![]() |type would use the factor type to set a differentĬolor and symbol for each level of type. Result of predict(model), type="terms")) as theĪ grouping variable can also be specified, so, for example Plot is against the first-order variable, which may be centered and scaledĭepending on how the arguments to the poly function. Plot is obtained using terms = ~ log(X1).įor polynomial terms generated using the poly function, the If a term like log(X1) is in the formula, then the corresponding To get a plot against fitted values only, use theĪrguments terms = ~ 1. X3 would plot against all termsĮxcept for X3. is to plot against all first-order terms. )Ī one-sided formula that specifies a subset of the terms that appear in the formula that defined the model. Plot = TRUE, quadratic = FALSE, smooth=TRUE. Xlab, ylab, lwd=1, grid=TRUE, key=!missing(groups). Quadratic = if(missing(groups)) TRUE else FALSE,Ĭol = carPalette(), col.quad = carPalette(), pch=1, ResidualPlot(model, variable = "fitted", type = "pearson", # residualPlots calls residualPlot, so these arguments can be Usage # This is a generic function with only one required argument:įitted=TRUE, AsIs=TRUE, plot=TRUE, tests=TRUE, groups. This is Tukey's test for nonadditivity when plotting against fitted values. For linear models curvature tests are computed for each of the plotsīy adding a quadratic term to the regression function and testing the quadratic to be zero. Residual Plots for Linear and Generalized Linear Models Descriptionĭraws a plot or plots of residuals versus one or more term in a mean function and/or versusįitted values. residualPlots: Residual Plots for Linear and Generalized Linear Models.powerTransform: Finding Univariate or Multivariate Power Transformations.poTest: Test for Proportional Odds in the Proportional-Odds.pointLabel: Label placement for points to avoid overlaps.ncvTest: Score Test for Non-Constant Error Variance.mcPlots: Draw Linear Model Marginal and Conditional Plots in Parallel.marginalModelPlot: Marginal Model Plotting.linearHypothesis: Test Linear Hypothesis.leveragePlots: Regression Leverage Plots.invTranPlot: Choose a Predictor Transformation Visually or Numerically.invResPlot: Inverse Response Plots to Transform the Response.influencePlot: Regression Influence Plot.influence-mixed-models: Influence Diagnostics for Mixed-Effects Models.Import: Import data from many file formats.hist.boot: Methods Functions to Support 'boot' Objects.hccm: Heteroscedasticity-Corrected Covariance Matrices.Export: Export a data frame to disk in one of many formats.Ellipses: Ellipses, Data Ellipses, and Confidence Ellipses.durbinWatsonTest: Durbin-Watson Test for Autocorrelated Errors.dfbetaPlots: dfbeta and dfbetas Index Plots.densityPlot: Nonparametric Density Estimates.deltaMethod: Estimate and Standard Error of a Nonlinear Function of.crPlots: Component+Residual (Partial Residual) Plots.Contrasts: Functions to Construct Contrasts.compareCoefs: Print estimated coefficients and their standard errors in a.carWeb: Access to the R Companion to Applied Regression Website.carPalette: Set or Retrieve 'car' Package Color Palette.car-internal: Internal Objects for the 'car' package.carHexsticker: View the Official Hex Sticker for the car Package.car-deprecated: Deprecated Functions in the car Package.car-defunct: Defunct Functions in the car Package.boxTidwell: Box-Tidwell Transformations.Boxplot: Boxplots With Point Identification.boxCoxVariable: Constructed Variable for Box-Cox Transformation.boxCox: Graph the profile log-likelihood for Box-Cox transformations.Boot: Bootstrapping for regression models.bcPower: Box-Cox, Box-Cox with Negatives Allowed, Yeo-Johnson and.Anova: Anova Tables for Various Statistical Models. ![]()
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