Nonparametric simple regression : smoothing plots /

Unfortunately, researchers have not had accessible information on nonparametric regression analysis, until now. Beginning with presentation of nonparametric regression based on dividing the data into bins and averaging the response values in each bin, Fox introduces readers to the techniques of kern...

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Bibliographic Details
Main Author: Fox, John, 1947-
Format: Book
Language:English
Published: Thousand Oaks, CA : Sage Publications, c2000
Series:Quantitative applications in the social sciences ; no. 07-130
Subjects:
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245 1 0 |a Nonparametric simple regression :  |b smoothing plots /  |c by John Fox 
260 |a Thousand Oaks, CA :  |b Sage Publications,  |c c2000 
300 |a viii, 83 p. :  |b ill. ;  |c 22 cm 
490 1 |a Quantitative applications in the social sciences ;  |v v. 130 
504 |a Includes bibliographical references 
505 0 0 |g 1  |t What Is Nonparametric Regression? --  |g 2.  |t Binning and Local Averaging --  |g 3.  |t Kernel Estimation --  |g 4.  |t Local Polynomial Regression --  |g 5.  |t Statistical Inference for Local-Polynomial Regression --  |g 6.  |t Splines --  |g 7.  |t Nonparametric Regression and Data Analysis. 
520 |a Unfortunately, researchers have not had accessible information on nonparametric regression analysis, until now. Beginning with presentation of nonparametric regression based on dividing the data into bins and averaging the response values in each bin, Fox introduces readers to the techniques of kernel estimation, additive nonparametric regression, and the ways nonparametric regression can be employed to select transformations of the data preceding a linear least-squares fit. The book concludes with ways nonparametric regression can be generalized to logit, probit, and Poisson regression."--Pub. desc 
520 |a "While regression analysis traces the dependence of the distribution of a response variable to see if it bears a particular (linear) relationship to one or more of the predictors, nonparametric regression analysis makes minimal assumptions about the form of relationship between the average response and the predictors. This makes nonparametric regression a more useful technique for analyzing data in which there are several predictors that may combine additively to influence the response. (An example could be something like birth order/gender/and temperament on achievement motivation) 
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650 0 |a Social sciences  |x Research  |x Statistical methods 
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