Descriptive Statistics for a Vector or a Data Frame
Applies descriptive statistics to a vector or a data frame. The function
stats0 is a general function. This function is used for extending
the basic descriptive statistics functions from the base and
stats package. The function prop_miss computes the proportion
of missing data for each variable.
stats0(x, FUN, na.rm=TRUE,...) max0(x, na.rm=TRUE) mean0(x, na.rm=TRUE) min0(x, na.rm=TRUE) quantile0(x, probs=seq(0, 1, 0.25), na.rm=TRUE) sd0(x, na.rm=TRUE) var0(x, na.rm=TRUE) prop_miss(x)
x |
Vector or a data frame |
FUN |
Function which is applied to |
na.rm |
Logical indicating whether missing data should be removed |
probs |
Probabilities |
... |
Further arguments to be passed |
A vector or a matrix
#############################################################################
# EXAMPLE 1: Descriptive statistics toy datasets
#############################################################################
#--- simulate vector y and data frame dat
set.seed(765)
N <- 25 # number of observations
y <- stats::rnorm(N)
V <- 4 # number of variables
dat <- matrix( stats::rnorm( N*V ), ncol=V )
colnames(dat) <- paste0("V",1:V)
#-- standard deviation
apply( dat, 2, stats::sd )
sd0( dat )
#-- mean
apply( dat, 2, base::mean )
mean0( dat )
#-- quantile
apply( dat, 2, stats::quantile )
quantile0( dat )
#-- minimum and maximum
min0(dat)
max0(dat)
#*** apply functions to missing data
dat1 <- dat
dat1[ cbind( c(2,5),2) ] <- NA
#-- proportion of missing data
prop_miss( dat1 )
#-- MAD statistic
stats0( dat, FUN=stats::mad )
#-- SD
sd0(y)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.