Table 1.

Functions present in the package modules.

Module	Function	Brief description
Present	drand	Returns a random number with homogeneous distribution between 0 and 1
in	exp_rvs	Returns a random number with exponential distribution between 0 and infinity
both	gauss_rvs	Returns a random number with gaussian distribution between minus infinity and infinity
modules	exg_rvs	Returns a random number with ex-Gaussian distribution between minus infinity and infinity
	gauss_pdf	Evaluates the gaussian distribution at a given point
	gauss_cdf	Evaluates the gaussian cumulative distribution at a given point
	exg_pdf	Evaluates the ex-Gaussian distribution at a given point
	exg_cdf	Evaluates the ex-Gaussian cumulative distribution at a given point
	exg_lamb_pdf	Evaluates the ex-Gaussian distribution parameterized in terms of its asymmetry at a given point
	exg_lamb_cdf	Evaluates the ex-Gaussian cumulative distribution parameterized in terms of its asymmetry at a given point
	pars_to_stats	Given the parameters μ, σ and τ, evaluates the corresponding statistics M, S, and K
	stats_to_pars	Given the statistics M, S and K, evaluates the corresponding parameters μ, σ and τ
	histogram	Given a set of observations, produces an histogram
	stats	Given a set of observations, returns the statistics M, S, and K
	stats_his	Given a set of observations, presented as a histogram, returns the statistics M, S, and K
	correlation	Given a set of points, returns the linear correlation coefficient for the points
	minsquare	Given a set of points, fits a polynomial to the data using the least square method
	exgLKHD	Evaluates the likelihood and its gradient in the parameter space for a dataset in a given point of the parameter space
	maxLKHD	Evaluates the parameters μ, σ and τ that maximize the likelihood for a given dataset
	exgSQR	Evaluates the sum of squared differences and its gradient in the parameter space for an histogram in a given point of the parameter space
	minSQR	Evaluates the parameters μ, σ and τ that minimize the sum of squared differences for a given histogram
Only	int_points_gauss	Creates a point partition of an interval for evaluating a
in		gaussian integral
uts	intsum	Evaluates the gaussian integral for a function calculated at the points in a gaussian partition
Only	zero	Finds the zero of an equation
in	ANOVA	Performs an ANOVA test
pyexg	integral	Evaluates an integral

In python type help(FUNC) (where FUNC should be the name of a given function), in order to obtain the list of arguments that each function should receive and in which order.