new_x: Create test input points for prediction

In jtimonen/lgpr: Longitudinal Gaussian Process Regression

Create test input points for prediction

Description

Replaces a continuous variable x in the data frame, and possibly another continuous variable x_ns derived from it, with new values, for each level of a grouping factor (usually id)

Usage

new_x(data, x_values, group_by = "id", x = "age", x_ns = NULL)

Arguments

data	A data frame. Can also be an lgpfit or lgpmodel object, in which case data is extracted from it.
x_values	the values of x to set for each individual
group_by	name of the grouping variable, must be a factor in data (or use group_by=NA to create a dummy grouping factor which has only one value)
x	of the variable along which to extend, must be a numeric in data
x_ns	of a nonstationary variable derived from x, must be a numeric in data

Value

a data frame containing the following columns

• all factors in the original data

• x

• x_ns (unless it is NULL)

See Also

Other data frame handling functions: add_dis_age(), add_factor(), add_factor_crossing(), adjusted_c_hat(), split()

jtimonen/lgpr documentation built on Sept. 15, 2024, 1:08 a.m.