mfv {fdth}

Most frequent value (statistical mode) of frequency distribution table (numerical and categorical variable)

Description

S3 methods for the most frequent value (statistical mode) of a fdt.
Useful to estimate the most frequent value or statistical mode. May also be used, by using a previous fdt, when the original data vector is not known.

Usage

## S3 generic
mfv(x, ...)

## S3 methods: numerical and categorical 
## Default S3 method:
mfv(x, ...)

## S3 method for class 'fdt'
mfv(x, ...)

## S3 method for class 'fdt.multiple'
mfv(x, ...)

## S3 method for class 'fdt_cat'
mfv(x, ...)

## S3 method for class 'fdt_cat.multiple'
mfv(x, ...)

Arguments

x

a fdt or fdt_cat (simple or multiple) object.

...

required to be generic.

Details

mfv.fdt and mfv.fdt_cat calculates the most frequent value (mfv) based on a known formula. mfv.fdt.multiple and mfv.fdt_cat.multiplecall respectively mfv.fdt or mfv.fdt_catfor each variable, that is, each column of the data.frame.

Value

mfv.fdt returns a numeric vector containing the mfv value of the fdt. mean.fdt.multiple returns a list, where each element is a numeric vector containing the mean value of the fdt for each variable. mfv.fdt_cat returns a character vector containing the mfv value of the fdt_cat. mean.fdt_cat.multiple returns a list, where each element is a character vector containing the mfv value of the fdt_cat for each variable.

Author(s)

Faria, J. C.
Allaman, I. B
Jelihovschi, E. G.

See Also

mean.fdt, median.fdt.

Examples

# Numerical
mdf <- data.frame(x=rnorm(1e2, 
                          20, 
                          2),
                  y=rnorm(1e2, 
                          30,
                          3),
                  z=rnorm(1e2,
                          40,
                          4))

head(mdf)

mfv(mdf$x)   # From vector x
mfv(mdf$y)   # From vector y
mfv(mdf$z)   # From vector z

(ft <- fdt(mdf))

mfv(ft)      # From agruped data in a fdt object


## Categorical
mdf <- data.frame(c1=sample(letters[1:5],
                            1e3,
                            rep=TRUE),
                  c2=sample(letters[6:10],
                            1e3,
                            rep=TRUE),
                  c3=sample(letters[11:21],
                            1e3,
                            rep=TRUE),
                  stringsAsFactors=TRUE)
head(mdf)

mfv(mdf$c1)   # From vector c1
mfv(mdf$c2)   # From vector c2
mfv(mdf$c3)   # From vector c3

(ft <- fdt_cat(mdf))

mfv(ft)      # From agruped data in a fdt object