nlme: pairs.lmList – R documentation

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pairs.lmList

Pairs Plot of an lmList Object

Description

Diagnostic plots for the linear model fits corresponding to the x components are obtained. The form argument gives considerable flexibility in the type of plot specification. A conditioning expression (on the right side of a | operator) always implies that different panels are used for each level of the conditioning factor, according to a Trellis display. The expression on the right hand side of the formula, before a | operator, must evaluate to a data frame with at least two columns. If the data frame has two columns, a scatter plot of the two variables is displayed (the Trellis function xyplot is used). Otherwise, if more than two columns are present, a scatter plot matrix with pairwise scatter plots of the columns in the data frame is displayed (the Trellis function splom is used).

Usage

## S3 method for class 'lmList'
pairs(x, form, label, id, idLabels, grid, ...)

Arguments

`x`	an object inheriting from class `"lmList"`, representing a list of `lm` objects with a common model.
`form`	an optional one-sided formula specifying the desired type of plot. Any variable present in the original data frame used to obtain `x` can be referenced. In addition, `x` itself can be referenced in the formula using the symbol `"."`. Conditional expressions on the right of a `\|` operator can be used to define separate panels in a Trellis display. The expression on the right hand side of `form`, and to the left of the `\|` operator, must evaluate to a data frame with at least two columns. Default is `~ coef(.)` , corresponding to a pairs plot of the coefficients of `x`.
`label`	an optional character vector of labels for the variables in the pairs plot.
`id`	an optional numeric value, or one-sided formula. If given as a value, it is used as a significance level for an outlier test based on the Mahalanobis distances of the estimated random effects. Groups with random effects distances greater than the 1-value percentile of the appropriate chi-square distribution are identified in the plot using `idLabels`. If given as a one-sided formula, its right hand side must evaluate to a logical, integer, or character vector which is used to identify points in the plot. If missing, no points are identified.
`idLabels`	an optional vector, or one-sided formula. If given as a vector, it is converted to character and used to label the points identified according to `id`. If given as a one-sided formula, its right hand side must evaluate to a vector which is converted to character and used to label the identified points. Default is the innermost grouping factor.
`grid`	an optional logical value indicating whether a grid should be added to plot. Default is `FALSE`.
`...`	optional arguments passed to the Trellis plot function.

Value

a diagnostic Trellis plot.

Author(s)

José Pinheiro and Douglas Bates bates@stat.wisc.edu

Examples

fm1 <- lmList(distance ~ age | Subject, Orthodont)

# scatter plot of coefficients by gender, identifying unusual subjects
pairs(fm1, ~coef(.) | Sex, id = 0.1, adj = -0.5)

# scatter plot of estimated random effects -- "bivariate Gaussian (?)"
pairs(fm1, ~ranef(.))

nlme

Linear and Nonlinear Mixed Effects Models

v3.1-152

GPL (>= 2) | file LICENCE

Authors

José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), Johannes Ranke [ctb] (varConstProp()), R-core [aut, cre]

Initial release

2021-02-03