4
vars <- list (substitute (women[["height"]]), substitute (test10z))
5
results <- data.frame ('Object'=rep (NA, length (vars)))
6
for (i in 1:length (vars)) {
7
results[i, 'Object'] <- rk.get.description (vars[[i]], is.substitute=TRUE)
8
var <- eval (vars[[i]], envir=globalenv()) # fetch the real object
10
# we wrap each single call in a "try" statement to always continue on errors.
11
results[i, 'mean'] <- try (mean (var, trim = 0.00, na.rm=TRUE))
12
results[i, 'median'] <- try (median (var, na.rm=TRUE))
14
range <- try (range (var, na.rm=TRUE))
15
results[i, 'min'] <- range[1]
16
results[i, 'max'] <- range[2]
18
results[i, 'standard deviation'] <- try (sd (var, na.rm=TRUE))
19
results[i, 'sum'] <- try (sum (var, na.rm=TRUE))
20
results[i, 'product'] <- try (prod (var, na.rm=TRUE))
21
results[i, 'Median Absolute Deviation'] <- try (mad (var, constant = 1.4628, na.rm=TRUE))
22
results[i, 'length of sample'] <- length (var)
23
results[i, 'number of NAs'] <- sum (is.na(var))
26
rk.header ("Descriptive statistics", parameters=list (
28
"Median Absolute Deviation",
29
paste ("constant:", 1.4628, "average")))
33
.rk.rerun.plugin.link(plugin="rkward::descriptive", settings="constMad.real=1.4628\nlength.state=1\nmad.state=1\nmad_type.string=average\nmean.state=1\nmedian.state=1\nprod.state=1\nrange.state=1\nsd.state=1\nsum.state=1\ntrim.real=0.00\nx.available=women[[\\\"height\\\"]]\\ntest10z", label="Run again")