Exponential Distribution¶

Table of contents

Density Function ¶

The density function of the Exponential distribution:

\[f(x; \lambda) = \lambda \exp(-\lambda x) \times \mathbf{1}[ x \geq 0]\]

Methods for scalar input, as well as for vector/matrix input, are listed below.

Scalar Input ¶

template<typename T1, typename T2> constexpr common_return_t<T1, T2> dexp(const T1 x, const T2 rate_par, const bool log_form = false) noexcept¶

Density function of the Exponential distribution.

Example:

stats::dexp(1.0,2.0,false); 

Parameters

x – a real-valued input.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-density or the true form.

Returns

the density function evaluated at x.

Vector/Matrix Input ¶

STL Containers ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>> inline std::vector<rT> dexp(const std::vector<eT> &x, const T1 rate_par, const bool log_form = false)¶

Density function of the Exponential distribution.

Example:

std::vector<double> x = {1.8, 0.7, 4.2};
stats::dexp(x,4,false);

Parameters

x – a standard vector.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-density or the true form.

Returns

a vector of density function values corresponding to the elements of x.

Armadillo ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>> inline ArmaMat<rT> dexp(const ArmaMat<eT> &X, const T1 rate_par, const bool log_form = false)¶

Density function of the Exponential distribution.

Example:

arma::mat X = { {1.8, 0.7, 4.2},
                {0.3, 5.3, 3.7} };
stats::dexp(X,4,false);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-density or the true form.

Returns

a matrix of density function values corresponding to the elements of X.

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>, bool To = blaze::columnMajor> inline BlazeMat<rT, To> dexp(const BlazeMat<eT, To> &X, const T1 rate_par, const bool log_form = false)¶

Density function of the Exponential distribution.

Example:

stats::dexp(X,4,false);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-density or the true form.

Returns

a matrix of density function values corresponding to the elements of X.

Eigen ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>, int iTr = Eigen::Dynamic, int iTc = Eigen::Dynamic> inline EigenMat<rT, iTr, iTc> dexp(const EigenMat<eT, iTr, iTc> &X, const T1 rate_par, const bool log_form = false)¶

Density function of the Exponential distribution.

Example:

stats::dexp(X,4,false);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-density or the true form.

Returns

a matrix of density function values corresponding to the elements of X.

Cumulative Distribution Function ¶

The cumulative distribution function of the Exponential distribution:

\[\int_0^x f(z; \lambda) dz = 1 - \exp(-\lambda x \times \mathbf{1}[ x \geq 0])\]

Methods for scalar input, as well as for vector/matrix input, are listed below.

Scalar Input ¶

template<typename T1, typename T2> constexpr common_return_t<T1, T2> pexp(const T1 x, const T2 rate_par, const bool log_form = false) noexcept¶

Distribution function of the Exponential distribution.

Example:

stats::pexp(1.0,2.0,false); 

Parameters

x – a real-valued input.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-probability or the true form.

Returns

the cumulative distribution function evaluated at x.

Vector/Matrix Input ¶

STL Containers ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>> inline std::vector<rT> pexp(const std::vector<eT> &x, const T1 rate_par, const bool log_form = false)¶

Distribution function of the Exponential distribution.

Example:

std::vector<double> x = {1.8, 0.7, 4.2};
stats::pexp(x,2.0,false);

Parameters

x – a standard vector.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-probability or the true form.

Returns

a vector of CDF values corresponding to the elements of x.

Armadillo ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>> inline ArmaMat<rT> pexp(const ArmaMat<eT> &X, const T1 rate_par, const bool log_form = false)¶

Distribution function of the Exponential distribution.

Example:

arma::mat X = { {1.8, 0.7, 4.2},
                {0.3, 5.3, 3.7} };
stats::pexp(X,2.0,false);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-probability or the true form.

Returns

a matrix of CDF values corresponding to the elements of X.

Blaze ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>, bool To = blaze::columnMajor> inline BlazeMat<rT, To> pexp(const BlazeMat<eT, To> &X, const T1 rate_par, const bool log_form = false)¶

Distribution function of the Exponential distribution.

Example:

stats::pexp(X,2.0,false);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-probability or the true form.

Returns

a matrix of CDF values corresponding to the elements of X.

Eigen ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>, int iTr = Eigen::Dynamic, int iTc = Eigen::Dynamic> inline EigenMat<rT, iTr, iTc> pexp(const EigenMat<eT, iTr, iTc> &X, const T1 rate_par, const bool log_form = false)¶

Distribution function of the Exponential distribution.

Example:

stats::pexp(X,2.0,false);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.
log_form – return the log-probability or the true form.

Returns

a matrix of CDF values corresponding to the elements of X.

Quantile Function ¶

The quantile function of the Exponential distribution:

\[q(p; \lambda) = - \ln (1 - p) / \lambda\]

Methods for scalar input, as well as for vector/matrix input, are listed below.

Scalar Input ¶

template<typename T1, typename T2> constexpr common_return_t<T1, T2> qexp(const T1 p, const T2 rate_par) noexcept¶

Quantile function of the Exponential distribution.

Example:

stats::qexp(0.5,4.0); 

Parameters

p – a real-valued input.
rate_par – the rate parameter, a real-valued input.

Returns

the quantile function evaluated at p.

Vector/Matrix Input ¶

STL Containers ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>> inline std::vector<rT> qexp(const std::vector<eT> &x, const T1 rate_par)¶

Quantile function of the Exponential distribution.

Example:

std::vector<double> x = {0.3, 0.5, 0.8};
stats::qexp(x,4);

Parameters

x – a standard vector.
rate_par – the rate parameter, a real-valued input.

Returns

a vector of quantile values corresponding to the elements of x.

Armadillo ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>> inline ArmaMat<rT> qexp(const ArmaMat<eT> &X, const T1 rate_par)¶

Quantile function of the Exponential distribution.

Example:

arma::mat X = { {0.2, 0.7, 0.9},
                {0.1, 0.8, 0.3} };
stats::qexp(X,4);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.

Returns

a matrix of quantile values corresponding to the elements of X.

Blaze ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>, bool To = blaze::columnMajor> inline BlazeMat<rT, To> qexp(const BlazeMat<eT, To> &X, const T1 rate_par)¶

Quantile function of the Exponential distribution.

Example:

stats::qexp(X,4);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.

Returns

a matrix of quantile values corresponding to the elements of X.

Eigen ¶

template<typename eT, typename T1, typename rT = common_return_t<eT, T1>, int iTr = Eigen::Dynamic, int iTc = Eigen::Dynamic> inline EigenMat<rT, iTr, iTc> qexp(const EigenMat<eT, iTr, iTc> &X, const T1 rate_par)¶

Quantile function of the Exponential distribution.

Example:

stats::qexp(X,4);

Parameters

X – a matrix of input values.
rate_par – the rate parameter, a real-valued input.

Returns

a matrix of quantile values corresponding to the elements of X.

Random Sampling ¶

Random sampling for the Cauchy distribution is achieved via the inverse probability integral transform.

Scalar Output ¶

Random number engines

template<typename T> inline return_t<T> rexp(const T rate_par, rand_engine_t &engine)¶

Random sampling function for the Exponential distribution.

Example:

stats::rand_engine_t engine(1776);
stats::rexp(4,engine);

Parameters

rate_par – the rate parameter, a real-valued input.
engine – a random engine, passed by reference.

Returns

a pseudo-random draw from the Exponential distribution.

Seed values

template<typename T> inline return_t<T> rexp(const T rate_par, const ullint_t seed_val = std::random_device{}())¶

Random sampling function for the Exponential distribution.

Example:

stats::rexp(4,1776);

Parameters

rate_par – the rate parameter, a real-valued input.
seed_val – initialize the random engine with a non-negative integral-valued seed.

Returns

a pseudo-random draw from the Exponential distribution.

Vector/Matrix Output ¶

Random number engines

template<typename mT, typename T1> inline mT rexp(const ullint_t n, const ullint_t k, const T1 rate_par, rand_engine_t &engine)¶

Random matrix sampling function for the Exponential distribution.

Example:

stats::rand_engine_t engine(1776);
// std::vector
stats::rexp<std::vector<double>>(5,4,4,engine);
// Armadillo matrix
stats::rexp<arma::mat>(5,4,4,engine);
// Blaze dynamic matrix
stats::rexp<blaze::DynamicMatrix<double,blaze::columnMajor>>(5,4,4,engine);
// Eigen dynamic matrix
stats::rexp<Eigen::MatrixXd>(5,4,4,engine);

Note

This function requires template instantiation; acceptable output types include: std::vector, with element type float, double, etc., as well as Armadillo, Blaze, and Eigen dense matrices.

Parameters

n – the number of output rows
k – the number of output columns
rate_par – the rate parameter, a real-valued input.
engine – a random engine, passed by reference.

Returns

a matrix of pseudo-random draws from the Exponential distribution.

Seed values

template<typename mT, typename T1> inline mT rexp(const ullint_t n, const ullint_t k, const T1 rate_par, const ullint_t seed_val = std::random_device{}())¶

Random matrix sampling function for the Exponential distribution.

Example:

// std::vector
stats::rexp<std::vector<double>>(5,4,4,engine);
// Armadillo matrix
stats::rexp<arma::mat>(5,4,4,engine);
// Blaze dynamic matrix
stats::rexp<blaze::DynamicMatrix<double,blaze::columnMajor>>(5,4,4,engine);
// Eigen dynamic matrix
stats::rexp<Eigen::MatrixXd>(5,4,4,engine);

Note

This function requires template instantiation; acceptable output types include: std::vector, with element type float, double, etc., as well as Armadillo, Blaze, and Eigen dense matrices.

Parameters

n – the number of output rows
k – the number of output columns
rate_par – the rate parameter, a real-valued input.
seed_val – initialize the random engine with a non-negative integral-valued seed.

Returns

a matrix of pseudo-random draws from the Exponential distribution.