Quantile of frequency distribution table (numerical variable)
S3 methods for the quantile of a fdt.
Useful to estimate the quantile (when the real data vector is not known) from a previous fdt.
## S3 methods: numerical
## S3 method for class 'fdt'
quantile(x,
...,
i=1,
probs=seq(0, 1, 0.25))
## S3 method for class 'fdt.multiple'
quantile(x, ...)x |
A |
i |
A vector of length up to the length of probs |
probs |
vector of probabilities defining the quantiles |
... |
Potencial further arguments (required by generic). |
quantile.fdt calculates the quantiles based on a known formula for
class intervals. quantile.fdt.multiple calls quantile.fdt
for each variable, that is, each column of the data.frame.
quantile.fdt returns a numeric vector containing the value(s) of the
quantile(s) from fdt.
quantile.fdt.multiple returns a list, where each element is a numeric vector
containing the quantile(s) of the fdt for each variable.
José Cláudio Faria
Enio G. Jelihovschi
Ivan B. Allaman
median.fdt, var.fdt.
mdf <- data.frame(x=rnorm(1e2,
20,
2),
y=rnorm(1e2,
30,
3),
z=rnorm(1e2,
40,
4))
head(mdf)
apply(mdf,
2,
quantile)[2,] # The first quartile
quantile(fdt(mdf)) # Notice that the i default is 1 (the first quartile)
## A small (but didactic) joke
quantile(fdt(mdf),
i=2,
probs=seq(0,
1,
0.25)) # The quartile 2
quantile(fdt(mdf),
i=5,
probs=seq(0,
1,
0.10)) # The decile 5
quantile(fdt(mdf),
i=50,
probs=seq(0,
1,
0.01)) # The percentile 50
quantile(fdt(mdf),
i=500,
probs=seq(0,
1,
0.001)) # The permile 500
median(fdt(mdf)) # The median (all the results are the same) ;)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.