Learn R Programming

⚠️There's a newer version (3.1-3) of this package.Take me there.

car (version 3.0-10)

Companion to Applied Regression

Description

Functions to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage, 2019.

Copy Link

Version

Install

install.packages('car')

Monthly Downloads

596,351

Version

3.0-10

License

GPL (>= 2)

Maintainer

Last Published

September 29th, 2020

Functions in car (3.0-10)

Import

Import data from many file formats
Predict

Model Predictions
ScatterplotSmoothers

Smoothers to Draw Lines on Scatterplots
Ellipses

Ellipses, Data Ellipses, and Confidence Ellipses
Contrasts

Functions to Construct Contrasts
Anova

Anova Tables for Various Statistical Models
Export

Export a data frame to disk in one of many formats
Boxplot

Boxplots With Point Identification
Boot

Bootstrapping for regression models
S

Modified Functions for Summarizing Linear, Generalized Linear, and Some Other Models
car-defunct

Defunct Functions in the car Package
boxTidwell

Box-Tidwell Transformations
brief

Print Abbreviated Ouput
bcPower

Box-Cox, Box-Cox with Negatives Allowed, Yeo-Johnson and Basic Power Transformations
boxCox

Graph the profile log-likelihood for Box-Cox transformations in 1D, or in 2D with the bcnPower family.
boxCoxVariable

Constructed Variable for Box-Cox Transformation
avPlots

Added-Variable Plots
car-deprecated

Deprecated Functions in the car Package
Tapply

Apply a Function to a Variable Within Factor Levels
TransformationAxes

Axes for Transformed Variables
ceresPlots

Ceres Plots
carPalette

Set or Retrieve car Package Color Palette
carWeb

Access to the R Companion to Applied Regression Website
compareCoefs

Print estimated coefficients and their standard errors in a table for several regression models.
car-internal.Rd

Internal Objects for the car package
carHexsticker

View the Official Hex Sticker for the car Package
crPlots

Component+Residual (Partial Residual) Plots
densityPlot

Nonparametric Density Estimates
deltaMethod

Estimate and Standard Error of a Nonlinear Function of Estimated Regression Coefficients
dfbetaPlots

dfbeta and dfbetas Index Plots
durbinWatsonTest

Durbin-Watson Test for Autocorrelated Errors
influence.mixed.models

Influence Diagnostics for Mixed-Effects Models
invResPlot

Inverse Response Plots to Transform the Response
hccm

Heteroscedasticity-Corrected Covariance Matrices
leveneTest

Levene's Test
hist.boot

Methods Functions to Support boot Objects
leveragePlots

Regression Leverage Plots
infIndexPlot

Influence Index Plot
invTranPlot

Choose a Predictor Transformation Visually or Numerically
influencePlot

Regression Influence Plot
ncvTest

Score Test for Non-Constant Error Variance
panel.car

Panel Function for Coplots
poTest

Test for Proportional Odds in the Proportional-Odds Logistic-Regression Model
mmps

Marginal Model Plotting
logit

Logit Transformation
mcPlots

Draw Linear Model Marginal and Conditional Plots in Parallel or Overlaid
linearHypothesis

Test Linear Hypothesis
outlierTest

Bonferroni Outlier Test
powerTransform

Finding Univariate or Multivariate Power Transformations
qqPlot

Quantile-Comparison Plot
sigmaHat

Return the scale estimate for a regression model
some

Sample a Few Elements of an Object
regLine

Plot Regression Line
recode

Recode a Variable
showLabels

Functions to Identify and Mark Extreme Points in a 2D Plot.
scatterplot

Enhanced Scatterplots with Marginal Boxplots, Point Marking, Smoothers, and More
scatterplotMatrix

Scatterplot Matrices
symbox

Boxplots for transformations to symmetry
subsets

Plot Output from regsubsets Function in leaps package
spreadLevelPlot

Spread-Level Plots
whichNames

Position of Row Names
strings2factors

Convert Character-String Variables in a Data Frame to Factors
testTransform

Likelihood-Ratio Tests for Univariate or Multivariate Power Transformations to Normality
vif

Variance Inflation Factors
wcrossprod

Weighted Matrix Crossproduct
scatter3d

Three-Dimensional Scatterplots and Point Identification
residualPlots

Residual Plots for Linear and Generalized Linear Models