From real data to distributionH.
data2hist(
data,
algo = "histogram",
type = "combined",
qua = 10,
breaks = numeric(0),
epsilon = 0.01
)
a set of numeric values.
(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.
(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.
a positive integer to provide if algo="FixedQuantiles"
is chosen. Default=10.
a vector of values to provide if algo="ManualBreaks"
is chosen.
a number between 0 and 1 to provide if algo="PolyLine"
is chosen. Default=0.01.
A distributionH
object, i.e. a distribution.
histogram
function
# NOT RUN {
data=rnorm(n = 1000,mean = 2,sd = 3)
mydist=data2hist(data)
plot(mydist)
# }
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