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OverviewFull Product DetailsAuthor: Kunio TakezawaPublisher: Springer Verlag, Japan Imprint: Springer Verlag, Japan Edition: Softcover reprint of the original 1st ed. 2014 Dimensions: Width: 15.50cm , Height: 1.70cm , Length: 23.50cm Weight: 4.745kg ISBN: 9784431561439ISBN 10: 4431561439 Pages: 300 Publication Date: 27 September 2016 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: In Print ![]() This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Language: English Table of ContentsChapter 1 Linear algebra. Starting up and executing R. Vectors. Matrices. Addition of two matrices. Multiplying two matrices. Identity and inverse matrices. Simultaneous equations. Diagonalization of a symmetric matrix. Quadratic forms.– Chapter 2 Distributions and tests. Sampling and random variables. Probability distribution. Normal distribution and the central limit theorem. Interval estimation by t distribution. t-test. Intervalestimation of population variance and the χ2 distribution. Fdistribution and F-test. Wilcoxon signed-rank sum test.– Chapter 3 Simple regression. Derivation of regression coefficients. Exchange between predictor variable and target variable. Regression to the mean. Confidence interval of regression coefficients in simple regression. t-Test in simple regression. F-teston simple regression. Selection between constant and nonconstant regression equations. Prediction error of simple regression. Weighted regression. Least squares method and prediction error.– Chapter 4 Multiple regression. Derivation of regression coefficients. Test on multiple regression. Prediction error on multiple regression. Notes on model selection using prediction error. Polynomial regression. Variance of regression coefficient and multicollinearity. Detection of multicollinearity using Variance Inflation Factors. Hessian matrix of log-likelihood.– Chapter 5 Akaike's Information Criterion (AIC) and the third variance. Cp and FPE. AIC of a multiple regression equation with independent and identical normal distribution. Derivation of AIC for multiple regression. AIC with unbiased estimator for error variance. Error variance by maximizing expectation of log-likelihood in light of the data in the future and the “third variance.” Relationship between AIC (or GCV) and F-test. AIC on Poisson regression.– Chapter 6 Linear mixed model. Random-effects model. Random intercept model. Random intercept and slope model. Generalized linear mixed model. Generalized additive mixed model.ReviewsFrom the reviews: The book uses a slightly different approach to teach applied statistics. ... The free software R has been used to make easy-to-use the statistical techniques considered in the book ... . the book is dedicated to readers of introductory texts in statistics, mainly for practical purposes. (Marina Gorunescu, zbMATH, Vol. 1281, 2014) From the reviews: The book uses a slightly different approach to teach applied statistics. ... The free software R has been used to make easy-to-use the statistical techniques considered in the book ... . the book is dedicated to readers of introductory texts in statistics, mainly for practical purposes. (Marina Gorunescu, zbMATH, Vol. 1281, 2014) Author InformationKunio Takezawa is senior research scientist at the National Agricultural Research Center of Japan and an associate professor in the Graduate School of Life and Environmental Sciences at the University of Tsukuba. He received B.A. and M.A. degrees in applied physics from Nagoya University and a Ph.D. in agricultural science from the University of Tokyo. Dr.Takezawa has served as a researcher at the National Institute of Agro-Environmental Sciences and as a senior researcher at the Hokuriku Agricultural Experiment Station. He and H. Omori (Tokyo University) translated Jeffrey S. Simonoff’s Smoothing Methodsin Statistics (Springer, 1996), which was published as Heikatsuka to nonparametric kaiki heno syotai by Norintokei-kyokaiin 1999 as the first Japanese textbook on nonparametric regression. He was recognized with awards from the Japan Science and Technology Agency in 1997 and the Japanese Agricultural Systems Society in 2002. Dr. Takezawa holds several patents for his inventions. Tab Content 6Author Website:Countries AvailableAll regions |