Reference

All functions
Math(<dist>)	Math group generic for distribution objects.
affine_transform()	Affine transformation of a normal or multivariate normal distribution.
beta_dist()	Construct a beta distribution object.
cdf()	Generic method for obtaining the cdf of an object.
cdf(<beta_dist>)	Cumulative distribution function for a beta distribution.
cdf(<chi_squared>)	Method for obtaining the cdf of a chi_squared object.
cdf(<edist>)	CDF for expression distributions.
cdf(<empirical_dist>)	Method for obtaining the cdf of empirical_dist object x.
cdf(<exponential>)	Method to obtain the cdf of an exponential object.
cdf(<gamma_dist>)	Method for obtaining the cdf of a gamma_dist object.
cdf(<lognormal>)	Cumulative distribution function for a log-normal distribution.
cdf(<mixture>)	Cumulative distribution function for a mixture distribution.
cdf(<mvn>)	Method for obtaining the CDF of a mvn object.
cdf(<normal>)	Method for obtaining the cdf of an normal object.
cdf(<poisson_dist>)	Cumulative distribution function for a Poisson distribution.
cdf(<uniform_dist>)	Cumulative distribution function for a uniform distribution.
cdf(<weibull_dist>)	Cumulative distribution function for a Weibull distribution.
chi_squared()	Construct a chi-squared distribution object.
clt()	Central Limit Theorem Limiting Distribution
conditional()	Generic method for obtaining the conditional distribution of a distribution object x given condition P.
conditional(<dist>)	Method for obtaining the condition distribution, x | P(x), of dist object x.
conditional(<edist>)	Conditional distribution for expression distributions.
conditional(<empirical_dist>)	Method for obtaining the condition distribution, x | P(x), of empirical_dist object x.
conditional(<mixture>)	Conditional distribution of a mixture.
conditional(<mvn>)	Conditional distribution for multivariate normal.
countable_set	Countable Set
delta_clt()	Delta Method CLT Limiting Distribution
density(<beta_dist>)	Probability density function for a beta distribution.
density(<chi_squared>)	Method for obtaining the density (pdf) of a chi_squared object.
density(<edist>)	Density for expression distributions.
density(<empirical_dist>)	Method for obtaining the pdf of a empirical_dist object.
density(<exponential>)	Method to obtain the pdf of an exponential object.
density(<gamma_dist>)	Method for obtaining the density (pdf) of a gamma_dist object.
density(<lognormal>)	Probability density function for a log-normal distribution.
density(<mixture>)	Probability density function for a mixture distribution.
density(<mvn>)	Function generator for obtaining the pdf of an mvn object (multivariate normal).
density(<normal>)	Method for obtaining the pdf of an normal object.
density(<poisson_dist>)	Probability mass function for a Poisson distribution.
density(<uniform_dist>)	Probability density function for a uniform distribution.
density(<weibull_dist>)	Probability density function for a Weibull distribution.
dim(<beta_dist>)	Dimension of a beta distribution (always 1).
dim(<chi_squared>)	Retrieve the dimension of a chi_squared object.
dim(<countable_set>)	Get the dimension of a countable set.
dim(<empirical_dist>)	Method for obtaining the dimension of a empirical_dist object.
dim(<exponential>)	Method to obtain the dimension of an exponential object.
dim(<finite_set>)	Return the dimension of the finite set.
dim(<gamma_dist>)	Retrieve the dimension of a gamma_dist object.
dim(<interval>)	Return the dimension of the interval.
dim(<lognormal>)	Dimension of a log-normal distribution (always 1).
dim(<mixture>)	Dimension of a mixture distribution.
dim(<mvn>)	Method for obtaining the dimension of an mvn object.
dim(<normal>)	Method for obtaining the dimension of a normal object.
dim(<poisson_dist>)	Dimension of a Poisson distribution (always 1).
dim(<uniform_dist>)	Dimension of a uniform distribution (always 1).
dim(<weibull_dist>)	Dimension of a Weibull distribution (always 1).
Summary(<dist>)	Summary group generic for distribution objects.
`-`(<dist>)	Method for negation or subtraction of dist objects.
edist()	Takes an expression e and a list vars and returns a lazy edist (expression distribution object), that is a subclass of dist that can be used in place of a dist object.
empirical_dist()	Construct empirical distribution object.
expectation()	Generic method for obtaining the expectation of f with respect to x.
expectation(<dist>)	Expectation of a Function Applied to a dist Object
expectation(<empirical_dist>)	Method for obtaining the expectation of empirical_dist object x under function g.
expectation(<poisson_dist>)	Exact expectation for a Poisson distribution.
expectation(<univariate_dist>)	Method for obtaining the expectation of f with respect to a univariate_dist object x.
expectation_data()	Function used for computing expectations given data (e.g., from an MC simulation or bootstrap). it expects a matrix, or something that can be coerced to a matrix (e.g., a data frame). it also expects a function g to apply to each row of the data, and returns the expectation of g under the empirical distribution of the data. it also returns a confidence interval for the expectation, and the number of samples used to compute the expectation.
exponential()	Construct exponential distribution object.
finite_set	Finite set
format(<beta_dist>)	Format a beta_dist object as a character string.
format(<chi_squared>)	Format a chi_squared object as a character string.
format(<edist>)	Format method for edist objects.
format(<empirical_dist>)	Format method for empirical_dist objects.
format(<exponential>)	Format method for exponential objects.
format(<gamma_dist>)	Format a gamma_dist object as a character string.
format(<lognormal>)	Format a lognormal object as a character string.
format(<mixture>)	Format a mixture object as a character string.
format(<mvn>)	Format method for mvn objects.
format(<normal>)	Format method for normal objects.
format(<poisson_dist>)	Format a poisson_dist object as a character string.
format(<realized_dist>)	Format a realized_dist object as a character string.
format(<uniform_dist>)	Format a uniform_dist object as a character string.
format(<weibull_dist>)	Format a weibull_dist object as a character string.
gamma_dist()	Construct a gamma distribution object.
has()	Support
has(<countable_set>)	Check membership in a countable set.
has(<finite_set>)	Determine if a value is contained in the finite set.
has(<interval>)	Determine if a value is contained in the interval.
hazard()	Generic method for obtaining the hazard function of an object.
hazard(<chi_squared>)	Method for obtaining the hazard function of a chi_squared object.
hazard(<exponential>)	Method to obtain the hazard function of an exponential object.
hazard(<gamma_dist>)	Method for obtaining the hazard function of a gamma_dist object.
hazard(<lognormal>)	Hazard function for a log-normal distribution.
hazard(<weibull_dist>)	Hazard function for a Weibull distribution.
infimum()	Get the infimum of the support.
infimum(<countable_set>)	Get the infimum of a countable set.
infimum(<finite_set>)	Return the infimum of the finite set.
infimum(<interval>)	Return the (vector of) infimum of the interval.
interval	Interval
inv_cdf()	Generic method for obtaining the quantile (inverse cdf) of an object.
inv_cdf(<beta_dist>)	Inverse CDF (quantile function) for a beta distribution.
inv_cdf(<chi_squared>)	Method for obtaining the inverse cdf (quantile function) of a chi_squared object.
inv_cdf(<edist>)	Inverse CDF (quantile function) for expression distributions.
inv_cdf(<empirical_dist>)	Method for obtaining the inverse CDF (quantile function) of a univariate empirical_dist object.
inv_cdf(<exponential>)	Method to obtain the inverse cdf of an exponential object.
inv_cdf(<gamma_dist>)	Method for obtaining the inverse cdf (quantile function) of a gamma_dist object.
inv_cdf(<lognormal>)	Inverse CDF (quantile function) for a log-normal distribution.
inv_cdf(<normal>)	Method for obtaining the inverse cdf of an normal object.
inv_cdf(<poisson_dist>)	Inverse CDF (quantile function) for a Poisson distribution.
inv_cdf(<uniform_dist>)	Inverse CDF (quantile function) for a uniform distribution.
inv_cdf(<weibull_dist>)	Inverse CDF (quantile function) for a Weibull distribution.
is_beta_dist()	Test whether an object is a beta_dist.
is_chi_squared()	Test whether an object is a chi_squared.
is_dist()	Function to determine whether an object x is a dist object.
is_edist()	Function to determine whether an object x is an edist object.
is_empirical_dist()	Function to determine whether an object x is an empirical_dist object.
is_exponential()	Function to determine whether an object x is an exponential object.
is_gamma_dist()	Test whether an object is a gamma_dist.
is_lognormal()	Test whether an object is a lognormal.
is_mixture()	Test whether an object is a mixture distribution.
is_mvn()	Function to determine whether an object x is an mvn object.
is_normal()	Function to determine whether an object x is an normal object.
is_poisson_dist()	Test whether an object is a poisson_dist.
is_realized_dist()	Test whether an object is a realized_dist.
is_uniform_dist()	Test whether an object is a uniform_dist.
is_weibull_dist()	Test whether an object is a weibull_dist.
lln()	Law of Large Numbers Limiting Distribution
lognormal()	Construct a log-normal distribution object.
marginal()	Generic method for obtaining the marginal distribution of a distribution object x over components indices.
marginal(<empirical_dist>)	Method for obtaining the marginal distribution of empirical_dist object x.
marginal(<mixture>)	Marginal distribution of a mixture.
marginal(<mvn>)	Generic method for obtaining the marginal distribution of an mvn object x over components indices.
mean(<beta_dist>)	Mean of a beta distribution.
mean(<chi_squared>)	Retrieve the mean of a chi_squared object.
mean(<edist>)	Method for obtaining the mean of an edist object.
mean(<empirical_dist>)	Method for obtaining the mean of empirical_dist object x.
mean(<exponential>)	Method to obtain the mean of an exponential object.
mean(<gamma_dist>)	Retrieve the mean of a gamma_dist object.
mean(<lognormal>)	Mean of a log-normal distribution.
mean(<mixture>)	Mean of a mixture distribution.
mean(<mvn>)	Retrieve the mean of a mvn object.
mean(<normal>)	Retrieve the mean of a normal object.
mean(<poisson_dist>)	Mean of a Poisson distribution.
mean(<uniform_dist>)	Mean of a uniform distribution.
mean(<univariate_dist>)	Method for obtaining the mean of univariate_dist object x.
mean(<weibull_dist>)	Mean of a Weibull distribution.
mixture()	Construct a mixture distribution.
mvn()	Construct a multivariate or univariate normal distribution object.
nobs(<empirical_dist>)	Method for obtaining the number of observations used to construct a empirical_dist object.
normal()	Construct univariate normal distribution object.
normal_approx()	Moment-Matching Normal Approximation
nparams()	Generic method for obtaining the number of parameters of distribution-like object x.
nparams(<empirical_dist>)	Method for obtaining the name of a empirical_dist object. Since the empirical distribution is parameter-free, this function returns 0.
nparams(<mixture>)	Number of parameters for a mixture distribution.
obs()	Retrieve the observations used to construct a distribution-like object. This is useful for obtaining the data used to construct an empirical distribution, but it is also useful for, say, retrieving the sample that was used by a fitted object, like an maximum likelihood estimate.
obs(<empirical_dist>)	Method for obtaining the observations used to construct a empirical_dist object.
params()	Generic method for obtaining the parameters of an object.
params(<beta_dist>)	Retrieve the parameters of a beta_dist object.
params(<chi_squared>)	Method for obtaining the parameters of a chi_squared object.
params(<edist>)	Method for obtaining the parameters of an edist object.
params(<empirical_dist>)	empirical_dist objects have no parameters, so this function returns NULL.
params(<exponential>)	Method for obtaining the parameters of an exponential object.
params(<gamma_dist>)	Method for obtaining the parameters of a gamma_dist object.
params(<lognormal>)	Retrieve the parameters of a lognormal object.
params(<mixture>)	Retrieve the parameters of a mixture object.
params(<mvn>)	Method for obtaining the parameters of a mvn object.
params(<normal>)	Method for obtaining the parameters of a normal object.
params(<poisson_dist>)	Retrieve the parameters of a poisson_dist object.
params(<uniform_dist>)	Retrieve the parameters of a uniform_dist object.
params(<weibull_dist>)	Retrieve the parameters of a weibull_dist object.
`+`(<dist>)	Method for adding dist objects, or shifting a distribution by a scalar.
poisson_dist()	Construct a Poisson distribution object.
`^`(<dist>)	Power operator for distribution objects.
print(<beta_dist>)	Print a beta_dist object.
print(<chi_squared>)	Print method for chi_squared objects.
print(<edist>)	Print method for edist objects.
print(<empirical_dist>)	Print method for empirical_dist objects.
print(<exponential>)	Print method for exponential objects.
print(<gamma_dist>)	Print method for gamma_dist objects.
print(<interval>)	Print the interval.
print(<lognormal>)	Print a lognormal object.
print(<mixture>)	Print a mixture object.
print(<mvn>)	Method for printing an mvn object.
print(<normal>)	Print method for normal objects.
print(<poisson_dist>)	Print a poisson_dist object.
print(<realized_dist>)	Print a realized_dist object.
print(<summary_dist>)	Print method for summary_dist objects.
print(<uniform_dist>)	Print a uniform_dist object.
print(<weibull_dist>)	Print a weibull_dist object.
realize()	Materialize any distribution to empirical_dist by sampling.
rmap()	Generic method for applying a map f to distribution object x.
rmap(<dist>)	Method for obtaining g(x)) where x is a dist object.
rmap(<edist>)	Map function over expression distribution.
rmap(<empirical_dist>)	Method for obtaining the empirical distribution of a function of the observations of empirical_dist object x.
rmap(<mvn>)	Computes the distribution of g(x) where x is an mvn object.
sample_mvn_region()	Function for obtaining sample points for an mvn object that is within the p-probability region. That is, it samples from the smallest region of the distribution that contains p probability mass. This is done by first sampling from the entire distribution, then rejecting samples that are not in the probability region (using the statistical distance mahalanobis from mu).
sampler()	Generic method for sampling from distribution-like objects.
sampler(<beta_dist>)	Sampler for a beta distribution.
sampler(<chi_squared>)	Method for sampling from a chi_squared object.
sampler(<default>)	Sampler for non-dist objects (degenerate distributions).
sampler(<edist>)	Method for obtaining the sampler of an edist object.
sampler(<empirical_dist>)	Method for obtaining the sampler for a empirical_dist object.
sampler(<exponential>)	Method to sample from an exponential object.
sampler(<gamma_dist>)	Method for sampling from a gamma_dist object.
sampler(<lognormal>)	Sampler for a log-normal distribution.
sampler(<mixture>)	Sampler for a mixture distribution.
sampler(<mvn>)	Function generator for sampling from a mvn (multivariate normal) object.
sampler(<normal>)	Method for sampling from a normal object.
sampler(<poisson_dist>)	Sampler for a Poisson distribution.
sampler(<uniform_dist>)	Sampler for a uniform distribution.
sampler(<weibull_dist>)	Sampler for a Weibull distribution.
simplify()	Generic method for simplifying distributions.
simplify(<dist>)	Default Method for simplifying a dist object. Just returns the object.
simplify(<edist>)	Method for simplifying an edist object.
`/`(<dist>)	Division of distribution objects.
summary(<dist>)	Method for obtaining a summary of a dist object.
summary_dist()	Method for constructing a summary_dist object.
sup()	Generic method for retrieving the support of a (dist) object x.
sup(<beta_dist>)	Support of a beta distribution.
sup(<chi_squared>)	Support for chi-squared distribution, the positive real numbers (0, Inf).
sup(<edist>)	Support for expression distributions.
sup(<empirical_dist>)	Method for obtaining the support of empirical_dist object x.
sup(<exponential>)	Support for exponential distribution, the positive real numbers, (0, Inf).
sup(<gamma_dist>)	Support for gamma distribution, the positive real numbers (0, Inf).
sup(<lognormal>)	Support of a log-normal distribution.
sup(<mixture>)	Support of a mixture distribution.
sup(<mvn>)	Method for obtaining the support of a mvn object, where the support is defined as values that have non-zero probability density.
sup(<normal>)	Method for obtaining the support of a normal object, where the support is defined as values that have non-zero probability density.
sup(<poisson_dist>)	Support of a Poisson distribution.
sup(<uniform_dist>)	Support of a uniform distribution.
sup(<weibull_dist>)	Support of a Weibull distribution.
supremum()	Get the supremum of the support.
supremum(<countable_set>)	Get the supremum of a countable set.
supremum(<finite_set>)	Return the supremum of the finite set.
supremum(<interval>)	Return the (vector of) supremum of the interval.
surv()	Generic method for obtaining the survival function of an object.
surv(<chi_squared>)	Method for obtaining the survival function of a chi_squared object.
surv(<exponential>)	Method to obtain the cdf of an exponential object.
surv(<gamma_dist>)	Method for obtaining the survival function of a gamma_dist object.
surv(<lognormal>)	Survival function for a log-normal distribution.
surv(<weibull_dist>)	Survival function for a Weibull distribution.
`*`(<dist>)	Multiplication of distribution objects.
uniform_dist()	Construct a uniform distribution object.
vcov(<beta_dist>)	Variance of a beta distribution.
vcov(<chi_squared>)	Retrieve the variance of a chi_squared object.
vcov(<default>)	Variance-covariance for non-dist objects (degenerate distributions).
vcov(<edist>)	Method for obtaining the variance-covariance matrix (or scalar)
vcov(<empirical_dist>)	Method for obtaining the variance of empirical_dist object x.
vcov(<exponential>)	Retrieve the variance of a exponential object.
vcov(<gamma_dist>)	Retrieve the variance of a gamma_dist object.
vcov(<lognormal>)	Variance of a log-normal distribution.
vcov(<mixture>)	Variance of a mixture distribution.
vcov(<mvn>)	Retrieve the variance-covariance matrix of an mvn object.
vcov(<normal>)	Retrieve the variance-covariance matrix (or scalar) of a normal object.
vcov(<poisson_dist>)	Variance of a Poisson distribution.
vcov(<uniform_dist>)	Variance of a uniform distribution.
vcov(<univariate_dist>)	Method for obtaining the variance of univariate_dist object.
vcov(<weibull_dist>)	Variance of a Weibull distribution.
weibull_dist()	Construct a Weibull distribution object.