHAPTER 3 EXAMPLES: REGRESSION AND PATH ANALYSIS Regression analysis with univariate or multivariate dependent variables is a standard procedure for modeling relationships

Data analysis in supersaturated designs

Statistics & Probability Letters 59 (2002) 35 44 Data analysis in supersaturated designs Runze Li a;b;, Dennis K.J. Lin a;b a Department of Statistics, The Pennsylvania State University, University Park,

Introduction to Predictive Modeling Using GLMs

Introduction to Predictive Modeling Using GLMs Dan Tevet, FCAS, MAAA, Liberty Mutual Insurance Group Anand Khare, FCAS, MAAA, CPCU, Milliman 1 Antitrust Notice The Casualty Actuarial Society is committed

Factoring Trinomials: The ac Method

6.7 Factoring Trinomials: The ac Method 6.7 OBJECTIVES 1. Use the ac test to determine whether a trinomial is factorable over the integers 2. Use the results of the ac test to factor a trinomial 3. For

Does Black-Scholes framework for Option Pricing use Constant Volatilities and Interest Rates? New Solution for a New Problem

Does Black-Scholes framework for Option Pricing use Constant Volatilities and Interest Rates? New Solution for a New Problem Gagan Deep Singh Assistant Vice President Genpact Smart Decision Services Financial

Local classification and local likelihoods

Local classification and local likelihoods November 18 k-nearest neighbors The idea of local regression can be extended to classification as well The simplest way of doing so is called nearest neighbor

16 : Demand Forecasting

16 : Demand Forecasting 1 Session Outline Demand Forecasting Subjective methods can be used only when past data is not available. When past data is available, it is advisable that firms should use statistical

Gender Differences in Smoking Behavior

DISCUSSION PAPER SERIES IZA DP No. 2259 Gender Differences in Smoking Behavior Thomas Bauer Silja Göhlmann Mathias Sinning August 2006 Forschungsinstitut zur Zukunft der Arbeit Institute for the Study

Lecture 5 : The Poisson Distribution

Lecture 5 : The Poisson Distribution Jonathan Marchini November 10, 2008 1 Introduction Many experimental situations occur in which we observe the counts of events within a set unit of time, area, volume,

[3] Big Data: Model Selection

[3] Big Data: Model Selection Matt Taddy, University of Chicago Booth School of Business faculty.chicagobooth.edu/matt.taddy/teaching [3] Making Model Decisions Out-of-Sample vs In-Sample performance Regularization

Package metafuse. November 7, 2015

Type Package Package metafuse November 7, 2015 Title Fused Lasso Approach in Regression Coefficient Clustering Version 1.0-1 Date 2015-11-06 Author Lu Tang, Peter X.K. Song Maintainer Lu Tang

Automated Biosurveillance Data from England and Wales, 1991 2011

Article DOI: http://dx.doi.org/10.3201/eid1901.120493 Automated Biosurveillance Data from England and Wales, 1991 2011 Technical Appendix This online appendix provides technical details of statistical

Package EstCRM. July 13, 2015

Version 1.4 Date 2015-7-11 Package EstCRM July 13, 2015 Title Calibrating Parameters for the Samejima's Continuous IRT Model Author Cengiz Zopluoglu Maintainer Cengiz Zopluoglu

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

DO SPA VISITS IMPROVE HEALTH: EVIDENCE FROM GERMAN MICRO DATA. Jonathan Klick Florida State University College of Law

DO SPA VISITS IMPROVE HEALTH: EVIDENCE FROM GERMAN MICRO DATA Jonathan Klick Florida State University College of Law Thomas Stratmann George Mason University Abstract The health benefits of spas have been

More Flexible GLMs Zero-Inflated Models and Hybrid Models

More Flexible GLMs Zero-Inflated Models and Hybrid Models Mathew Flynn, Ph.D. Louise A. Francis FCAS, MAAA Motivation: GLMs are widely used in insurance modeling applications. Claim or frequency models

Package SurvCorr. February 26, 2015

Type Package Title Correlation of Bivariate Survival Times Version 1.0 Date 2015-02-25 Package SurvCorr February 26, 2015 Author Meinhard Ploner, Alexandra Kaider and Georg Heinze Maintainer Georg Heinze

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

Time Series Analysis of Network Traffic

Time Series Analysis of Network Traffic Cyriac James IIT MADRAS February 9, 211 Cyriac James (IIT MADRAS) February 9, 211 1 / 31 Outline of the presentation Background Motivation for the Work Network Trace

Modelling the Scores of Premier League Football Matches

Modelling the Scores of Premier League Football Matches by: Daan van Gemert The aim of this thesis is to develop a model for estimating the probabilities of premier league football outcomes, with the potential

Practical Differential Gene Expression. Introduction

Practical Differential Gene Expression Introduction In this tutorial you will learn how to use R packages for analysis of differential expression. The dataset we use are the gene-summarized count data

Pattern Analysis. Logistic Regression. 12. Mai 2009. Joachim Hornegger. Chair of Pattern Recognition Erlangen University

Pattern Analysis Logistic Regression 12. Mai 2009 Joachim Hornegger Chair of Pattern Recognition Erlangen University Pattern Analysis 2 / 43 1 Logistic Regression Posteriors and the Logistic Function Decision

University of Zurich. Happiness and unemployment: a panel data analysis for Germany. Zurich Open Repository and Archive. Winkelmann, L; Winkelmann, R

University of Zurich Zurich Open Repository and Archive Winterthurerstr. 190 CH-8057 Zurich http://www.zora.unizh.ch Year: 1995 Happiness and unemployment: a panel data analysis for Germany Winkelmann,

Causal Leading Indicators Detection for Demand Forecasting

Causal Leading Indicators Detection for Demand Forecasting Yves R. Sagaert, El-Houssaine Aghezzaf, Nikolaos Kourentzes, Bram Desmet Department of Industrial Management, Ghent University 13/07/2015 EURO

Addressing Analytics Challenges in the Insurance Industry. Noe Tuason California State Automobile Association

Addressing Analytics Challenges in the Insurance Industry Noe Tuason California State Automobile Association Overview Two Challenges: 1. Identifying High/Medium Profit who are High/Low Risk of Flight Prospects

Logistic Regression (1/24/13)

STA63/CBB540: Statistical methods in computational biology Logistic Regression (/24/3) Lecturer: Barbara Engelhardt Scribe: Dinesh Manandhar Introduction Logistic regression is model for regression used

BayesX - Software for Bayesian Inference in Structured Additive Regression

BayesX - Software for Bayesian Inference in Structured Additive Regression Thomas Kneib Faculty of Mathematics and Economics, University of Ulm Department of Statistics, Ludwig-Maximilians-University Munich

Logistic Regression for Spam Filtering

Logistic Regression for Spam Filtering Nikhila Arkalgud February 14, 28 Abstract The goal of the spam filtering problem is to identify an email as a spam or not spam. One of the classic techniques used

Evidence to Action: Use of Predictive Models for Beach Water Postings

Evidence to Action: Use of Predictive Models for Beach Water Postings Canadian Society for Epidemiology and Biostatistics Caitlyn Paget, June 4 th 2015 Goal is to improve program delivery Can we improve

BLOCKWISE SPARSE REGRESSION

Statistica Sinica 16(2006), 375-390 BLOCKWISE SPARSE REGRESSION Yuwon Kim, Jinseog Kim and Yongdai Kim Seoul National University Abstract: Yuan an Lin (2004) proposed the grouped LASSO, which achieves

Human Capital and Ethnic Self-Identification of Migrants

DISCUSSION PAPER SERIES IZA DP No. 2300 Human Capital and Ethnic Self-Identification of Migrants Laura Zimmermann Liliya Gataullina Amelie Constant Klaus F. Zimmermann September 2006 Forschungsinstitut

Association Between Variables

Contents 11 Association Between Variables 767 11.1 Introduction............................ 767 11.1.1 Measure of Association................. 768 11.1.2 Chapter Summary.................... 769 11.2 Chi

GLAM Array Methods in Statistics

GLAM Array Methods in Statistics Iain Currie Heriot Watt University A Generalized Linear Array Model is a low-storage, high-speed, GLAM method for multidimensional smoothing, when data forms an array,

Cloud Analytics for Capacity Planning and Instant VM Provisioning

Cloud Analytics for Capacity Planning and Instant VM Provisioning Yexi Jiang Florida International University Advisor: Dr. Tao Li Collaborator: Dr. Charles Perng, Dr. Rong Chang Presentation Outline Background

Elisa Iezzi* Matteo Lippi Bruni** Cristina Ugolini**

24-25 June 2010 Elisa Iezzi* Matteo Lippi Bruni** Cristina Ugolini** elisa.iezzi@unibo.it matteo.lippibruni2@unibo.it cristina.ugolini@unibo.it * Department of Statistics, University of Bologna **Department

5. Multiple regression

5. Multiple regression QBUS6840 Predictive Analytics https://www.otexts.org/fpp/5 QBUS6840 Predictive Analytics 5. Multiple regression 2/39 Outline Introduction to multiple linear regression Some useful

A Comparison of Variable Selection Techniques for Credit Scoring

1 A Comparison of Variable Selection Techniques for Credit Scoring K. Leung and F. Cheong and C. Cheong School of Business Information Technology, RMIT University, Melbourne, Victoria, Australia E-mail:

Entry Strategies, Founder s Human Capital and Start- Up Size

Entry Strategies, Founder s Human Capital and Start- Up Size Sandra Gottschalk, Kathrin Müller, and Michaela Niefert Centre for European Economic Research (ZEW), Mannheim, Germany First version (January,

Machine Learning Big Data using Map Reduce

Machine Learning Big Data using Map Reduce By Michael Bowles, PhD Where Does Big Data Come From? -Web data (web logs, click histories) -e-commerce applications (purchase histories) -Retail purchase histories

BOOSTED REGRESSION TREES: A MODERN WAY TO ENHANCE ACTUARIAL MODELLING

BOOSTED REGRESSION TREES: A MODERN WAY TO ENHANCE ACTUARIAL MODELLING Xavier Conort xavier.conort@gear-analytics.com Session Number: TBR14 Insurance has always been a data business The industry has successfully

Blockwise Sparse Regression

Blockwise Sparse Regression 1 Blockwise Sparse Regression Yuwon Kim, Jinseog Kim, and Yongdai Kim Seoul National University, Korea Abstract: Yuan an Lin (2004) proposed the grouped LASSO, which achieves

Online Appendix The Earnings Returns to Graduating with Honors - Evidence from Law Graduates

Online Appendix The Earnings Returns to Graduating with Honors - Evidence from Law Graduates Ronny Freier Mathias Schumann Thomas Siedler February 13, 2015 DIW Berlin and Free University Berlin. Universität

Lecture 3: Linear methods for classification

Lecture 3: Linear methods for classification Rafael A. Irizarry and Hector Corrada Bravo February, 2010 Today we describe four specific algorithms useful for classification problems: linear regression,

Acknowledgments. Data Mining with Regression. Data Mining Context. Overview. Colleagues

Data Mining with Regression Teaching an old dog some new tricks Acknowledgments Colleagues Dean Foster in Statistics Lyle Ungar in Computer Science Bob Stine Department of Statistics The School of the

HEALTH CARE REFORM AND THE NUMBER OF DOCTOR VISITS AN ECONOMETRIC ANALYSIS

JOURNAL OF APPLIED ECONOMETRICS J. Appl. Econ. 19: 455 472 (2004) Published online in Wiley InterScience (www.interscience.wiley.com). DOI: 10.1002/jae.764 HEALTH CARE REFORM AND THE NUMBER OF DOCTOR VISITS

Logistic Regression (a type of Generalized Linear Model)

Logistic Regression (a type of Generalized Linear Model) 1/36 Today Review of GLMs Logistic Regression 2/36 How do we find patterns in data? We begin with a model of how the world works We use our knowledge

Financial Vulnerability Index (IMPACT)

Household s Life Insurance Demand - a Multivariate Two Part Model Edward (Jed) W. Frees School of Business, University of Wisconsin-Madison July 30, 1 / 19 Outline 1 2 3 4 2 / 19 Objective To understand

Pearson's Correlation Tests

Chapter 800 Pearson's Correlation Tests Introduction The correlation coefficient, ρ (rho), is a popular statistic for describing the strength of the relationship between two variables. The correlation

Chapter Seven. Multiple regression An introduction to multiple regression Performing a multiple regression on SPSS

Chapter Seven Multiple regression An introduction to multiple regression Performing a multiple regression on SPSS Section : An introduction to multiple regression WHAT IS MULTIPLE REGRESSION? Multiple

Studying Auto Insurance Data

Studying Auto Insurance Data Ashutosh Nandeshwar February 23, 2010 1 Introduction To study auto insurance data using traditional and non-traditional tools, I downloaded a well-studied data from http://www.statsci.org/data/general/motorins.

Location matters. 3 techniques to incorporate geo-spatial effects in one's predictive model

Location matters. 3 techniques to incorporate geo-spatial effects in one's predictive model Xavier Conort xavier.conort@gear-analytics.com Motivation Location matters! Observed value at one location is

Asymmetric Information in the Portuguese Health Insurance Market

Asymmetric Information in the Portuguese Health Insurance Market Teresa Bago d Uva Instituto Nacional de Estatística J.M.C. Santos Silva ISEG/Universidade Técnica de Lisboa 1 1 Introduction ² The negative

Utilization of Home Healthcare Service by Medicare-Medicaid Dual Eligibles

ANNALS OF ECONOMICS AND FINANCE 6, 89 104 (2005) Utilization of Home Healthcare Service by Medicare-Medicaid Dual Eligibles Jaeun Shin KDI School of Public Policy and Management, Seoul, Korea E-mail: jshin@kdischool.ac.kr

Detection of changes in variance using binary segmentation and optimal partitioning

Detection of changes in variance using binary segmentation and optimal partitioning Christian Rohrbeck Abstract This work explores the performance of binary segmentation and optimal partitioning in the

Examining a Fitted Logistic Model

STAT 536 Lecture 16 1 Examining a Fitted Logistic Model Deviance Test for Lack of Fit The data below describes the male birth fraction male births/total births over the years 1931 to 1990. A simple logistic

APPLICATION OF LINEAR REGRESSION MODEL FOR POISSON DISTRIBUTION IN FORECASTING

APPLICATION OF LINEAR REGRESSION MODEL FOR POISSON DISTRIBUTION IN FORECASTING Sulaimon Mutiu O. Department of Statistics & Mathematics Moshood Abiola Polytechnic, Abeokuta, Ogun State, Nigeria. Abstract

Big Data Techniques Applied to Very Short-term Wind Power Forecasting

Big Data Techniques Applied to Very Short-term Wind Power Forecasting Ricardo Bessa Senior Researcher (ricardo.j.bessa@inesctec.pt) Center for Power and Energy Systems, INESC TEC, Portugal Joint work with

GLM with a Gamma-distributed Dependent Variable

GLM with a Gamma-distributed Dependent Variable Paul E. Johnson October 6, 204 Introduction I started out to write about why the Gamma distribution in a GLM is useful. In the end, I ve found it difficult

Department of Epidemiology and Public Health Miller School of Medicine University of Miami

Department of Epidemiology and Public Health Miller School of Medicine University of Miami BST 630 (3 Credit Hours) Longitudinal and Multilevel Data Wednesday-Friday 9:00 10:15PM Course Location: CRB 995

Basic Statistics and Data Analysis for Health Researchers from Foreign Countries

Basic Statistics and Data Analysis for Health Researchers from Foreign Countries Volkert Siersma siersma@sund.ku.dk The Research Unit for General Practice in Copenhagen Dias 1 Content Quantifying association

Cross Validation techniques in R: A brief overview of some methods, packages, and functions for assessing prediction models.

Cross Validation techniques in R: A brief overview of some methods, packages, and functions for assessing prediction models. Dr. Jon Starkweather, Research and Statistical Support consultant This month

CS231M Project Report - Automated Real-Time Face Tracking and Blending

CS231M Project Report - Automated Real-Time Face Tracking and Blending Steven Lee, slee2010@stanford.edu June 6, 2015 1 Introduction Summary statement: The goal of this project is to create an Android

Leadership Studies, Ph.D. University of San Diego. 2014 Exit Survey Results

Leadership Studies, Ph.D. School of Leadership and Education Sciences University of San Diego 2014 Exit Survey Results This report was prepared by the USD-SOLES Office of Assessment on October 6, 2014.

Penalized regression: Introduction

Penalized regression: Introduction Patrick Breheny August 30 Patrick Breheny BST 764: Applied Statistical Modeling 1/19 Maximum likelihood Much of 20th-century statistics dealt with maximum likelihood

Running Head: MONEY, WELL-BEING, AND LOSS AVERSION 1. Money, Well-Being, and Loss Aversion:

Running Head: MONEY, WELL-BEING, AND LOSS AVERSION 1 Money, Well-Being, and Loss Aversion: Does an Income Loss Have a Greater Effect on Well-Being than an Equivalent Income Gain? Christopher J. Boyce Behavioural

MISSING DATA TECHNIQUES WITH SAS. IDRE Statistical Consulting Group

MISSING DATA TECHNIQUES WITH SAS IDRE Statistical Consulting Group ROAD MAP FOR TODAY To discuss: 1. Commonly used techniques for handling missing data, focusing on multiple imputation 2. Issues that could

2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system

1. Systems of linear equations We are interested in the solutions to systems of linear equations. A linear equation is of the form 3x 5y + 2z + w = 3. The key thing is that we don t multiply the variables

From the help desk: Demand system estimation

The Stata Journal (2002) 2, Number 4, pp. 403 410 From the help desk: Demand system estimation Brian P. Poi Stata Corporation Abstract. This article provides an example illustrating how to use Stata to

GI01/M055 Supervised Learning Proximal Methods

GI01/M055 Supervised Learning Proximal Methods Massimiliano Pontil (based on notes by Luca Baldassarre) (UCL) Proximal Methods 1 / 20 Today s Plan Problem setting Convex analysis concepts Proximal operators

REPORT DOCUMENTATION PAGE

REPORT DOCUMENTATION PAGE Form Approved OMB NO. 0704-0188 Public Reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions,

Modelling and analysis of T-cell epitope screening data.

Modelling and analysis of T-cell epitope screening data. Tim Beißbarth 2, Jason A. Tye-Din 1, Gordon K. Smyth 1, Robert P. Anderson 1 and Terence P. Speed 1 1 WEHI, 1G Royal Parade, Parkville, VIC 3050,

Advertising, Alcohol, and Youth

ADVERTISING & MEDIA Is the alcoholic beverage industry targeting minors with magazine ads? Advertising, Alcohol, and Youth BY JON P. N ELSON Pennsylvania State University In 2001, the u.s. alcoholic beverage

Chapter 7. Lyapunov Exponents. 7.1 Maps

Chapter 7 Lyapunov Exponents Lyapunov exponents tell us the rate of divergence of nearby trajectories a key component of chaotic dynamics. For one dimensional maps the exponent is simply the average

The effect of private health insurance on medical care utilization and self-assessed health in Germany

HEDG Working Paper 09/17 The effect of private health insurance on medical care utilization and self-assessed health in Germany Patrick Hullegie Tobias J. Klein July 2009 ISSN 1751-1976 york.ac.uk/res/herc/hedgwp