Namespaces
	details

Classes
struct	WelfordVar

Typedefs
using	dist_value_t = util::dist_value_t

Functions
size_t	padded_length (size_t N)

template<class T >
auto	autocorrelation (const Eigen::MatrixBase< T > &x)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>
dist_value_t	normal_pdf (const XType &x, const MeanType &mean, const SigmaType &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>
dist_value_t	normal_pdf (const Eigen::MatrixBase< XType > &x, const MeanType &mean, const SigmaType &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<SigmaType> >>
dist_value_t	normal_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MeanType > &mean, const SigmaType &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> >>
dist_value_t	normal_pdf (const Eigen::MatrixBase< XType > &x, const MeanType &mean, const Eigen::MatrixBase< SigmaType > &sigma)

template<class XType , class MeanType , class SigmaType >
dist_value_t	normal_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MeanType > &mean, const Eigen::MatrixBase< SigmaType > &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>
dist_value_t	normal_log_pdf (const XType &x, const MeanType &mean, const SigmaType &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>
dist_value_t	normal_log_pdf (const Eigen::MatrixBase< XType > &x, const MeanType &mean, const SigmaType &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<SigmaType> >>
dist_value_t	normal_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MeanType > &mean, const SigmaType &sigma)

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> >>
dist_value_t	normal_log_pdf (const Eigen::MatrixBase< XType > &x, const MeanType &mean, const Eigen::MatrixBase< SigmaType > &sigma)

template<class XType , class MeanType , class SigmaType >
dist_value_t	normal_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MeanType > &mean, const Eigen::MatrixBase< SigmaType > &sigma)

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<LocType> && std::is_arithmetic_v<ScaleType> >>
dist_value_t	cauchy_log_pdf (const XType &x, const LocType &loc, const ScaleType &scale)

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<LocType> && std::is_arithmetic_v<ScaleType> >>
dist_value_t	cauchy_log_pdf (const Eigen::MatrixBase< XType > &x, const LocType &loc, const ScaleType &scale)

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<ScaleType> >>
dist_value_t	cauchy_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< LocType > &loc, const ScaleType &scale)

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<LocType> >>
dist_value_t	cauchy_log_pdf (const Eigen::MatrixBase< XType > &x, const LocType &loc, const Eigen::MatrixBase< ScaleType > &scale)

template<class XType , class LocType , class ScaleType >
dist_value_t	cauchy_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< LocType > &loc, const Eigen::MatrixBase< ScaleType > &scale)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>
dist_value_t	uniform_pdf (const XType &x, const MinType &min, const MaxType &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>
dist_value_t	uniform_pdf (const Eigen::MatrixBase< XType > &x, const MinType &min, const MaxType &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MaxType> >>
dist_value_t	uniform_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MinType > &min, const MaxType &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> >>
dist_value_t	uniform_pdf (const Eigen::MatrixBase< XType > &x, const MinType &min, const Eigen::MatrixBase< MaxType > &max)

template<class XType , class MinType , class MaxType >
dist_value_t	uniform_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MinType > &min, const Eigen::MatrixBase< MaxType > &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>
dist_value_t	uniform_log_pdf (const XType &x, const MinType &min, const MaxType &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>
dist_value_t	uniform_log_pdf (const Eigen::MatrixBase< XType > &x, const MinType &min, const MaxType &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MaxType> >>
dist_value_t	uniform_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MinType > &min, const MaxType &max)

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> >>
dist_value_t	uniform_log_pdf (const Eigen::MatrixBase< XType > &x, const MinType &min, const Eigen::MatrixBase< MaxType > &max)

template<class XType , class MinType , class MaxType >
dist_value_t	uniform_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< MinType > &min, const Eigen::MatrixBase< MaxType > &max)

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<PType> >>
dist_value_t	bernoulli_pdf (const XType &x, const PType &p)

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<PType> >>
dist_value_t	bernoulli_pdf (const Eigen::MatrixBase< XType > &x, const PType &p)

template<class XType , class PType >
dist_value_t	bernoulli_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< PType > &p)

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<PType> >>
dist_value_t	bernoulli_log_pdf (const XType &x, const PType &p)

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<PType> >>
dist_value_t	bernoulli_log_pdf (const Eigen::MatrixBase< XType > &x, const PType &p)

template<class XType , class PType >
dist_value_t	bernoulli_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< PType > &p)

template<class XType , class VType , class NType >
dist_value_t	wishart_log_pdf (const Eigen::MatrixBase< XType > &x, const Eigen::MatrixBase< VType > &v, const NType &n)

template<class T >
auto	ess (const details::vec_cref_t< T > &samples)

template<class T >
auto	ess (const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > &samples)

template<class T >
T	lse (T x, T y)

Variables
constexpr double	SQRT_TWO_PI

constexpr double	LOG_SQRT_TWO_PI

template<class T >
constexpr T	inf

template<class T >
constexpr T	neg_inf

Typedef Documentation

◆ dist_value_t

using ppl::math::dist_value_t = typedef util::dist_value_t

Function Documentation

◆ autocorrelation()

template<class T >

auto ppl::math::autocorrelation ( const Eigen::MatrixBase< T > & x )

inline

Computes autocorrelation of x where each column of x is a component of a process and hence each row is a time point. More mathematically, x(i,...) is the process value at time i.

For more detail, see: https://lingpipe-blog.com/2012/06/08/autocorrelation-fft-kiss-eigen/ https://github.com/stan-dev/math/blob/41e548e19da5675121c245b535d4019c8bbd754b/stan/math/prim/mat/fun/autocorrelation.hpp

Template Parameters

T	underlying value type (usually double)

Parameters

x	process matrix

◆ bernoulli_log_pdf() [1/3]

template<class XType , class PType >

dist_value_t ppl::math::bernoulli_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< PType > &	p
	)

inline

◆ bernoulli_log_pdf() [2/3]

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<PType> >>

dist_value_t ppl::math::bernoulli_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const PType &	p
	)

inline

◆ bernoulli_log_pdf() [3/3]

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<PType> >>

dist_value_t ppl::math::bernoulli_log_pdf	(	const XType &	x,
		const PType &	p
	)

inline

◆ bernoulli_pdf() [1/3]

template<class XType , class PType >

dist_value_t ppl::math::bernoulli_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< PType > &	p
	)

inline

◆ bernoulli_pdf() [2/3]

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<PType> >>

dist_value_t ppl::math::bernoulli_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const PType &	p
	)

inline

◆ bernoulli_pdf() [3/3]

template<class XType , class PType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<PType> >>

dist_value_t ppl::math::bernoulli_pdf	(	const XType &	x,
		const PType &	p
	)

inline

Bernoulli pdf and log pdf (pmf actually). It is defined to clip when p is out of the range [0,1], i.e. if p < 0, then we take p = 0 and if p > 1, then we take p = 1.

◆ cauchy_log_pdf() [1/5]

template<class XType , class LocType , class ScaleType >

dist_value_t ppl::math::cauchy_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< LocType > &	loc,
		const Eigen::MatrixBase< ScaleType > &	scale
	)

inline

◆ cauchy_log_pdf() [2/5]

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<ScaleType> >>

dist_value_t ppl::math::cauchy_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< LocType > &	loc,
		const ScaleType &	scale
	)

inline

◆ cauchy_log_pdf() [3/5]

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<LocType> >>

dist_value_t ppl::math::cauchy_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const LocType &	loc,
		const Eigen::MatrixBase< ScaleType > &	scale
	)

inline

◆ cauchy_log_pdf() [4/5]

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<LocType> && std::is_arithmetic_v<ScaleType> >>

dist_value_t ppl::math::cauchy_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const LocType &	loc,
		const ScaleType &	scale
	)

inline

◆ cauchy_log_pdf() [5/5]

template<class XType , class LocType , class ScaleType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<LocType> && std::is_arithmetic_v<ScaleType> >>

dist_value_t ppl::math::cauchy_log_pdf	(	const XType &	x,
		const LocType &	loc,
		const ScaleType &	scale
	)

inline

◆ ess() [1/2]

template<class T >

auto ppl::math::ess ( const details::vec_cref_t< T > & samples )

inline

Computes the effective sample size (ESS) for a given vector of samples (matrices). Every element of the vector is a matrix of samples for each chain. Every matrix contains the samples as rows, i.e. every row is a sample of an p-dimensional vector, where p is the number of columns of the matrix (number of parameters).

The algorithm assumes that every sample matrix has the same dimensions.

Template Parameters

T	underlying Eigen expression type

Parameters

samples vector of samples

Returns: a vector of ESS for each component If number of samples is 1 or less, or there are 0 components, or number of chains is 0, return an empty vector. In either case, the dimension of the return vector is same as the number of components.

◆ ess() [2/2]

template<class T >

auto ppl::math::ess ( const Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > & samples )

inline

Computes the effective sample size (ESS) for a given sample matrix. This is an overload for when there is only chain and can supply a single matrix instead. See above overload for more details.

Template Parameters

T	underlying Eigen expression type

Parameters

samples sample matrix (1 chain)

Returns: a vector of ESS for each component

◆ lse()

template<class T >

T ppl::math::lse	(	T	x,
		T	y
	)

inline

LogSumExp taken from wikipedia: log(e^x + e^y)

◆ normal_log_pdf() [1/5]

template<class XType , class MeanType , class SigmaType >

dist_value_t ppl::math::normal_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MeanType > &	mean,
		const Eigen::MatrixBase< SigmaType > &	sigma
	)

inline

◆ normal_log_pdf() [2/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<SigmaType> >>

dist_value_t ppl::math::normal_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MeanType > &	mean,
		const SigmaType &	sigma
	)

inline

◆ normal_log_pdf() [3/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> >>

dist_value_t ppl::math::normal_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MeanType &	mean,
		const Eigen::MatrixBase< SigmaType > &	sigma
	)

inline

◆ normal_log_pdf() [4/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>

dist_value_t ppl::math::normal_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MeanType &	mean,
		const SigmaType &	sigma
	)

inline

◆ normal_log_pdf() [5/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>

dist_value_t ppl::math::normal_log_pdf	(	const XType &	x,
		const MeanType &	mean,
		const SigmaType &	sigma
	)

inline

◆ normal_pdf() [1/5]

template<class XType , class MeanType , class SigmaType >

dist_value_t ppl::math::normal_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MeanType > &	mean,
		const Eigen::MatrixBase< SigmaType > &	sigma
	)

inline

◆ normal_pdf() [2/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<SigmaType> >>

dist_value_t ppl::math::normal_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MeanType > &	mean,
		const SigmaType &	sigma
	)

inline

◆ normal_pdf() [3/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> >>

dist_value_t ppl::math::normal_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MeanType &	mean,
		const Eigen::MatrixBase< SigmaType > &	sigma
	)

inline

◆ normal_pdf() [4/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>

dist_value_t ppl::math::normal_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MeanType &	mean,
		const SigmaType &	sigma
	)

inline

◆ normal_pdf() [5/5]

template<class XType , class MeanType , class SigmaType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MeanType> && std::is_arithmetic_v<SigmaType> >>

dist_value_t ppl::math::normal_pdf	(	const XType &	x,
		const MeanType &	mean,
		const SigmaType &	sigma
	)

inline

◆ padded_length()

size_t ppl::math::padded_length ( size_t N )

inline

◆ uniform_log_pdf() [1/5]

template<class XType , class MinType , class MaxType >

dist_value_t ppl::math::uniform_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MinType > &	min,
		const Eigen::MatrixBase< MaxType > &	max
	)

inline

◆ uniform_log_pdf() [2/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MaxType> >>

dist_value_t ppl::math::uniform_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MinType > &	min,
		const MaxType &	max
	)

inline

◆ uniform_log_pdf() [3/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> >>

dist_value_t ppl::math::uniform_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MinType &	min,
		const Eigen::MatrixBase< MaxType > &	max
	)

inline

◆ uniform_log_pdf() [4/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>

dist_value_t ppl::math::uniform_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MinType &	min,
		const MaxType &	max
	)

inline

◆ uniform_log_pdf() [5/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>

dist_value_t ppl::math::uniform_log_pdf	(	const XType &	x,
		const MinType &	min,
		const MaxType &	max
	)

inline

◆ uniform_pdf() [1/5]

template<class XType , class MinType , class MaxType >

dist_value_t ppl::math::uniform_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MinType > &	min,
		const Eigen::MatrixBase< MaxType > &	max
	)

inline

◆ uniform_pdf() [2/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MaxType> >>

dist_value_t ppl::math::uniform_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< MinType > &	min,
		const MaxType &	max
	)

inline

◆ uniform_pdf() [3/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> >>

dist_value_t ppl::math::uniform_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MinType &	min,
		const Eigen::MatrixBase< MaxType > &	max
	)

inline

◆ uniform_pdf() [4/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>

dist_value_t ppl::math::uniform_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const MinType &	min,
		const MaxType &	max
	)

inline

◆ uniform_pdf() [5/5]

template<class XType , class MinType , class MaxType , class = std::enable_if_t< std::is_arithmetic_v<XType> && std::is_arithmetic_v<MinType> && std::is_arithmetic_v<MaxType> >>

dist_value_t ppl::math::uniform_pdf	(	const XType &	x,
		const MinType &	min,
		const MaxType &	max
	)

inline

◆ wishart_log_pdf()

template<class XType , class VType , class NType >

dist_value_t ppl::math::wishart_log_pdf	(	const Eigen::MatrixBase< XType > &	x,
		const Eigen::MatrixBase< VType > &	v,
		const NType &	n
	)

inline

Variable Documentation

◆ inf

template<class T >

constexpr T ppl::math::inf

inlineconstexpr

Initial value:

= 
    std::numeric_limits<T>::is_iec559 ? 
    std::numeric_limits<T>::infinity() :
    std::numeric_limits<T>::max()

◆ LOG_SQRT_TWO_PI

constexpr double ppl::math::LOG_SQRT_TWO_PI

inlineconstexpr

Initial value:

=

0.918938533204672741780329736405617

◆ neg_inf

template<class T >

constexpr T ppl::math::neg_inf

inlineconstexpr

Initial value:

= 
    std::numeric_limits<T>::is_iec559 ? 
    -std::numeric_limits<T>::infinity() :
    std::numeric_limits<T>::lowest()

◆ SQRT_TWO_PI

constexpr double ppl::math::SQRT_TWO_PI

inlineconstexpr

Initial value:

=

2.506628274631000502415765284811045

Namespaces

Classes

Typedefs

Functions

Variables

Typedef Documentation

◆ dist_value_t

Function Documentation

◆ autocorrelation()

◆ bernoulli_log_pdf() [1/3]

◆ bernoulli_log_pdf() [2/3]

◆ bernoulli_log_pdf() [3/3]

◆ bernoulli_pdf() [1/3]

◆ bernoulli_pdf() [2/3]

◆ bernoulli_pdf() [3/3]

◆ cauchy_log_pdf() [1/5]

◆ cauchy_log_pdf() [2/5]

◆ cauchy_log_pdf() [3/5]

◆ cauchy_log_pdf() [4/5]

◆ cauchy_log_pdf() [5/5]

◆ ess() [1/2]

◆ ess() [2/2]

◆ lse()

◆ normal_log_pdf() [1/5]

◆ normal_log_pdf() [2/5]

◆ normal_log_pdf() [3/5]

◆ normal_log_pdf() [4/5]

◆ normal_log_pdf() [5/5]

◆ normal_pdf() [1/5]

◆ normal_pdf() [2/5]

◆ normal_pdf() [3/5]

◆ normal_pdf() [4/5]

◆ normal_pdf() [5/5]

◆ padded_length()

◆ uniform_log_pdf() [1/5]

◆ uniform_log_pdf() [2/5]

◆ uniform_log_pdf() [3/5]

◆ uniform_log_pdf() [4/5]

◆ uniform_log_pdf() [5/5]

◆ uniform_pdf() [1/5]

◆ uniform_pdf() [2/5]

◆ uniform_pdf() [3/5]

◆ uniform_pdf() [4/5]

◆ uniform_pdf() [5/5]

◆ wishart_log_pdf()

Variable Documentation

◆ inf

◆ LOG_SQRT_TWO_PI

◆ neg_inf

◆ SQRT_TWO_PI