Titlebook: Regression; Models, Methods and Ludwig Fahrmeir,Thomas Kneib,Brian D. Marx Textbook 2021Latest edition Springer-Verlag GmbH Germany, part

sustained

書(shū)目名稱Regression影響因子(影響力)




書(shū)目名稱Regression影響因子(影響力)學(xué)科排名




書(shū)目名稱Regression網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Regression網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Regression被引頻次




書(shū)目名稱Regression被引頻次學(xué)科排名




書(shū)目名稱Regression年度引用




書(shū)目名稱Regression年度引用學(xué)科排名




書(shū)目名稱Regression讀者反饋




書(shū)目名稱Regression讀者反饋學(xué)科排名

harbinger

Promotion

小歌劇

Categorical Regression Models, may express their opinion about some product in ordered categories ranging from “very satisfied” to “not satisfied at all.” Similarly, voters choose between several parties or they assess the quality of candidates in ordered categories.

investigate

Introduction, grown children. He examined the . between the body heights of the children and the average body height of both parents. To adjust for the natural height differences across gender, the body height of women was multiplied by a factor of 1.08. In order to better examine this relationship, he listed all his data in a contingency table (Table?.).

追逐

Introduction,ally known for the Galton board which provides a demonstration of the principles underlying the binomial distribution. At the end of the nineteenth century, Galton was mainly interested in questions regarding heredity. Galton collected extensive data illustrating the body height of parents and their

right-atrium

The Classical Linear Model,ect.?.. In addition to their direct application, linear regression models are also the basis of a variety of more complex regression methods. Examples are generalized linear models (Chap.?.), mixed models (Chap.?.), or semiparametric models (Chaps.?. and .).

Promotion

Generalized Linear Models,propriate transformation is needed to ensure approximate normality of the response. In addition, the expectation of the response is assumed to be a linear combination of covariates. Again, these covariates may be transformed before being included in the linear predictor. However, in many application

未成熟

Categorical Regression Models,y applications response variables often have more than two categories. For example, consumers may choose between different brands of a product or they may express their opinion about some product in ordered categories ranging from “very satisfied” to “not satisfied at all.” Similarly, voters choose

promote