Author: M. Hashem PesaranPublisher:
ISBN: 9780868311418
Category : Econometrics
Languages : en
Pages : 10
Book Description
Tests of Non-nested Linear Regression Models Subject to Linear Restrictions
Author: M. Hashem PesaranPublisher:
ISBN: 9780868311418
Category : Econometrics
Languages : en
Pages : 10
Book Description
Time Series and Panel Data Econometrics
Author: M. Hashem PesaranPublisher: Oxford University Press
ISBN: 0198736916
Category : Business & Economics
Languages : en
Pages : 1095
Book Description
This book is concerned with recent developments in time series and panel data techniques for the analysis of macroeconomic and financial data. It provides a rigorous, nevertheless user-friendly, account of the time series techniques dealing with univariate and multivariate time series models, as well as panel data models. It is distinct from other time series texts in the sense that it also covers panel data models and attempts at a more coherent integration of time series, multivariate analysis, and panel data models. It builds on the author's extensive research in the areas of time series and panel data analysis and covers a wide variety of topics in one volume. Different parts of the book can be used as teaching material for a variety of courses in econometrics. It can also be used as reference manual. It begins with an overview of basic econometric and statistical techniques, and provides an account of stochastic processes, univariate and multivariate time series, tests for unit roots, cointegration, impulse response analysis, autoregressive conditional heteroskedasticity models, simultaneous equation models, vector autoregressions, causality, forecasting, multivariate volatility models, panel data models, aggregation and global vector autoregressive models (GVAR). The techniques are illustrated using Microfit 5 (Pesaran and Pesaran, 2009, OUP) with applications to real output, inflation, interest rates, exchange rates, and stock prices.
The Robustness of Model Selection Rules
Author: Jochen A. JungeilgesPublisher: LIT Verlag Münster
ISBN:
Category : Business & Economics
Languages : en
Pages : 276
Book Description
Journal of Econometrics
Author: Applied Linear Statistical Models
Author: Michael H. KutnerPublisher: McGraw-Hill/Irwin
ISBN: 9780072386882
Category : Mathematics
Languages : en
Pages : 1396
Book Description
Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Modern Statistics with R
Author: Måns ThulinPublisher:
ISBN: 9781032497457
Category : Mathematics
Languages : en
Pages : 0
Book Description
The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. Modern Statistics with R introduces you to key parts of this modern statistical toolkit. It teaches you: Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. Exploratory data analysis - using visualisations and multivariate techniques to explore datasets. Statistical inference - modern methods for testing hypotheses and computing confidence intervals. Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. Ethics in statistics - ethical issues and good statistical practice. R programming - writing code that is fast, readable, and (hopefully!) free from bugs. No prior programming experience is necessary. Clear explanations and examples are provided to accommodate readers at all levels of familiarity with statistical principles and coding practices. A basic understanding of probability theory can enhance comprehension of certain concepts discussed within this book. In addition to plenty of examples, the book includes more than 200 exercises, with fully worked solutions available at: www.modernstatisticswithr.com.
ECNOMICS LETTERS
Author: Econometric Models, Techniques, and Applications
Author: Michael D. IntriligatorPublisher: Pearson
ISBN:
Category : Business & Economics
Languages : en
Pages : 684
Book Description
This book surveys the theories, techniques (model- building and data collection), and applications of econometrics. KEY TOPICS: It focuses on those aspects of econometrics that are of major importance to readers and researchers interested in performing, evaluating, or understanding econometric studies in a variety of areas. It reviews matrix notation and the use of multivariate statistics; discusses the specification of the model and the development of data for its estimation; covers recent developments in econometric models, techniques, and applications; explains the estimation of single-equation models; and provides case studies of the applications of econometrics to a wide array of areas -- including traditional areas such as the estimation of demand functions and production functions, and macroeconometric models.
Learning Statistics with R
Author: Daniel NavarroPublisher: Lulu.com
ISBN: 1326189727
Category : Computers
Languages : en
Pages : 617
Book Description
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Beyond Multiple Linear Regression
Author: Paul RobackPublisher: CRC Press
ISBN: 1439885400
Category : Mathematics
Languages : en
Pages : 436
Book Description
Beyond Multiple Linear Regression: Applied Generalized Linear Models and Multilevel Models in R is designed for undergraduate students who have successfully completed a multiple linear regression course, helping them develop an expanded modeling toolkit that includes non-normal responses and correlated structure. Even though there is no mathematical prerequisite, the authors still introduce fairly sophisticated topics such as likelihood theory, zero-inflated Poisson, and parametric bootstrapping in an intuitive and applied manner. The case studies and exercises feature real data and real research questions; thus, most of the data in the textbook comes from collaborative research conducted by the authors and their students, or from student projects. Every chapter features a variety of conceptual exercises, guided exercises, and open-ended exercises using real data. After working through this material, students will develop an expanded toolkit and a greater appreciation for the wider world of data and statistical modeling. A solutions manual for all exercises is available to qualified instructors at the book’s website at www.routledge.com, and data sets and Rmd files for all case studies and exercises are available at the authors’ GitHub repo (https://github.com/proback/BeyondMLR)