get_predictions_lin: Predictions for linear regression

In CARRoT: Predicting Categorical and Continuous Outcomes Using One in Ten Rule

Predictions for linear regression

Description

Function which runs a linear regression on a training set, computes predictions for the test set

Usage

get_predictions_lin(trset,testset,outc,k,n_tr,p,Rsq,Rsq_v,marg)

Arguments

trset	values of predictors on the training set
testset	values of predictors on the test set
outc	values of predictors on the training set
k	length of the test set
n_tr	size of the training set
p	weight of the model
Rsq	whether the R-squared statistics constraint is introduced
Rsq_v	value of R-squared statistics on the training spli of the data
marg	margin of error for R-squared statistics constraint

Value

An array of continous variables of the length equal to the size of a testset

See Also

Function uses function lsfit and coef

Examples

trset<-matrix(c(rnorm(90,2,4),runif(90,0,0.5),rbinom(90,1,0.5)),ncol=3)

testset<-matrix(c(rnorm(10,2,4),runif(10,0,0.5),rbinom(10,1,0.5)),ncol=3)

get_predictions_lin(trset,testset,runif(90,0,1),10)

CARRoT documentation built on Oct. 14, 2023, 1:06 a.m.