simplereg: Simple linear and nonparametric regression

In BasketballAnalyzeR: Analysis and Visualization of Basketball Data

Description

Simple linear and nonparametric regression

Usage

simplereg(x, y, type = "lin", sp = NULL)

Arguments

x	numerical vector, input x values.
y	numerical vector, input y values.
type	character, type of regression; available options are: lin (linear regression, the default), pol (local polynomial regression of degree 2), ks (nonparametric kernel smoothing).
sp	numeric, parameter to control the degree of smoothing; span for local polynomial regression and bandwidth for ksmooth.

Value

An object of class simplereg, i.e. a list with the following objects:

• Model, the output model (linear regression, local polynomial regression, or kernel smoothing)

• R2, (in-sample) coefficient of determination

• x, input x values

• y, input y values

• type, type of regression

Author(s)

Marco Sandri, Paola Zuccolotto, Marica Manisera ([e-mail])

References

P. Zuccolotto and M. Manisera (2020) Basketball Data Science: With Applications in R. CRC Press.

See Also

loess, ksmooth

Examples

Pbox.sel <- subset(Pbox, MIN >= 500)
X <- Pbox.sel$AST/Pbox.sel$MIN
Y <- Pbox.sel$TOV/Pbox.sel$MIN
Pl <- Pbox.sel$Player
mod <- simplereg(x=X, y=Y, type="lin")

BasketballAnalyzeR documentation built on July 2, 2020, 2:14 a.m.