pdflib

pdflib, a MATLAB code which evaluates Probability Density Functions (PDF's) and produces random samples from them, including beta, binomial, chi, exponential, gamma, inverse chi, inverse gamma, multinomial, normal, scaled inverse chi, and uniform.

Licensing:

The computer code and data files made available on this web page are distributed under the MIT license

Languages:

pdflib is available in a C version and a C++ version and a FORTRAN90 version and a MATLAB version and a Python version.

Related Data and Programs:

log_normal_truncated_ab, a MATLAB code which returns quantities associated with the log normal Probability Distribution Function (PDF) truncated to the interval [A,B].

pdflib_test

prob, a MATLAB code which evaluates, samples and inverts a number of Probability Density Functions (PDF's).

ranlib, a MATLAB code which produces random samples from Probability Density Functions (PDF's), including Beta, Chi-square Exponential, F, Gamma, Multivariate normal, Noncentral chi-square, Noncentral F, Univariate normal, random permutations, Real uniform, Binomial, Negative Binomial, Multinomial, Poisson and Integer uniform, by Barry Brown and James Lovato.

rnglib, a MATLAB code which implements a random number generator (RNG) with splitting facilities, allowing multiple independent streams to be computed, by L'Ecuyer and Cote.

walker_sample, a MATLAB code which efficiently samples a discrete probability vector using Walker sampling.

Source Code:

• i4_binomial_pdf.m, evaluates the binomial PDF.
• i4_binomial_sample.m, generates a binomial random deviate.
• i4_uniform_sample.m, generates a uniform random deviate.
• i4vec_multinomial_pdf.m, evaluates the multinomial PDF.
• i4vec_multinomial_sample.m, generates a multinomial random deviate.
• r8_beta_pdf.m, evaluates the PDF of a beta distribution.
• r8_beta_sample.m, generates a beta random deviate.
• r8_chi_pdf.m, evaluates the PDF of a chi-squared distribution.
• r8_chi_sample.m, generates a Chi-Square random deviate.
• r8_exponential_pdf.m, evaluates the PDF of an exponential distribution.
• r8_exponential_sample.m, samples the exponential PDF.
• r8_exponential_01_pdf.m, PDF of a standard exponential distribution.
• r8_exponential_01_sample.m, samples the standard exponential PDF.
• r8_gamma_pdf.m, evaluates the PDF of a gamma distribution.
• r8_gamma_sample.m, generates a Gamma random deviate.
• r8_gamma_01_pdf.m, evaluates the PDF of a standard gamma distribution.
• r8_gamma_01_sample.m, samples the standard Gamma distribution.
• r8_invchi_pdf.m, evaluates the PDF of an inverse chi-squared distribution.
• r8_invchi_sample.m, samples an inverse chi-squared distribution.
• r8_invgam_pdf.m, evaluates the PDF of an inverse gamma distribution.
• r8_invgam_sample.m, samples an inverse gamma distribution.
• r8_normal_pdf.m, evaluates the PDF of a normal distribution.
• r8_normal_sample.m, generates a normal random deviate.
• r8_normal_01_pdf.m, evaluates the PDF of a standard normal distribution.
• r8_normal_01_sample.m, returns a unit pseudonormal R8.
• r8_scinvchi_pdf.m, PDF for a scaled inverse chi-squared distribution.
• r8_scinvchi_sample.m, sample a scaled inverse chi-squared distribution.
• r8_uniform_pdf.m, evaluates the PDF of a uniform distribution.
• r8_uniform_sample.m, generates a uniform random deviate.
• r8_uniform_01_pdf.m, evaluates the PDF of a standard uniform distribution.
• r8_uniform_01_sample.m, generates a uniform random deviate from [0,1].
• r8mat_podet.m, computes the determinant of a factored positive definite matrix.
• r8mat_pofac.m, factors a real symmetric positive definite matrix.
• r8mat_poinv.m, computes the inverse of a factored positive definite matrix.
• r8mat_upsol.m, solves R * X = B for an upper triangular matrix R.
• r8mat_utsol.m, solves R' * X = B for an upper triangular matrix R.
• r8po_fa.m, factors a real symmetric positive definite matrix.
• r8vec_multinormal_pdf.m, evaluates a multivariate normal PDF.
• r8vec_multinormal_sample.m, samples a multivariate normal PDF.
• r8vec_print.m