Hands-On Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software Second Edition | 2 Edition

Compare Textbook Prices for Hands-On Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software Second Edition 2 Edition ISBN 9789811256738 by Vinod, Hrishikesh D
Author: Vinod, Hrishikesh D
ISBN:981125673X
ISBN-13: 9789811256738
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Details about Hands-On Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software Second Edition:

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 edition's 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.

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Hi my name is Santanu, I have a master's degree in applied mathematics from Trinity College(Dublin Ireland) ,with a minor in chemistry and physics. I am a CRLA ( College Reading and Learning Association) certified tutor and held the position of head math and science tutor at Oakland Community College. I have several years of experience in tutoring chemistry, math and physics. I have tutored students ranging from elementary school level to college level. My teaching style involves detailed explan ... Read more

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