Nonparametric Simple Regression

Smoothing Scatterplots

By:

John Fox

Format:

Paperback / softback

Series:

Quantitative Applications in the Social Sciences

Show Hide Adult Content

$117.00

Available from supplier

Usually ships in 3-4 weeks

0 in Trolley

Price Match

Wrap this item as a gift ($5.90) - add a free gift card on the next page

Free Delivery with Primate

Join Now

Free 14 day free trial, cancel anytime.

Buy Now, Pay Later with:

4 payments of $29.25 with Afterpay Learn more

6 weekly interest-free payments of $19.50 with Laybuy Learn more

Availability

Delivering to:

Estimated arrival:

Around 4-14 June using International Courier

Description

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.

Author Biography:

John Fox received a BA from the City College of New York and a PhD from the University of Michigan, both in Sociology. He is Professor Emeritus of Sociology at McMaster University in Hamilton, Ontario, Canada, where he was previously the Senator William McMaster Professor of Social Statistics. Prior to coming to McMaster, he was Professor of Sociology, Professor of Mathematics and Statistics, and Coordinator of the Statistical Consulting Service at York University in Toronto. Professor Fox is the author of many articles and books on applied statistics, including \emph{Applied Regression Analysis and Generalized Linear Models, Third Edition} (Sage, 2016). He is an elected member of the R Foundation, an associate editor of the Journal of Statistical Software, a prior editor of R News and its successor the R Journal, and a prior editor of the Sage Quantitative Applications in the Social Sciences monograph series.

Release date NZ

March 15th, 2000

Author

John Fox

Audience

Tertiary Education (US: College)

Pages

Series

Quantitative Applications in the Social Sciences

Dimensions

140x216x6

ISBN-13

9780761915850

Product ID

2065261

Customer reviews

Nobody has reviewed this product yet. You could be the first!

Write a Review

Marketplace listings

There are no Marketplace listings available for this product currently.
Already own it? Create a free listing and pay just 9% commission when it sells!

Sell Yours Here