SLR_prediction.matrix: SLR prediction S3 method for matrices

In EmanuelSommer/SLRprediction: A quick and easy way of predicting within a simple linear regression model + visualization

Description

Predicting with a simple linear regression model

Usage

## S3 method for class 'matrix'
SLR_prediction(y, col_response = 1,
  col_exploratory = 2, pre_x_value = mean(y[, col_exploratory]))

Arguments

y	a numeric matrix containing the response and exploratory variable
col_response	column number of the response variable within y (default is 1)
col_exploratory	column number of the exploratory variable within y (default is 2)
pre_x_value	the numeric value (within the range of the exploratory vector) for which the prediction is made

Details

The function first builds a simple linear regression model with one response and one exploratory variable. Then the prediction for a given value of the exploratory variable (default the mean and no out of sample predictions) gets returned.

Value

the predicted value of the response variable

Author(s)

Emanuel Sommer

See Also

SLR_prediction_vis

Examples

special <- 6
Y<-matrix(data = append(1:5,c(1,3,4.5,7,8)),byrow = FALSE,ncol = 2)
SLR_prediction(Y,pre_x_value = special)

EmanuelSommer/SLRprediction documentation built on Nov. 22, 2020, 3:18 p.m.