Topics in Statistical Simulation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Topics in Statistical Simulation write by V.B. Melas. This book was released on 2014-12-05. Topics in Statistical Simulation available in PDF, EPUB and Kindle. The Department of Statistical Sciences of the University of Bologna in collaboration with the Department of Management and Engineering of the University of Padova, the Department of Statistical Modelling of Saint Petersburg State University, and INFORMS Simulation Society sponsored the Seventh Workshop on Simulation. This international conference was devoted to statistical techniques in stochastic simulation, data collection, analysis of scientific experiments, and studies representing broad areas of interest. The previous workshops took place in St. Petersburg, Russia in 1994, 1996, 1998, 2001, 2005, and 2009. The Seventh Workshop took place in the Rimini Campus of the University of Bologna, which is in Rimini’s historical center.
Essentials of Monte Carlo Simulation
Essentials of Monte Carlo Simulation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Essentials of Monte Carlo Simulation write by Nick T. Thomopoulos. This book was released on 2012-12-19. Essentials of Monte Carlo Simulation available in PDF, EPUB and Kindle. Essentials of Monte Carlo Simulation focuses on the fundamentals of Monte Carlo methods using basic computer simulation techniques. The theories presented in this text deal with systems that are too complex to solve analytically. As a result, readers are given a system of interest and constructs using computer code, as well as algorithmic models to emulate how the system works internally. After the models are run several times, in a random sample way, the data for each output variable(s) of interest is analyzed by ordinary statistical methods. This book features 11 comprehensive chapters, and discusses such key topics as random number generators, multivariate random variates, and continuous random variates. Over 100 numerical examples are presented as part of the appendix to illustrate useful real world applications. The text also contains an easy to read presentation with minimal use of difficult mathematical concepts. Very little has been published in the area of computer Monte Carlo simulation methods, and this book will appeal to students and researchers in the fields of Mathematics and Statistics.
Topics in Statistical Simulation
Topics in Statistical Simulation - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Topics in Statistical Simulation write by V. B. Melas. This book was released on 2014-12-31. Topics in Statistical Simulation available in PDF, EPUB and Kindle.
The Foundations of Statistics: A Simulation-based Approach
The Foundations of Statistics: A Simulation-based Approach - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Foundations of Statistics: A Simulation-based Approach write by Shravan Vasishth. This book was released on 2010-11-11. The Foundations of Statistics: A Simulation-based Approach available in PDF, EPUB and Kindle. Statistics and hypothesis testing are routinely used in areas (such as linguistics) that are traditionally not mathematically intensive. In such fields, when faced with experimental data, many students and researchers tend to rely on commercial packages to carry out statistical data analysis, often without understanding the logic of the statistical tests they rely on. As a consequence, results are often misinterpreted, and users have difficulty in flexibly applying techniques relevant to their own research — they use whatever they happen to have learned. A simple solution is to teach the fundamental ideas of statistical hypothesis testing without using too much mathematics. This book provides a non-mathematical, simulation-based introduction to basic statistical concepts and encourages readers to try out the simulations themselves using the source code and data provided (the freely available programming language R is used throughout). Since the code presented in the text almost always requires the use of previously introduced programming constructs, diligent students also acquire basic programming abilities in R. The book is intended for advanced undergraduate and graduate students in any discipline, although the focus is on linguistics, psychology, and cognitive science. It is designed for self-instruction, but it can also be used as a textbook for a first course on statistics. Earlier versions of the book have been used in undergraduate and graduate courses in Europe and the US. ”Vasishth and Broe have written an attractive introduction to the foundations of statistics. It is concise, surprisingly comprehensive, self-contained and yet quite accessible. Highly recommended.” Harald Baayen, Professor of Linguistics, University of Alberta, Canada ”By using the text students not only learn to do the specific things outlined in the book, they also gain a skill set that empowers them to explore new areas that lie beyond the book’s coverage.” Colin Phillips, Professor of Linguistics, University of Maryland, USA
Monte Carlo Simulation and Resampling Methods for Social Science
Monte Carlo Simulation and Resampling Methods for Social Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Monte Carlo Simulation and Resampling Methods for Social Science write by Thomas M. Carsey. This book was released on 2013-08-05. Monte Carlo Simulation and Resampling Methods for Social Science available in PDF, EPUB and Kindle. Taking the topics of a quantitative methodology course and illustrating them through Monte Carlo simulation, this book examines abstract principles, such as bias, efficiency, and measures of uncertainty in an intuitive, visual way. Instead of thinking in the abstract about what would happen to a particular estimator "in repeated samples," the book uses simulation to actually create those repeated samples and summarize the results. The book includes basic examples appropriate for readers learning the material for the first time, as well as more advanced examples that a researcher might use to evaluate an estimator he or she was using in an actual research project. The book also covers a wide range of topics related to Monte Carlo simulation, such as resampling methods, simulations of substantive theory, simulation of quantities of interest (QI) from model results, and cross-validation. Complete R code from all examples is provided so readers can replicate every analysis presented using R.
