Pick Subsets from a Vector

Description

Provides a Tk dialog or a text-based menu for interactive selection of one or more subsets from a vector.

Usage

pickFrom(vec, nsets = 1, return.indices = FALSE,
                 setlabels = NULL, edit.setlabels = TRUE,
                 subset = TRUE,
                 warningText = "one or more selections empty",
                 title = "Subset picker",
                 items.label = "Pick from",
                 labels.prompt = "Your label for this set",
                 list.height = 20,
                 items.scrollbar = TRUE,
                 preserve.order = TRUE,
                 graphics = TRUE,
                 listFont = "Courier 12",
                 labelFont = "Helvetica 11",
                 windowPos = "+150+30")

Arguments

Details

If graphics = TRUE and the tcltk package is operational, a Tk dialog is used, otherwise a text menu.

If return.indices is used together with subset, the indices returned relate to vec, not to vec[subset].

Value

EITHER (in the case of a text menu or if the dialog is ended with "OK") a list, with nsets components. Each component is a selected sub-vector, or a numeric vector of indices for a selected sub-vector (if return.indices is TRUE). The component names are as specified in setlabels, or as specified interactively.

OR (if the dialog is ended either "Cancel" or the close-window control button is used) NULL.

Author(s)

David Firth, with contributions from Heather Turner

Examples

## These examples cannot be run by example() but should be OK when pasted
## into an interactive R session
## Not run: 
pickFrom(c("apple", "banana", "plum", "grapefruit"), nsets = 2,
  preserve.order = FALSE,
  setlabels = c("Fruits I like", "Fruits I tolerate"))

## End(Not run)
## Not run: 
## Type selections as e.g. 1:2, 4
pickFrom(c("apple", "banana", "plum", "grapefruit"), nsets = 2,
  preserve.order = FALSE,
  setlabels = c("Fruits I like", "Fruits I tolerate"),
  graphics = FALSE)

## End(Not run)

Convert a Character Vector to Tcl Format

Description

Converts a character vector into a brace-delimited Tcl list

Usage

R.to.Tcl(character.vector)

Arguments

Value

A character vector of length 1

Author(s)

David Firth, d.firth@warwick.ac.uk

See Also

Tcl.to.R

Examples

R.to.Tcl(c("apple","banana"))

Relative Importance of Predictors in a Regression Model

Description

Produces a summary of the relative importance of two predictors or two sets of predictors in a fitted model object.

Usage

relimp(object, set1=NULL,  set2=NULL, label1="set1", label2="set2", 
          subset=TRUE, 
          response.cat=NULL, ...)
## S3 method for class 'relimp'
print(x, digits=3, ...)

Arguments

Details

If set1 and set2 both have length 1, relative importance is measured by the ratio of the two standardized coefficients. Equivalently this is the ratio of the standard deviations of the two contributions to the linear predictor, and this provides the generalization to comparing two sets rather than just a pair of predictors.

The computed ratio is the square root of the variance-ratio quantity denoted as ‘omega’ in Silber, J H, Rosenbaum, P R and Ross, R N (1995). Estimated standard errors are calculated by the delta method, as described in that paper for example.

If set1 and set2 are unspecified, and if the tcltk package has been loaded, a dialog box is provided (by a call to pickFrom) for the choice of set1 and set2 from the available model coefficients.

Value

An object of class relimp, with at least the following components:

If dispersion was supplied as an argument, its value is stored as the dispersion component of the resultant object.

Author(s)

David Firth d.firth@warwick.ac.uk

References

Silber, J. H., Rosenbaum, P. R. and Ross, R N (1995) Comparing the Contributions of Groups of Predictors: Which Outcomes Vary with Hospital Rather than Patient Characteristics? JASA 90, 7–18.

See Also

relrelimp

Examples

set.seed(182)  ## an arbitrary number, just for reproducibility
x <- rnorm(100)
z <- rnorm(100)
w <- rnorm(100)
y <- 3 + (2 * x) + z + w + rnorm(100)
test <- lm(y ~ x + z + w)
print(test)
relimp(test, 2, 3)    #  compares effects of x and z
relimp(test, 2, 3:4)  #  compares effect of x with that of (z,w) combined
##
##  Data on housing and satisfaction, from Venables and Ripley
##  -- multinomial logit model
library(MASS)
library(nnet)
data(housing)
house.mult <- multinom(Sat ~ Infl + Type + Cont, weights = Freq,
  data = housing)
relimp(house.mult, set1 = 2:3, set2 = 7, response.cat = "High")

Comparison of Relative Importances in a Multinomial Logit Model

Description

Produces a summary of the relative importance of two predictors or two sets of predictors in a fitted multinom model object, and compares relative importances across two of the fitted logit models.

Usage

relrelimp(object, set1=NULL, set2=NULL, label1="set1", label2="set2", 
          subset=TRUE, 
          response.cat1=NULL, response.cat2=NULL)

Arguments

Details

Computes a relative importance summary as described in relimp, for each of the two regressions specified by response.cat1 and response.cat2 (relative to the same reference category); and computes the difference of those two relative importance summaries, along with an estimated standard error for that difference.

Value

An object of class relrelimp, with at least the following components:

Author(s)

David Firth, d.firth@warwick.ac.uk

See Also

relimp

Examples

##  Data on housing and satisfaction, from Venables and Ripley
library(MASS)
library(nnet)
data(housing)
house.mult <- multinom(Sat ~ Infl + Type + Cont, weights = Freq,
  data = housing)
relrelimp(house.mult, set1 = 2:3, set2 = 7, 
                      label1 = "Influence", label2 = "Contact",
                      response.cat1 = "Medium", response.cat2 = "High")
## Computes the relative contribution of Influence and Contact in 
## each of the two logistic regressions (Med/Low and High/Low), and
## compares those two relative-contribution measures.

Display a Data Frame in a Tk Text Widget

Description

Displays the contents of a data frame in a modeless Tk text window, for inspection. Objects not of class data.frame, for example objects of class table, or matrix, are coerced using as.data.frame prior to display.

Usage

showData(dataframe, 
       colname.bgcolor = "grey50", 
       rowname.bgcolor = "grey50", 
       body.bgcolor = "white", 
       colname.textcolor = "white", 
       rowname.textcolor = "white", 
       body.textcolor = "black",
       font = "Courier 12", 
       maxheight = 30, 
       maxwidth = 80, 
       title = NULL,
       rowname.bar = "left",
       colname.bar = "top",
       rownumbers = FALSE, 
       placement = "-20-40",
       suppress.X11.warnings = TRUE)

Arguments

Value

Invisibly returns the Tk window containing the displayed data frame.

Note

An error results if the printed representation of dataframe exceeds the maximum allowed width of 10000 characters; see options.

Text can be copied from the Tk window to the system clipboard, using <Control-C> or via a right-click pop-up menu.

On some systems the window may take a few seconds to appear if the data frame is very large.

Author(s)

David Firth, d.firth@warwick.ac.uk; with Rcmdr-specific features contributed by John Fox

Examples

## This cannot be run by example() but should be OK when pasted
## into an interactive R session
## Not run: 
data(mtcars)
showData(mtcars)
## End(Not run)

Convert a Tcl List to R Character Vector

Description

Converts a brace-delimited list from Tcl into a character vector

Usage

Tcl.to.R(tcl.list)

Arguments

Value

a character vector

Author(s)

David Firth, d.firth@warwick.ac.uk

See Also

R.to.Tcl

Examples

Tcl.to.R("{apple} {banana} {pear}")