R: Deprecated functions in package 'robustHD'

robustHD-deprecated {robustHD}

R Documentation

Deprecated functions in package robustHD

Description

These functions are provided for compatibility with older versions only, and may be defunct as soon as the next release.

Usage

## S3 method for class 'seqModel'
fortify(model, data, s = NA, covArgs = list(...), ...)

## S3 method for class 'sparseLTS'
fortify(
  model,
  data,
  s = NA,
  fit = c("reweighted", "raw", "both"),
  covArgs = list(...),
  ...
)

## Default S3 method:
diagnosticPlot(
  object,
  which = c("all", "rqq", "rindex", "rfit", "rdiag"),
  ask = (which == "all"),
  facets = attr(object, "facets"),
  size = c(2, 4),
  id.n = NULL,
  ...
)

Arguments

`model`	the model fit to be converted.
`data`	currently ignored.
`s`	for the `"seqModel"` method, an integer vector giving the steps of the submodels to be converted (the default is to use the optimal submodel). For the `"sparseLTS"` method, an integer vector giving the indices of the models to be converted (the default is to use the optimal model for each of the requested fits).
`covArgs`	a list of arguments to be passed to `covMcd` for computing robust Mahalanobis distances.
`...`	for the `fortify` methods, additional arguments to be passed to `covMcd` can be specified directly instead of via `covArgs`. For the default method of `diagnosticPlot`, additional arguments to be passed down to `geom_point`.
`fit`	a character string specifying which fit to convert. Possible values are `"reweighted"` (the default) to convert the reweighted fit, `"raw"` to convert the raw fit, or `"both"` to convert both fits.
`object`	a data frame containing all necessary information for plotting (as generated by the `fortify` methods).
`which`	a character string indicating which plot to show. Possible values are `"all"` (the default) for all of the following, `"rqq"` for a normal Q-Q plot of the standardized residuals, `"rindex"` for a plot of the standardized residuals versus their index, `"rfit"` for a plot of the standardized residuals versus the fitted values, or `"rdiag"` for a regression diagnostic plot (standardized residuals versus robust Mahalanobis distances of the predictor variables).
`ask`	a logical indicating whether the user should be asked before each plot (see `devAskNewPage`). The default is to ask if all plots are requested and not ask otherwise.
`facets`	a faceting formula to override the default behavior. If supplied, `facet_wrap` or `facet_grid` is called depending on whether the formula is one-sided or two-sided.
`size`	a numeric vector of length two giving the point and label size, respectively.
`id.n`	an integer giving the number of the most extreme observations to be identified by a label. The default is to use the number of identified outliers, which can be different for the different plots.

Details

The fortify methods supplement the fitted values and residuals of a sequence of regression models (such as robust least angle regression models or sparse least trimmed squares regression models) with other useful information for diagnostic plots.

The default method of diagnosticPlot creates the corresponding plot from the data frame returned by fortify.

Value

The fortify methods return data frame containing the columns listed below, as well as additional information stored in the attributes "qqLine" (intercepts and slopes of the respective reference lines to be displayed in residual Q-Q plots), "q" (quantiles of the Mahalanobis distribution used as cutoff points for detecting leverage points), and "facets" (default faceting formula for the diagnostic plots).

step: the steps (for the "seqModel" method) or indices (for the "sparseLTS" method) of the models (only returned if more than one model is requested).
fit: the model fits (only returned if both the reweighted and raw fit are requested in the "sparseLTS" method).
index: the indices of the observations.
fitted: the fitted values.
residual: the standardized residuals.
theoretical: the corresponding theoretical quantiles from the standard normal distribution.
qqd: the absolute distances from a reference line through the first and third sample and theoretical quartiles.
rd: the robust Mahalanobis distances computed via the MCD (see covMcd).
xyd: the pairwise maxima of the absolute values of the standardized residuals and the robust Mahalanobis distances, divided by the respective other outlier detection cutoff point.
weight: the weights indicating regression outliers.
leverage: logicals indicating leverage points (i.e., outliers in the predictor space).
classification: a factor with levels "outlier" (regression outliers) and "good" (data points following the model).

Author(s)

Andreas Alfons

[Package robustHD version 0.7.2 Index]