dist_data_cdf-methods: The data cumulative distribution function

Description Usage Arguments Note Examples

Description

This is generic function for distribution objects. This function calculates the data or empirical cdf.

The functions dist_data_all_cdf and dist_all_cdf are only available for discrete distributions. Their main purpose is to optimise the bootstrap procedure, where generating a vector xmin:xmax is very quick. Also, when bootstrapping very large values can be generated.

Usage

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dist_all_cdf(m, lower_tail = TRUE, xmax = 1e+05)

dist_data_cdf(m, lower_tail = TRUE, xmax = 1e+05)

dist_data_all_cdf(m, lower_tail = TRUE, xmax = 1e+05)

## S4 method for signature 'discrete_distribution'
dist_data_cdf(m, lower_tail = TRUE,
  xmax = 1e+05)

## S4 method for signature 'discrete_distribution'
dist_data_all_cdf(m, lower_tail = TRUE,
  xmax = 1e+05)

## S4 method for signature 'ctn_distribution'
dist_data_cdf(m, lower_tail = TRUE,
  xmax = 1e+05)

Arguments

m

a distribution object.

lower_tail

logical; if TRUE (default), probabilities are P[X ≤ x], otherwise, P[X > x].

xmax

default 1e5. The maximum x value calculated when working out the CDF.

Note

This method does *not* alter the internal state of the distribution objects.

Examples

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##########################################
#Load data and create distribution object#
##########################################
data(moby_sample)
m = displ$new(moby_sample)
m$setXmin(7);m$setPars(2)

##########################################
# The data cdf                           #
##########################################
dist_data_cdf(m)

csgillespie/poweRlaw documentation built on July 26, 2018, 9:54 p.m.