stat_out: stat_out

In JakubStats/marge: Multivariate Adaptive Regression splines using Generalized estimating Equations

stat_out

Description

Fits a linear regression model and calculates RSS/GCV measures (used for MARS linear models).

Usage

stat_out(Y, B1, TSS, GCV.null, pen = 2, ...)

Arguments

Y	: the response variable.
B1	: the model matrix of predictor variables.
TSS	: total sum of squares.
GCV.null	: GCV value for the intercept model.
pen	: the set/fixed penalty used for the GCV (the default is 2).
...	: further arguments passed to or from other methods.

Details

See the earth package for more details on the output measures calculated here.

Value

stat_out returns a list of values, consisting of: RSS, RSSq1, GCV1 and GCVq1 values for the fitted model.

Author(s)

Jakub Stoklosa and David I. Warton

References

Friedman, J. (1991). Multivariate adaptive regression splines. The Annals of Statistics, 19, 1–67.

Milborrow, S. (2017a). Notes on the earth package. Package vignette. Available at: http://127.0.0.1:31355/library/earth/doc/earth-notes.pdf.

Milborrow, S. (2017b). earth: Multivariate Adaptive Regression Splines. R package version 4.4.7. Available at http://CRAN.R-project.org/package = earth.

Stoklosa, J. and Warton, D.I. (2018). A generalized estimating equation approach to multivariate adaptive regression splines. Journal of Computational and Graphical Statistics, 27, 245–253.

See Also

stat_out_score_null and stat_out_score_glm_null

JakubStats/marge documentation built on Feb. 25, 2024, 9:38 p.m.