math.stats.distribution

+distributions+

+distributions-map+

ansari

(ansari m n)

arcsine

(arcsine a b)

beta

(beta a b)

beta-binomial

(beta-binomial mu sigma bd)

beta-prime

(beta-prime a b)

binomial

(binomial n p)

cauchy

(cauchy location scale)

chi

(chi df)

chi-square

(chi-square df)

create-distribution-form

added in 3.0

(create-distribution-form [cls params])

creates the defn form for a particular distribution

(create-distribution-form [net.sourceforge.jdistlib.Wilcoxon :m :n]) => ’(defn wilcoxon m n (net.sourceforge.jdistlib.Wilcoxon. m n))

create-distribution-forms

added in 3.0

(create-distribution-forms)(create-distribution-forms dists)

helper for create-distributions

(create-distribution-forms) => vector?

create-distributions

macro

added in 3.0

(create-distributions)

creates all methods for constructing distributions

(create-distributions)

cumulative

added in 3.0

(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

(exponential scale)

extreme

(extreme dist mlen largest)

f

(f df1 df2)

fn-name

added in 3.0

(fn-name cls)

creates a function name based on class

(fn-name net.sourceforge.jdistlib.evd.Order) => “order”

fretchet

(fretchet loc scale shape)

gamma

(gamma scale shape)

generalized-pareto

(generalized-pareto loc scale shape)

geometric

(geometric p)

gev

(gev loc scale shape)

gumbel

(gumbel loc scale)

hyper-geometric

(hyper-geometric r b n)

inv-gamma

(inv-gamma shape scale)

inv-normal

(inv-normal mu sigma)

kendall

(kendall n)

kumaraswamy

(kumaraswamy a b)

laplace

(laplace location scale)

levy

(levy mu sigma)

log-normal

(log-normal meanlog sdlog)

logarithmic

(logarithmic mu)

logistic

(logistic location scale)

nakagami

(nakagami m omega)

neg-binomial

(neg-binomial prob size)

non-central-beta

(non-central-beta a b ncp)

non-central-chi-square

(non-central-chi-square df ncp)

non-central-f

(non-central-f df1 df2 ncp)

non-central-t

(non-central-t df ncp)

normal

(normal mu sigma)

order

(order dist mlen j largest)

poisson

(poisson lambda)

probability

added in 3.0

(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) => (contains (approx 0.1210608) (approx 0.2334744) (approx 0.2668279))

random-sample

added in 3.0

(random-sample dist)

gives a random sample from distribution

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

rayleigh

(rayleigh scale)

reverse-weibull

(reverse-weibull loc scale shape)

sign-rank

(sign-rank n)

skewed-t

(skewed-t df gamma)

spearman

(spearman n)

t

(t df)

tukey

(tukey rr cc df)

uniform

(uniform a b)

weibull

(weibull shape scale)

wilcoxon

(wilcoxon m n)

zipf

(zipf N s)