You are here

Nonparametric Simple Regression
Share

Nonparametric Simple Regression
Smoothing Scatterplots



January 2000 | 96 pages | SAGE Publications, Inc

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).

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.

Learn more about "The Little Green Book" - QASS Series! Click Here


 
What Is Nonparametric Regression?
 
Binning and Local Averaging
 
Kernel Estimation
 
Local Polynomial Regression
 
Splines
 
Nonparametric Regression and Data Analysis

Preview this book

For instructors

To inquire about the availability of this title for review (print and/or digital), please contact your local sales representative or call (800) 818-7243.

Select a Purchasing Option

Electronic version
Prices from
$11.00*
*180 day rental

This title is also available on SAGE Knowledge, the ultimate social sciences online library. If your library doesn’t have access, ask your librarian to start a trial.