A function to classify continuous variables.
Arguments
- x
a vector of numeric values. NA and Inf values are not used in the classification.
- nbreaks
a number of classes
- breaks
a classification method; one of "fixed", "sd", "equal", "pretty", "quantile", "kmeans", "hclust", "bclust", "fisher", "jenks", "dpih", "q6", "geom", "arith", "em" or "msd" (see Details).
- k
number of standard deviation for "msd" method (see Details)
- central
creation of a central class for "msd" method (see Details)
- ...
further arguments of
classIntervals
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, all values must be strictly greater than zero.
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.
Examples
mtq <- mf_get_mtq()
mf_get_breaks(x = mtq$MED, nbreaks = 6, breaks = "quantile")
#> [1] 11929.0 13667.0 14786.0 15685.5 16860.0 18622.0 21761.0