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require 'distribution/lognormal/gsl'
require 'distribution/lognormal/ruby'
module Distribution
# From Wikipedia:
# In probability theory, a log-normal distribution is a probability
# distribution of a random variable whose logarithm is normally
# distributed. If X is a random variable with a normal distribution, then
# Y = exp(X) has a log-normal distribution; likewise, if Y is
# log-normally distributed, then X = log(Y) is normally distributed. (This
# is true regardless of the base of the logarithmic function: if loga(Y) is
# normally distributed, then so is logb(Y), for any two positive numbers
# a, b ≠ 1.)
#
# This module calculate the pdf, cdf and inverse cdf for Beta Distribution.
#
module LogNormal
extend Distributable
SHORTHAND='lognormal'
create_distribution_methods
##
# :singleton-method: pdf(x,u,s)
# Returns PDF of of Lognormal distribution with parameters u (position) and
# s (deviation)
##
# :singleton-method: cdf(x,u,s)
# Returns the CDF of Lognormal distribution of x with parameters
# u (position) and s(deviation)
##
# :singleton-method: p_value(pr,u,s)
# Return the quantile of the corresponding integral +pr+
# on a lognormal distribution's cdf with parameters z and s
end
end
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