Applied regression analysis (1998)
Norman Richard Draper, Harry Allen Smith
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Dados técnicos
Editora: Wiley. Número de páginas: 736. Livro em inglês. 3ed, 1998.Comentários
Livro de regressão linear introdutória que pega um pouco mais leve na teoria e propõe uma abordagem mais didática ao invés de rigorosa.Capítulos
0) Basic Prerequisite Knowledge1) Fitting a Straight Line by Least Squares
2) Checking the Straight Line Fit
3) Fitting Straight Lines: Special Topics
4) Regression in Matrix Terms: Straight Line Case
5) The General Regression Situation
6) Extra Sums of Squares and Tests for Several Parameters Being Zero
7) Serial Correlation in the Residuals and the Durbin-Watson Test
8) More on Checking Fitted Models
9) Multiple Regression: Special Topics
10) Bias in Regression Estimates, and Expected Values of Mean Squares and Sums of Squares
11) On Worthwhile Regressions, Big F's, and R2
12) Models Containing Functions of the Predictors, Including Polynomial Models
13) Transformation of the Response Variable
14) "Dummy" Variables
15) Selecting the "Best" Regression Equation
16) Ill-Conditioning in Regression Data
17) Ridge Regression
18) Generalized Linear Models (GLIM)
19) Mixture Ingredients as Predictor Variables
20) The Geometry of Least Squares
21) More Geometry of Least Squares
22) Orthogonal Polynomials and Summary Data
23) Multiple Regression Applied to Analysis of Variance Problems
24) An Introduction to Nonlinear Estimation
25) Robust Regression
26) Resampling Procedures (Bootstrapping)
