Produce boxandwhisker plots of continuous or semicontinuous variables, possibly broken down according to conditioning variables and taking into account sample weights.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15  spBwplot(inp, x, cond = NULL, horizontal = TRUE, coef = 1.5,
zeros = TRUE, minRatio = NULL, do.out = FALSE, ...)
panelSpBwplot(x, y, coef = 1.5, zeros = TRUE, ratio, outliers, subscripts,
...)
getBwplotStats(x, weights = NULL, cond = NULL, data, ..., name = "")
prepBwplotStats(x, w, ..., name = "")
## S3 method for class 'data.frame'
prepBwplotStats(x, w, ..., name = "")
## Default S3 method:
prepBwplotStats(x, w, ..., name = "")

inp 
an object of class 
x 
a character vector specifying the columns of data available in the sample and the population (specified in input object 'inp') to be plotted. 
cond 
an optional character vector (of length 1, if used) specifying the conditioning variable. 
horizontal 
a logical indicating whether the boxes should be horizontal or vertical. 
coef 
a numeric value that determines the extension of the whiskers. 
zeros 
a logical indicating whether the variables specified by

minRatio 
a numeric value in (0,1]; if 
do.out 
a logical indicating whether data points that lie beyond the
extremes of the whiskers should be plotted. Note that this is 
... 
further arguments to be passed to

Missing values are ignored for producing box plots and weights are directly
extracted from the input object inp
.
An object of class "trellis"
, as returned by
bwplot
.
Andreas Alfons and Bernhard Meindl
spBwplotStats
, bwplot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23  ## these take some time and are not run automatically
## copy & paste to the R command line
set.seed(1234) # for reproducibility
data(eusilcS) # load sample data
## Not run:
## approx. 20 seconds computation time
inp < specifyInput(data=eusilcS, hhid="db030", hhsize="hsize",
strata="db040", weight="db090")
simPop < simStructure(data=inp, method="direct",
basicHHvars=c("age", "rb090", "hsize", "pl030", "pb220a"))
# multinomial model with random draws
eusilcM < simContinuous(simPop, additional="netIncome",
regModel = ~rb090+hsize+pl030+pb220a+hsize,
upper=200000, equidist=FALSE, nr_cpus=1)
class(eusilcM)
# plot results
spBwplot(eusilcM, x="netIncome", cond=NULL)
spBwplot(eusilcM, x="netIncome", cond="rb090", layout=c(1,2))
## End(Not run)

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