A function to classify continuous variables.

mf_get_breaks(x, nbreaks, breaks, k = 1, central = FALSE, ...)

## Arguments

x a vector of numeric values a number of classes a classification method; one of "fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust", "bclust", "fisher", "jenks", "dpih", "q6", "geom", "arith", "em" or "msd" (see Details). number of standard deviation for "msd" method (see Details) creation of a central class for "msd" method (see Details) further arguments of classIntervals

## Value

A numeric vector of breaks

## Details

"fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust", "bclust", "fisher", "jenks" and "dpih" are classIntervals methods. You may need to pass additional arguments for some of them.

Jenks ("jenks" method) and Fisher ("fisher" method) algorithms are based on the same principle and give quite similar results but Fisher is much faster.

The "q6" method uses the following quantile probabilities: 0, 0.05, 0.275, 0.5, 0.725, 0.95, 1.

The "geom" method is based on a geometric progression along the variable values.

The "arith" method is based on an arithmetic progression along the variable values.

The "em" method is based on nested averages computation.

The "msd" method is based on the mean and the standard deviation of a numeric vector. The nbreaks parameter is not relevant, use k and central instead. k indicates the extent of each class in share of standard deviation. If central=TRUE then the mean value is the center of a class else the mean is a break value.

## Note

This function is mainly a wrapper of classIntervals + "arith", "em", "q6", "geom" and "msd" methods.

mtq <- mf_get_mtq()
#> [1] 11929.0 13667.0 14786.0 15685.5 16860.0 18622.0 21761.0