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check_logical()
Checks a variable is a single logical value (and optionally not missing)
check_numeric()
Checks a variable is a single number (and optionally, in a range and not NA)
estimate_mixture_of_two_normals()
Estimate the parameters of a mixture of two normal distributions
logistic()
logistic(x) = 1 / (1 + exp(-x)), a wrapper for stats::plogis()
logit()
logit(p) = log(p / (1 - p)), a wrapper for stats::qlogis()
plot_posterior()
Plots the marginal posteriors of each parameter in a stanfit object
posterior_intervals()
Calculates central probability intervals for each parameter for each stanfit object
posterior_mass_in_range()
Calculates the amount of probability (mass) a parameter has in a range
posterior_means() posterior_medians()
Calculates the mean or median for each parameter for each stanfit object
rename_params_cmdstanfile_to_rstan()
Renames tensor parameters from cmdstandr to rstan format
simulate_mixture_of_two_normals()
Simulate (randomly draw) numbers from a mixture of two normal distributions.
stan_example_regression
Example data from Stan analysis of simple linear normal regression
stanfit_to_matrix() stanfit_to_dt()
Converts a stanfit object to a matrix or data.table
uniroot.vectorized()
Vectorised uniroot

R6 Interface Classes

Class definitions for an extension to R6 classes including interfaces

R6.class()
Class: R6.class
R6.interface()
R6.interface
R6.interface.implements()
R6.interface.implements

R6 Distribution Classes

Constructor functions for R6 distribution classes

Mastiff-Distributions
Distribution Classes
is.distribution()
is.distribution
distribution.mixture()
distribution.mixture

Discrete Distributions

distribution.binomial()
distribution.binomial
distribution.negative_binomial()
distribution.negative_binomial
distribution.point_mass()
distribution.point_mass
distribution.poisson()
distribution.poisson

Continuous Distributions

distribution.exponential()
distribution.exponential
distribution.gamma()
distribution.gamma
distribution.lognormal()
distribution.lognormal
distribution.normal()
distribution.normal
distribution.uniform()
distribution.uniform

Class Definitions

distribution.abstract.class
Class: distribution.abstract.class
distribution.continuous.class
Class: distribution.continuous.class
distribution.continuous.exponential.class
Class: distribution.continuous.exponential.class
distribution.continuous.gamma.class
Class: distribution.continuous.gamma.class
distribution.continuous.lognormal.class
Class: distribution.continuous.lognormal.class
distribution.continuous.normal.class
Class: distribution.continuous.normal.class
distribution.continuous.uniform.class
Class: distribution.continuous.uniform.class
distribution.discrete.binomial.class
Class: distribution.discrete.binomial.class
distribution.discrete.class
Class: distribution.discrete.class
distribution.discrete.negative_binomial.class
Class: distribution.discrete.negative_binomial.class
distribution.discrete.point_mass.class
Class: distribution.discrete.point_mass.class
distribution.discrete.poisson.class
Class: distribution.discrete.poisson.class
distribution.mixture.class
Class: distribution.mixture.class