plot_matr: Correlation exploration using vectors or data frames

In MAGALA-RICHARD/cormat: What the Package Does (One Line, Title Case)

Correlation exploration using vectors or data frames

Description

plot_matr generate plots and fitted lines of significantly correlated variables for exploration.

Usage

plot_matr(y, df, nrow = 2, ncol = 2, sig.level = 0.05, ylab = "")

Arguments

y	is a response variable for exploring its relationship with the other predictor variables
df	data frame or a matrix with predictor variables
nrow	specifies the number of plots to be inserted in a row
ncol	specifies the number of plots to be inserted in a column
sig.level	specifies the number significant level default is 0.05
ylab	specifies the y-axis, which is the name of the respons variables defaults is the y names

Details

This function allows you to visualize the correlated variables with the selected variable. the fitted line is through regression It takes on an array or a data frame. if a vector is passed to the function it will be converted into a data frame Check if all the variables are numeric and not strings

Value

a matrix of plots

Author(s)

Richard Magala, 2022

MAGALA-RICHARD/cormat documentation built on July 8, 2022, 12:14 p.m.