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Author Agung, I. Gusti Ngurah, author.

Title Quantile regression : applications on experimental and cross section data using EViews / I Gusti Ngurah Agung. [O'Reilly electronic resource]

Publication Info. Hoboken : John Wiley & Sons, Inc., 2021.
©2021
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Description 1 online resource (xviii, 473 pages) : illustrations (some color)
Bibliography Includes bibliographical references and index.
Summary "Quantile regression aims at estimating either the conditional median or other quantiles of the response variable. Essentially, quantile regression is the extension of linear regression and we use it when the conditions of linear regression are not applicable. LS-Regressions, Ordinary-Regressions or Mean-Regressions, the Quantile-Regressions (QRs) can be classified into three groups. The first group consists of the QRs with categorical variables, caller ANOVA QRs, where ordinal variables are treated as nominal variables and the numerical independent variables (IVs) are transformed to ordinal variables. The second group consists of the QRs with numerical variables, where the ordinal variables are treated as the numerical IVs. The third group consists of the various interaction QRs with numerical and categorical IV, where the ordinal variables can be treated as either numerical or nominal categorical IVs. Applications of Quantile Regression of Experimental and Cross Section Data using EViews presents examples of statistical results of various QRs in order to display their richer characteristics, based on the LS-Regression, Ordinary-Regressions, or Mean-Regressions. It offers instructions how to develop the best possible QRs and how to present more advanced analysis by using the Quantile Process, the Wald test, the Redundant Variables test, Omitted Variables Test, and forecasting, as well as to draw the best conclusions from results. A mathematical knowledge of quantile regression is not necessary so this book is applicable to students and lecturers in statistics, data analysis and engineering"-- Provided by publisher
Subject EViews (Computer file) http://id.loc.gov/authorities/names/no2007122127
EViews (Computer file) (OCoLC)fst01781707
Quantile regression. http://id.loc.gov/authorities/subjects/sh2013001932
Mathematical statistics. http://id.loc.gov/authorities/subjects/sh85082133
Mathematical statistics (OCoLC)fst01012127
Quantile regression (OCoLC)fst01896520
Genre Electronic books.
Other Form: Print version: Agung, I Gusti Ngurah. Quantile regression. First edition. Hoboken : Wiley, [2020] 9781119715177 (DLC) 2020025365
ISBN 1119715180 (electronic book)
9781119715160 (electronic book)
1119715164 (electronic book)
9781119714958 (electronic book)
1119714958 (electronic book)
9781119715184 (electronic bk.)
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