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hara.math.stats


anderson-darlingclj

(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

Performs the Anderson-Darling test for normality

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

ansariclj

(ansari m n)

arcsineclj

(arcsine a b)

betaclj

(beta a b)

beta-binomialclj

(beta-binomial mu sigma bd)

beta-primeclj

(beta-prime a b)

binomialclj

(binomial n p)

cauchyclj

(cauchy location scale)

chiclj

(chi df)

chi-squareclj

(chi-square df)

cramer-vonmisesclj

(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

Performs the Cramer-vonMises test for normality

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

cumulativeclj

(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]

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]
raw docstring

exponentialclj

(exponential scale)

extremeclj

(extreme dist mlen largest)

fclj

(f df1 df2)

fretchetclj

(fretchet loc scale shape)

gammaclj

(gamma scale shape)

generalized-paretoclj

(generalized-pareto loc scale shape)

geometricclj

(geometric p)

gevclj

(gev loc scale shape)

gumbelclj

(gumbel loc scale)

hyper-geometricclj

(hyper-geometric r b n)

inv-gammaclj

(inv-gamma shape scale)

inv-normalclj

(inv-normal mu sigma)

jarque-beraclj

(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

Performs the Jarque-Bera test for normality

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

kendallclj

(kendall n)

kolmogorov-lillieforsclj

(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

Performs the Kolmogorov-Lilliefors test for normality

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

kolmogorov-smirnovclj

(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]

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]
raw docstring

kumaraswamyclj

(kumaraswamy a b)

laplaceclj

(laplace location scale)

levyclj

(levy mu sigma)

log-normalclj

(log-normal meanlog sdlog)

logarithmicclj

(logarithmic mu)

logisticclj

(logistic location scale)

nakagamiclj

(nakagami m omega)

neg-binomialclj

(neg-binomial prob size)

non-central-betaclj

(non-central-beta a b ncp)

non-central-chi-squareclj

(non-central-chi-square df ncp)

non-central-fclj

(non-central-f df1 df2 ncp)

non-central-tclj

(non-central-t df ncp)

normalclj

(normal mu sigma)

orderclj

(order dist mlen j largest)

poissonclj

(poisson lambda)

probabilityclj

(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]

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]
raw docstring

random-sampleclj

(random-sample dist)

gives a random sample from distribution

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

gives a random sample from distribution

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

rayleighclj

(rayleigh scale)

reverse-weibullclj

(reverse-weibull loc scale shape)

shapiro-franciaclj

(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

Performs the Shapiro-Francia test for normality

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

shapiro-wilkclj

(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

Performs the Shapiro-Wilk test for normality

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

sign-rankclj

(sign-rank n)

skewed-tclj

(skewed-t df gamma)

spearmanclj

(spearman n)

tclj

(t df)

tukeyclj

(tukey rr cc df)

uniformclj

(uniform a b)

weibullclj

(weibull shape scale)

wilcoxonclj

(wilcoxon m n)

zipfclj

(zipf N s)

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