Crate ruststat

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§ruststat

Utilities for working with many common random variables.

probability mass function (pmf), probability density function (pdf) cumulative distribution function (cdf) percentiles (inverse cdf) random number generation mean, variance

Distributions: Continuous: beta, chi-square, exponential, F, gamma, normal, log-normal, Pareto (1 thru 4), Student’s t, continuous uniform Discrete: binomial, geometric, hypergeometric, negative binomial, poisson

Utilities for working with many common random variables.

probability mass function (pmf), probability density function (pdf)
cumulative distribution function (cdf)
percentiles (inverse cdf)
random number generation
mean, variance

Distributions:

Continuous: beta, chi-square, exponential, F, gamma, normal, log-normal, Pareto (1 thru 4), Student’s t, continuous uniform
Discrete: binomial, geometric, hypergeometric, negative binomial, poisson

§Quick Start

use ruststat::*;
// X~N(mu=0,sigma=1.0), find 97.5th percentile
println!("normal percentile: {}", normal_per(0.975, 0.0, 1.0));
// X~Bin(n=10,p=0.7), compute P(X=4)
println!("binomial probability: {}", bin_pmf(4, 10, 0.7));

For convenience, functions can also be accessed via Structs.

use ruststat::*;
// X~Beta(alpha=0.5,beta=2.0)
let mut mybeta = BetaDist{alpha:0.5, beta:2.0};
// 30th percentile
println!("percentile: {}", mybeta.per(0.3));
// P(X <= 0.4)
println!("cdf: {}", mybeta.cdf(0.4));
// Random draw
println!("random draw: {}", mybeta.ran());
// Variance
println!("variance: {}", mybeta.var());

Structs§

BetaDist: Struct for the beta distribution X ~ Beta(alpha, beta).
BinDist: Struct for the binomial distirubion X ~ Bin(n,p).
ChiSqDist: Struct for the chi-square distribution X ~ ChiSq(nu).
ExpDist: Struct for the exponential distribution X ~ Exp(lambda).
FDist: Struct for the F distribution X ~ F(nu1, nu2).
GammaDist: Struct for the gamma distribution X ~ Gamma(alpha, beta).
Geo2Dist: Struct for the geometric distribution X ~ Geo(p) where X = the trial on which the first success is observed.
GeoDist: Struct for the geometric distribution X ~ Geo(p) where X = the number of failures prior to observing the first success.
GumbelDist: Struct for the Gumbel distribution X ~ Gumbel(mu, beta).
HGDist: Struct for the hypergeometric distribution X ~ HG(n,N,M).
LogNormalDist: Struct for the log-normal distribution X ~ LogNormal(mu, sigma).
NB2Dist: Struct for the negative binomial distribution X ~ NB(r,p) where X = the trial on which the rth success is observed.
NBDist: Struct for the negative binomial distribution X ~ NB(r,p) where X = the number of failures prior to observing the rth success.
NormalDist: Struct for the normal distribution X ~ Normal(mu, sigma).
Pareto1Dist: Struct for the Pareto (type I) distribution X ~ Pareto1(sigma, alpha).
Pareto2Dist: Struct for the Pareto (type II) distribution X ~ Pareto2(mu, sigma, alpha).
Pareto3Dist: Struct for the Pareto (type III) distribution X ~ Pareto3(mu, sigma, gamma).
Pareto4Dist: Struct for the Pareto (type IV) distribution X ~ Pareto4(mu, sigma, gamma, alpha).
PoisDist: Struct for the Poisson distribution X ~ Pois(lambda).
TDist: Struct for Student’s t distribution X ~ t(nu).
UnifDist: Struct for continuous uniform distribution X ~ Unif(a,b).

Functions§

beta_cdf: Computes cumulative distribution function (cdf) for X ~ Beta(alpha, beta).
beta_fn: Computes beta function.
beta_pdf: Computes probability density function (pdf) for X ~ Beta(alpha, beta).
beta_per: Computes a percentile for X ~ Beta(alpha,beta)
beta_ran: Random draw from X ~ Beta(alpha,beta) distribution.
beta_ranvec: Save random draws from X ~ Beta(alpha, beta) distribution into a Vec
betai: Incomplete beta function.
betai_inv: Inverse of incomplete beta function
bin_cdf: Computes cumulative distribution function (cdf) for X ~ Bin(n,p)
bin_per: Computes a percentile for X ~ Bin(n,p)
bin_pmf: Computes probability mass function (pmf) for X ~ Bin(n,p)
bin_ran: Random draw from X ~ Bin(n,p) distribution Sheldon Ross, Simulation, (2003)
bin_ranvec: Save random draws from X ~ Bin(n,p) distribution into a Vec
chisq_cdf: Computes cumulative distribution function (cdf) for X ~ ChiSq(nu).
chisq_pdf: Computes probability density function (pdf) for X ~ ChiSq(nu).
chisq_per: Computes a percentile for X ~ ChiSq(nu)
chisq_ran: Random draw from X ~ ChiSq(nu) distribution.
chisq_ranvec: Save random draws from X ~ ChiSq(nu) into a Vec.
comb: Combination
erf: Error function (Chebyshev implementation)
erf2: Error function (gammp implementation) Erf(x)
erf_inv: Inverse of error function
erfc: Complementary error function
erfc_inv: Inverse of complementary error function
exp_cdf: Computes cumulative distribution function (cdf) for X ~ Exp(lambda).
exp_pdf: Computes probability density function (pdf) for X ~ Exp(lambda).
exp_per: Computes a percentile for X ~ Exp(lambda)
exp_ran: Random draw from X ~ Exp(lambda) distribution.
exp_ranvec: Save random draws from X ~ Exp(lambda) into a Vec.
f_cdf: Computes cumulative distribution function (cdf) for X ~ F(nu1, nu2).
f_pdf: Computes probability density function (pdf) for X ~ F(nu1, nu2).
f_per: Computes a percentile for X ~ F(nu1, nu2).
f_ran: Random draw from X ~ F(nu1, nu2) distribution.
f_ranvec: Save random draws from X ~ F(nu1, nu2) distribution into a Vec
fact_f: Generalized factorial (f64).
fact_i: Factorial (i32).
factln_f: Log Generalized factorial (f64).
factln_i: Log factorial (i32).
gamma: Gamma function
gamma_cdf: Computes cumulative distribution function (cdf) for X ~ Gamma(alpha, beta).
gamma_pdf: Computes probability density function (pdf) for X ~ Gamma(alpha, beta).
gamma_per: Computes a percentile for X ~ Gamma(alpha, beta).
gamma_ran: Random draw from X ~ Gamma(alpha, beta) distribution.
gamma_ranvec: Save random draws from X ~ Gamma(alpha, beta) distribution into a Vec
gammai_inv: Inverse of incomplete gamma function
gammaln: Log gamma function
gammapprox: Incomplete gamma function, quadrature P(x,a)
gammp: Incomplete gamma function P(x,a)
gammq: Complmentary incomplete gamma function Q(x,a)
gcf: Incomplete gamma function, continued fraction representation
geo2_cdf: Computes cumulative distribution function (cdf) for X ~ Geo(p) where X = the trial on which the first success is observed.
geo2_per: Computes a percentile for X ~ Geo(p) where X = the trial on which the first success is observed.
geo2_pmf: Computes probability mass function (pmf) for X ~ Geo(p) where X = the trial on which the first success is observed.
geo2_ran: Random draw from X ~ Geo(p) distribution where X = the trial on which the first success is observed.
geo2_ranvec: Save random draws from X ~ Geo(p) distribution into a Vec where X = the trial on which the first success is observed.
geo_cdf: Computes cumulative distribution function (cdf) for X ~ Geo(p) where X = the number of failures prior to the first success.
geo_per: Computes a percentile for X ~ Geo(p) where X = the number of failures prior to the first success.
geo_pmf: Computes probability mass function (pmf) for X ~ Geo(p) where X = the number of failures prior to the first success.
geo_ran: Random draw from X ~ Geo(p) distribution where X = the number of failures prior to the first success.
geo_ranvec: Save random draws from X ~ Geo(p) distribution into a Vec
gser: Incomplete gamma function, series representation
gumbel_cdf: Computes cumulative distribution function (cdf) for X ~ Gumbel(mu, beta).
gumbel_pdf: Computes probability density function (pdf) for X ~ Gumbel(mu, beta).
gumbel_per: Computes a percentile for X ~ Gumbel(mu, beta).
gumbel_ran: Random draw from X ~ Gumbel(mu, beta) distribution.
gumbel_ranvec: Random Vector taken from X ~ Gumbel(mu, beta) distribution.
hg_cdf: Computes cumulative distribution function (cdf) for X ~ HG(n,N,M) where X = the number of successes.
hg_per: Computes a percentile for X ~ HG(n,N,M) where X = the number of successes.
hg_pmf: Computes probability mass function (pmf) for X ~ HG(n,N,M) where X = the number of successes.
hg_ran: Random draw from X ~ HG(n, N, M) distribution where X = the number of successes.
hg_ranvec: Save random draws from X ~ HG(n,N,M) distribution into a Vec where X = the number of successes.
lognormal_cdf: Computes cumulative distribution function (cdf) for X ~ LogNormal(mu, sigma).
lognormal_pdf: Computes probability density function (pdf) for X ~ LogNormal(mu, sigma).
lognormal_per: Computes a percentile for X ~ LogNormal(mu, sigma).
lognormal_ran: Random draw from X ~ LogNormal(mu, sig) distribution.
lognormal_ranvec: Save random draws from X ~ LogNormal(mu, sigma) distribution into a Vec
nb2_cdf: Computes cumulative distribution function (cdf) for X ~ NB(r,p) where X = the trial on which the rth success is observed.
nb2_per: Computes a percentile for X ~ NB(r,p) where X = the trial on which the rth success is observed.
nb2_pmf: Computes probability mass function (pmf) for X ~ NB(r,p) where X = the trial on which the rth success is observed.
nb2_ran: Random draw from X ~ NB(r, p) distribution where X = the trial on which the rth success is observed.
nb2_ranvec: Save random draws from X ~ NB(r,p) distribution into a Vec where X = the trial on which the rth success is observed.
nb_cdf: Computes cumulative distribution function (cdf) for X ~ NB(r,p) where X = the number of failures prior to the rth success.
nb_per: Computes a percentile for X ~ NB(r,p) where X = the number of failures prior to the rth success.
nb_pmf: Computes probability mass function (pmf) for X ~ NB(r,p) where X = the number of failures prior to the rth success.
nb_ran: Random draw from X ~ NB(r, p) distribution where X = the number of failures prior to the rth success.
nb_ranvec: Save random draws from X ~ NB(r,p) distribution into a Vec where X = the number of failures prior to the rth success.
normal_cdf: Computes cumulative distribution function (cdf) for X ~ Normal(mu, sigma).
normal_pdf: Computes probability density function (pdf) for X ~ Normal(mu, sigma).
normal_per: Computes a percentile for X ~ Normal(mu, sigma).
normal_ran: Random draw from X ~ Normal(mu, sigma) distribution.
normal_ranvec: Save random draws from X ~ Normal(mu, sigma) distribution into a Vec
pareto4_cdf: Computes cumulative distribution function (cdf) for X ~ Pareto(mu, sigma, gamma, alpha).
pareto4_pdf: Computes probability density function (pdf) for X ~ Pareto(mu, sigma, gamma, alpha).
pareto4_per: Computes a percentile for X ~ Pareto(mu, sigma, gamma, alpha).
pareto4_ran: Random draw from X ~ Pareto(mu, sigma, gamma, alpha) distribution.
pareto4_ranvec: Save random draws from X ~ Pareto(mu, sigma, gamma, alpha) distribution into a Vec
pois_cdf: Computes cumulative distriubtion function (cdf) for X ~ Pois(lambda).
pois_per: Computes a percentile for X ~ Pois(lambda).
pois_pmf: Computes probability mass function (pmf) for X ~ Pois(lambda).
pois_ran: Random draw from X ~ Pois(r, p) distribution. Sheldon Ross, Simulation, 2003
pois_ranvec: Save random draws from X ~ Pois(lambda) distribution into a Vec
sample_mean: Computes sample mean of elements in a Vec
sample_sd: Computes sample standard deviation of elements in a Vec
sample_var: Computes sample variance of elements in a Vec
t_cdf: Computes cumulative distribution function (cdf) for X ~ t(nu).
t_pdf: Computes probability density function (pdf) for X ~ t(nu).
t_per: Computes a percentile for X ~ t(nu).
t_ran: Random draw from X ~ t(nu) distribution.
t_ranvec: Save random draws from X ~ t(nu) distribution into a Vec
unif_cdf: Computes cumulative distribution function (cdf) for X ~ Unif(a,b).
unif_pdf: Computes probability density function (pdf) for X ~ Unif(a,b).
unif_per: Computes a percentile for X ~ Unif(a,b).
unif_ran: Random draw from X ~ Unif(a,b) distribution.
unif_ranvec: Save random draws from X ~ Unif(a,b) distribution into a Vec

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§ruststat

§Quick Start

Structs§

Functions§

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