hara.math.stats — hara/math 3.0.6

anderson-darling clj

(anderson-darling arr)

Performs the Anderson-Darling test for normality

(anderson-darling [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.]) => 2.1947640982019347

ansari clj

(ansari m n)

arcsine clj

(arcsine a b)

beta clj

(beta a b)

beta-binomial clj

(beta-binomial mu sigma bd)

beta-prime clj

(beta-prime a b)

binomial clj

(binomial n p)

cauchy clj

(cauchy location scale)

chi clj

(chi df)

chi-square clj

(chi-square df)

cramer-vonmises clj

(cramer-vonmises arr)

Performs the Cramer-vonMises test for normality

(cramer-vonmises [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.]) => 0.3625667515860767

cumulative clj

(cumulative dist x)

returns the cumulative density for the distribution

(cumulative (laplace 1 2) 4) => 0.888434919925785

(cumulative (binomial 10 0.3) [1 2 3]) => [0.14930834590000003 0.38278278639999974 0.6496107184000002]

exponential clj

(exponential scale)

extreme clj

(extreme dist mlen largest)

f clj

(f df1 df2)

fretchet clj

(fretchet loc scale shape)

gamma clj

(gamma scale shape)

generalized-pareto clj

(generalized-pareto loc scale shape)

geometric clj

(geometric p)

gev clj

(gev loc scale shape)

gumbel clj

(gumbel loc scale)

hyper-geometric clj

(hyper-geometric r b n)

inv-gamma clj

(inv-gamma shape scale)

inv-normal clj

(inv-normal mu sigma)

jarque-bera clj

(jarque-bera arr)

Performs the Jarque-Bera test for normality

(jarque-bera [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.]) => 2.1669737339380206

kendall clj

(kendall n)

kolmogorov-lilliefors clj

(kolmogorov-lilliefors arr)

Performs the Kolmogorov-Lilliefors test for normality

(-> [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.] kolmogorov-lilliefors) => 0.3515941066052153

kolmogorov-smirnov clj

(kolmogorov-smirnov arr)

Performs the Kolmogorov-Smirnov test for normality

(-> [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.] (kolmogorov-smirnov) seq) => [0.5 7.868992957994292E-4]

kumaraswamy clj

(kumaraswamy a b)

laplace clj

(laplace location scale)

levy clj

(levy mu sigma)

log-normal clj

(log-normal meanlog sdlog)

logarithmic clj

(logarithmic mu)

logistic clj

(logistic location scale)

nakagami clj

(nakagami m omega)

neg-binomial clj

(neg-binomial prob size)

non-central-beta clj

(non-central-beta a b ncp)

non-central-chi-square clj

(non-central-chi-square df ncp)

non-central-f clj

(non-central-f df1 df2 ncp)

non-central-t clj

(non-central-t df ncp)

normal clj

(normal mu sigma)

order clj

(order dist mlen j largest)

poisson clj

(poisson lambda)

probability clj

(probability dist x)

returns the probability density for the distribution

(probability (laplace 1 2) 4) => 0.05578254003710745

(probability (binomial 10 0.3) [1 2 3]) => [0.1210608209999997 0.2334744405000001 0.26682793199999993]

random-sample clj

(random-sample dist)

gives a random sample from distribution

(random-sample (laplace 1 2)) ;; 1.9528692108205805 => number?

rayleigh clj

(rayleigh scale)

reverse-weibull clj

(reverse-weibull loc scale shape)

shapiro-francia clj

(shapiro-francia arr)

Performs the Shapiro-Francia test for normality

(-> [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.] shapiro-francia) => 0.6756836312861318

shapiro-wilk clj

(shapiro-wilk arr)

Performs the Shapiro-Wilk test for normality

(-> [0. 0. 0. 0. 0. 0. 0. 100. 100. 100. 100. 100. 100.] shapiro-wilk) => 0.6457043943928288

sign-rank clj

(sign-rank n)

skewed-t clj

(skewed-t df gamma)

spearman clj

(spearman n)

t clj

(t df)

tukey clj

(tukey rr cc df)

uniform clj

(uniform a b)

weibull clj

(weibull shape scale)

wilcoxon clj

(wilcoxon m n)

zipf clj

(zipf N s)