The Log Normal Probability Density Function

**LOG_NORMAL**
is a MATLAB library which
can evaluate quantities associated with the log normal Probability
Density Function (PDF).

If X is a variable drawn from the log normal distribution, then correspondingly, the logarithm of X will have the normal distribution.

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

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

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

NORMAL, a MATLAB library which samples the normal distribution.

PDFLIB, a MATLAB library 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.

PROB, a MATLAB library which evaluates, samples, inverts, and characterizes a number of Probability Density Functions (PDF's) and Cumulative Density Functions (CDF's), including anglit, arcsin, benford, birthday, bernoulli, beta_binomial, beta, binomial, bradford, burr, cardiod, cauchy, chi, chi squared, circular, cosine, deranged, dipole, dirichlet mixture, discrete, empirical, english sentence and word length, error, exponential, extreme values, f, fisk, folded normal, frechet, gamma, generalized logistic, geometric, gompertz, gumbel, half normal, hypergeometric, inverse gaussian, laplace, levy, logistic, log normal, log series, log uniform, lorentz, maxwell, multinomial, nakagami, negative binomial, normal, pareto, planck, poisson, power, quasigeometric, rayleigh, reciprocal, runs, sech, semicircular, student t, triangle, uniform, von mises, weibull, zipf.

TRUNCATED_NORMAL, a MATLAB library which works with the truncated normal distribution over [A,B], or [A,+oo) or (-oo,B], returning the probability density function (PDF), the cumulative density function (CDF), the inverse CDF, the mean, the variance, and sample values.

UNIFORM, a MATLAB library which samples the uniform distribution.

- log_normal_cdf.m evaluates the Lognormal CDF.
- log_normal_cdf_test.m
- log_normal_cdf_inv.m inverts the Lognormal CDF.
- log_normal_cdf_values.m returns some values of the Log Normal CDF.
- log_normal_check.m checks the parameters of the Lognormal PDF.
- log_normal_mean.m returns the mean of the Lognormal PDF.
- log_normal_pdf.m evaluates the Lognormal PDF.
- log_normal_sample.m samples the Lognormal PDF.
- log_normal_sample_test.m
- log_normal_variance.m returns the variance of the Lognormal PDF.
- normal_01_cdf.m evaluates the Normal 01 CDF.
- normal_01_cdf_inv.m inverts the Normal 01 CDF.
- normal_cdf.m evaluates the Normal CDF.
- normal_cdf_inv.m inverts the Normal CDF.
- r8_uniform_01.m returns a random value in [0,1].
- r8poly_value_horner.m evaluates a polynomial.
- r8vec_max.m returns the maximum value in an R8VEC.
- r8vec_mean.m returns the mean of an R8VEC.
- r8vec_min.m returns the minimum value in an R8VEC.
- r8vec_variance.m returns the variance of an R8VEC..
- timestamp.m returns the current YMDHMS date as a timestamp.

- log_normal_test.m, runs all the tests;
- log_normal_test_output.txt, the output file.

You can go up one level to the MATLAB source codes.