W.numSummary {RcmdrPlugin.TeachStat}

Summary statistics for weighted variables

Description

W.numSummary gives the main statistical summary for weighted variables (mean, standard deviation, coefficient of variation, skewness, kurtosis and quantiles). It also allows the partition of the data by a factor variable.

Usage

W.numSummary(data, 
             statistics = c("mean", "sd", "se(mean)", "IQR",
             "quantiles", "cv", "skewness", "kurtosis"),type = c("2", "1", "3"),
             quantiles = c(0, 0.25, 0.5, 0.75, 1),groups = NULL, weights)

Arguments

data

data.frame with the variables.

statistics

any of "mean", "sd", "se(mean)", "quantiles", "cv" (coefficient of variation - sd/mean), "skewness" or "kurtosis"; defaulting to c("mean", "sd", "quantiles", "IQR").

type

definition to use in computing skewness and kurtosis; see the skewness and kurtosis functions in the e1071 package. The default is "2".

quantiles

quantiles to report; by default is c(0, 0.25, 0.5, 0.75, 1).

groups

optional variable, typically a factor, to be used to partition the data. By default is NULL.

weights

numeric vector of weights. Zero values are allowed.

Details

W.numSummary performs a descriptive analysis of quantitative variables weighted (or not) by a numeric variable which determines the importance of each subject in the data frame. Optionally it allows the partition of the data by a factor variable (groups).

Note that, unlike the numSummary function, the sample standard deviation is calculated instead of the sample standard quasideviation.

Value

An object with class "numSummary".

See Also

numSummary, skewness, kurtosis.

Examples

data(cars93)

# no weighted
W.numSummary(data=cars93[,c("CityMPG")], statistics =c("mean", "sd", "IQR", "quantiles"),
   quantiles = c(0,0.25,0.5,0.75,1), weights=NULL, groups=NULL)
# weighted
W.numSummary(data=cars93[,c("CityMPG")], statistics =c("mean", "sd", "IQR", "quantiles"),
   quantiles = c(0,0.25,0.5,0.75,1), weights=cars93$FuelCapacity, groups=NULL)
# no weighted
W.numSummary(data=cars93[,c("CityMPG")], statistics =c("mean", "sd", "IQR", "quantiles"),
   quantiles = c(0,0.25,0.5,0.75,1), weights=NULL, groups=cars93$Manual)
# weighted
bb <- W.numSummary(data=cars93[,c("CityMPG")], statistics =c("mean", "sd", "IQR", "quantiles"),
   quantiles = c(0,0.25,0.5,0.75,1), weights=cars93$FuelCapacity, groups=cars93$Manual)

bb
str(bb)
class(bb)