Mode

0th

Percentile

Mode, Most Frequent Value(s)

Calculate the mode, the most frequent value, of a variable x. This makes mostly sense for qualitative data, at most for x being an integer vector.

Keywords
univar
Usage
Mode(x, na.rm = FALSE)
Arguments
x

a (non-empty) numeric vector of data values.

na.rm

logical. Should missing values be removed? Defaults to FALSE.

Value

Returns the most frequent value. If there are more than one, all of them will be returned in a vector.

Note

Consider using density(x)$x[which.max(density(x)$y)] for quantitative data or alternatively use hist(). Another interesting idea:

peak <- optimize(function(x, model) predict(model, data.frame(x = x)),
                 c(min(x), max(x)),
                 maximum = TRUE,
                 model = y.loess)

points(peak$maximum, peak$objective, pch=FILLED.CIRCLE <- 19)

References

https://stackoverflow.com/questions/55212746/rcpp-fast-statistical-mode-function-with-vector-input-of-any-type/ https://stackoverflow.com/a/55213471/8416610

See Also

mean, median

Aliases
  • Mode
Examples
# NOT RUN {
# normal mode
Mode(c(0:5, 5))

Mode(5)
Mode(NA)
Mode(c(NA, NA))
Mode(c(NA, 0:5))
Mode(c(NA, 0:5), na.rm=TRUE)
Mode(c(NA, 0:5, 5), na.rm=TRUE)

# returns all encountered modes, if several exist
Mode(c(0:5, 4, 5, 6))


data(d.pizza)
Mode(d.pizza$driver)

# use sapply for evaluating data.frames (resp. apply for matrices)
sapply(d.pizza[,c("driver","temperature","date")], Mode, na.rm=TRUE)
# }
Documentation reproduced from package DescTools, version 0.99.32, License: GPL (>= 2)

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