infIndexPlot.mlm | R Documentation |
Provides index plots of some diagnostic measures for a multivariate linear model: Cook's distance, a generalized (squared) studentized residual, hat-values (leverages), and Mahalanobis squared distances of the residuals.
## S3 method for class 'mlm' infIndexPlot( model, infl = mlm.influence(model, do.coef = FALSE), FUN = det, vars = c("Cook", "Studentized", "hat", "DSQ"), main = paste("Diagnostic Plots for", deparse(substitute(model))), pch = 19, labels, id.method = "y", id.n = if (id.method[1] == "identify") Inf else 0, id.cex = 1, id.col = palette()[1], id.location = "lr", grid = TRUE, ... )
model |
A multivariate linear model object of class |
infl |
influence measure structure as returned by
|
FUN |
For |
vars |
All the quantities listed in this argument are plotted. Use
|
main |
main title for graph |
pch |
Plotting character for points |
id.method, labels, id.n, id.cex, id.col, id.location |
Arguments for the
labeling of points. The default is |
grid |
If TRUE, the default, a light-gray background grid is put on the graph |
... |
Arguments passed to |
This function produces index plots of the various influence measures
calculated by influence.mlm
, and in addition, the measure
based on the Mahalanobis squared distances of the residuals from the origin.
None. Used for its side effect of producing a graph.
Michael Friendly; borrows code from car::infIndexPlot
Barrett, B. E. and Ling, R. F. (1992). General Classes of Influence Measures for Multivariate Regression. Journal of the American Statistical Association, 87(417), 184-191.
Barrett, B. E. (2003). Understanding Influence in Multivariate Regression Communications in Statistics - Theory and Methods, 32, 667-680.
influencePlot.mlm
,
Mahalanobis
, infIndexPlot
,
# iris data data(iris) iris.mod <- lm(as.matrix(iris[,1:4]) ~ Species, data=iris) infIndexPlot(iris.mod, col=iris$Species, id.n=3) # Sake data data(Sake, package="heplots") Sake.mod <- lm(cbind(taste,smell) ~ ., data=Sake) infIndexPlot(Sake.mod, id.n=3) # Rohwer data data(Rohwer, package="heplots") Rohwer2 <- subset(Rohwer, subset=group==2) rownames(Rohwer2)<- 1:nrow(Rohwer2) rohwer.mlm <- lm(cbind(SAT, PPVT, Raven) ~ n + s + ns + na + ss, data=Rohwer2) infIndexPlot(rohwer.mlm, id.n=3)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.