grnn.partial: Derive the partial effect of a predictor used in a GRNN

In yager: Yet Another General Regression Neural Network

Description

The function grnn.partial derives the partial effect of a predictor used in a GRNN by average-out values of the rest predictors.

Usage

grnn.partial(net, i, plot = TRUE)

Arguments

net	The GRNN object generated by grnn.fit()
i	The ith predictor in the GRNN
plot	TRUE or FALSE to plot the partial effect

Value

A plot of the partial effect or a dataframe of the partial effect

See Also

grnn.margin

Examples

data(iris, package = "datasets")
Y <- ifelse(iris[, 5] == "setosa", 1, 0)
X <- scale(iris[, 1:4])
gnet <- grnn.fit(x = X, y = Y)
## Not run: 
grnn.partial(gnet, 1, plot = FALSE)

## End(Not run)

yager documentation built on Oct. 26, 2020, 1:06 a.m.