Download or read book A Monte Carlo Study of Feasible Predictors of the Linear Regression Model written by Howard L. Roth and published by . This book was released on 1985 with total page 90 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Study of Linear Regression Assumptions written by G. C. Sumner and published by . This book was released on 1969 with total page 41 pages. Available in PDF, EPUB and Kindle. Book excerpt: The report demonstrates the effects on linear regression estimates of variations in (1) the distribution of the dependent variable, (2) distribution of the independent variable, and (3) intercorrelation between independent variables. The basic approach is to premise a population model to reflect some underlying physical law or structural relationship, assign numerical values to parameters, and then introduce violations of the classical assumptions that might be typical in cost estimation problems. From the various cases thus constructed, samples are generated by computer in Monte Carlo fashion. This empirical study tests the sensitivity (in terms of bias and sampling variability) of regression coefficients and common statistical measures of reliability.
Download or read book A Monte Carlo Comparison of Stability and Accuracy of Prediction for Six Methods of Multiple Linear Regression written by Christopher W. Hornick and published by . This book was released on 1979 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Two Stage Estimation Methods in the Generalized Linear Regression Model written by and published by . This book was released on 1972 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Simulation Based Statistical Modeling written by Ding-Geng (Din) Chen and published by Springer. This book was released on 2017-02-01 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together expert researchers engaged in Monte-Carlo simulation-based statistical modeling, offering them a forum to present and discuss recent issues in methodological development as well as public health applications. It is divided into three parts, with the first providing an overview of Monte-Carlo techniques, the second focusing on missing data Monte-Carlo methods, and the third addressing Bayesian and general statistical modeling using Monte-Carlo simulations. The data and computer programs used here will also be made publicly available, allowing readers to replicate the model development and data analysis presented in each chapter, and to readily apply them in their own research. Featuring highly topical content, the book has the potential to impact model development and data analyses across a wide spectrum of fields, and to spark further research in this direction.
Download or read book Using R for Principles of Econometrics written by Constantin Colonescu and published by Lulu.com. This book was released on 2017-12-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.
Download or read book Prediction in Non linear Models written by Sean Scanlon Collins and published by . This book was released on 1988 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Evaluation of Ridge Regression as an Alternative to Ordinary Least Squares written by Bryan Walter Coyle and published by . This book was released on 1979 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Lectures on Monte Carlo Methods written by Neal Noah Madras and published by American Mathematical Soc.. This book was released on 2002 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monte Carlo methods form an experimental branch of mathematics that employs simulations driven by random number generators. These methods are often used when others fail, since they are much less sensitive to the ``curse of dimensionality'', which plagues deterministic methods in problems with a large number of variables. Monte Carlo methods are used in many fields: mathematics, statistics, physics, chemistry, finance, computer science, and biology, for instance. This book is an introduction to Monte Carlo methods for anyone who would like to use these methods to study various kinds of mathematical models that arise in diverse areas of application. The book is based on lectures in a graduate course given by the author. It examines theoretical properties of Monte Carlo methods as well as practical issues concerning their computer implementation and statistical analysis. The only formal prerequisite is an undergraduate course in probability. The book is intended to be accessible to students from a wide range of scientific backgrounds. Rather than being a detailed treatise, it covers the key topics of Monte Carlo methods to the depth necessary for a researcher to design, implement, and analyze a full Monte Carlo study of a mathematical or scientific problem. The ideas are illustrated with diverse running examples. There are exercises sprinkled throughout the text. The topics covered include computer generation of random variables, techniques and examples for variance reduction of Monte Carlo estimates, Markov chain Monte Carlo, and statistical analysis of Monte Carlo output.
Download or read book Estimation in Linear Models with Heteroscedasticity written by Susan Therese Vaitekunas and published by . This book was released on 1982 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Monte Carlo Simulation written by Christopher Z. Mooney and published by SAGE. This book was released on 1997-04-07 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Aimed at researchers across the social sciences, this book explains the logic behind the Monte Carlo simulation method and demonstrates its uses for social and behavioural research.
Download or read book A Monte Carlo Study of a Moderated Regression Model written by Alan L. Gross and published by . This book was released on 1970 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Analysis of Prediction in Regression with and Without Data Pooling written by Carl K. Brenner and published by . This book was released on 2002 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Study of the Relationship Between Linear Model Specification and Estimates of Lag one Error Autocorrelation in Data from a Single case N written by Marilyn F. Belwood and published by . This book was released on 1997 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Study of Power Analysis of Hierarchical Linear Model and Repeated Measures Approaches to Longitudinal Data Analysis written by Hua Fang and published by . This book was released on 2006 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Monte Carlo Study of the Regression Model with Autocorrelated Disturbances written by Clifford G. Hildreth and published by . This book was released on 1969 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt: The paper gives a description of the relative performance of estimators based on the results of a Monte Carlo experiment, under the assumption that disturbances are generated by a first-order autoregressive process. To generate artifical data for the experiment, eight structures were specified. For each structure, 300 samples were drawn and estimates of unknown parameters were calculated for each sample by five different methods, namely, maximum likelihood, Theil-Nager, approximate Bayes, Durbin, and least squares estimators. The task was first to examine the performance of the various estimators and second, to check the behavior of several commonly used tests of independence regression analysis. Characteristics of the various structures were chosen to represent a variety of circumstances that might be reasonably encountered in practical work.
Download or read book Monte Carlo Study of the Regression Model With Autocorrelated Disturbances written by Rand Corporation and published by . This book was released on 1967 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:
