Hrishikesh D Vinod Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software (Second Edition) 9789811256172

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Автор: Hrishikesh D Vinod
Название: Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software (Second Edition)
ISBN: 9789811256172
Издательство: World Scientific Publishing
Классификация:

Эконометрика

ISBN-10: 9811256179
Обложка/Формат: Hardback
Страницы: 644
Вес: 1.02 кг.
Дата издания: 05.05.2022
Язык: English
Издание: Second edition
Размер: 22.86 x 15.24 x 3.51 cm
Ключевые слова: Econometrics, BUSINESS & ECONOMICS / Econometrics,BUSINESS & ECONOMICS / Statistics,MATHEMATICS / Probability & Statistics / Time Series
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Поставляется из: Англии
Описание: How to learn both applied statistics (econometrics) and free, open-source software R? This book allows students to have a sense of accomplishment by copying and pasting many hands-on templates provided here.The textbook is essential for anyone wishing to have a practical understanding of an extensive range of topics in Econometrics. No other text provides software snippets to learn so many new statistical tools with hands-on examples. The explicit knowledge of inputs and outputs of each new method allows the student to know which algorithm is worth studying. The book offers sufficient theoretical and algorithmic details about a vast range of statistical techniques.The second editions preface lists the following topics generally absent in other textbooks. (i) Iteratively reweighted least squares, (ii) Pillar charts to represent 3D data. (iii) Stochastic frontier analysis (SFA) (iv) model selection with Mallows Cp criterion. (v) Hodrick-Prescott (HP) filter. (vi) Automatic ARIMA models. (vi) Nonlinear Granger-causality using kernel regressions and bootstrap confidence intervals. (vii) new Keynesian Phillips curve (NKPC). (viii) Market-neutral pairs trading using two cointegrated stocks. (ix) Artificial neural network (ANN) for product-specific forecasting. (x) Vector AR and VARMA models. (xi) New tools for diagnosing the endogeneity problem. (xii) The elegant set-up of k-class estimators and identification. (xiii) Probit-logit models and Heckman selection bias correction. (xiv) Receiver operating characteristic (ROC) curves and areas under them. (xv) Confusion matrix. (xvi) Quantile regression (xvii) Elastic net estimator. (xviii) generalized Correlations (xix) maximum entropy bootstrap for time series. (xx) Convergence concepts quantified. (xxi) Generalized partial correlation coefficients (xxii) Panel data and duration (survival) models.

Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software (Second Edition), Hrishikesh D Vinod