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HistDAWass (version 1.0.4)

data2hist: From real data to distributionH.

Description

From real data to distributionH.

Usage

data2hist(
  data,
  algo = "histogram",
  type = "combined",
  qua = 10,
  breaks = numeric(0),
  epsilon = 0.01
)

Arguments

data

a set of numeric values.

algo

(optional) a string. Default is "histogram", i.e. the function "histogram" defined in the histogram package. If "base" the hist function is used. "FixedQuantiles" computes the histogram using as breaks a fixed number of quantiles. "ManualBreaks" computes a histogram where braks are provided as a vector of values. "PolyLine" computes a histogram using a piecewise linear approximation of the empirical cumulative distribution function using the "Ramer-Douglas-Peucker algorithm", http://en.wikipedia.org/wiki/Ramer-Douglas-Peucker_algorithm. An epsilon parameter is required. The data are scaled in order to have a standard deviation equal to one.

type

(optional) a string. Default is "combined" and generates a histogram having regularly spaced breaks (i.e., equi-width bins) and irregularly spaced ones. The choice is done accordingly with the penalization method described in histogram. "regular" returns equi-width binned histograms, "irregular" returns a histogram without equi-width histograms.

qua

a positive integer to provide if algo="FixedQuantiles" is chosen. Default=10.

breaks

a vector of values to provide if algo="ManualBreaks" is chosen.

epsilon

a number between 0 and 1 to provide if algo="PolyLine" is chosen. Default=0.01.

Value

A distributionH object, i.e. a distribution.

See Also

histogram function

Examples

Run this code
# NOT RUN {
data=rnorm(n = 1000,mean = 2,sd = 3)
mydist=data2hist(data)
plot(mydist)
# }

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