John Fox – författare
3 434 kr
Skickas inom 3-6 vardagar
183 kr
Skickas inom 5-8 vardagar
102 kr
Läs direkt efter köp
269 kr
Skickas inom 3-6 vardagar
1 169 kr
Läs direkt efter köp
391 kr
Skickas inom 10-15 vardagar
849 kr
Skickas inom 10-15 vardagar
212 kr
Skickas inom 7-10 vardagar
535 kr
Skickas inom 10-15 vardagar
577 kr
Läs direkt efter köp
535 kr
Skickas inom 10-15 vardagar
577 kr
Läs direkt efter köp
2 712 kr
Skickas inom 3-6 vardagar
1 747 kr
Skickas inom 3-6 vardagar
Nonparametric Simple Regression
Smoothing Scatterplots
808 kr
Skickas inom 3-6 vardagar
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.
Multiple and Generalized Nonparametric Regression
808 kr
Skickas inom 3-6 vardagar
This book builds on John Fox's previous volume in the QASS Series, Non Parametric Simple Regression. In this monograph readers learn to estimate and plot smooth functions when there are multiple independent variables. 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.
2 343 kr
Skickas inom 10-15 vardagar
430 kr
Skickas inom 3-6 vardagar
494 kr
Skickas inom 3-6 vardagar
397 kr
Skickas inom 3-6 vardagar
501 kr
Skickas inom 3-6 vardagar
298 kr
Skickas inom 5-8 vardagar
306 kr
Skickas inom 5-8 vardagar
445 kr
Skickas inom 5-8 vardagar
302 kr
Skickas inom 5-8 vardagar
381 kr
Skickas inom 5-8 vardagar
220 kr
Skickas inom 5-8 vardagar
398 kr
Skickas inom 5-8 vardagar
285 kr
Skickas inom 5-8 vardagar
346 kr
Skickas inom 5-8 vardagar