A  
add [Sample.Summary] 
Adds a value to the data set.

adjust [Tests.Multiple] 
Adjusts obtained Pvalues for multiple comparisons using a given
adjustment method.

B  
bca [Resampling.Bootstrap] 
Biascorrected and accelerated (BCa) bootstrap.

bernoulli [Distributions]  
beta [Distributions]  
binomial [Distributions]  
C  
cauchy [Distributions]  
chi_squared [Distributions]  
compare [Distributions.Categorical.OrderedType]  
continuous_by [Sample.Quantile] 
O(n log n) Estimates sample quantile corresponding to the given
probability
p , using the continuous sample method with given
parameters.

create [Distributions.Categorical.S] 
Creates a categorical distribution over values of type
elt ,
where each value is given a probability, which defaults to 0
for values not in the list.

create [Distributions.NegativeBinomial] 
Creates negative Binomial distribution with a given number of
failures and success probability.

create [Distributions.Hypergeometric] 
Creates Hypergeometric distribution.

create [Distributions.Geometric] 
Creates Geometric distribution with a given probability of success.

create [Distributions.Binomial] 
Creates binomial distribution.

create [Distributions.Bernoulli] 
Creates Bernoulli distribution with given success probability
p .

create [Distributions.Poisson] 
Creates a Poisson distribution.

create [Distributions.Logistic] 
Creates logistic distribution.

create [Distributions.Beta] 
Creates beta distribution.

create [Distributions.Cauchy] 
Creates CauchyLorentz distribution from parameters.

create [Distributions.Gamma] 
Creates gamma distribution.

create [Distributions.T] 
Creates Student's tdistribution with a given number of degrees
of freedom.

create [Distributions.F] 
Creates FisherSnedecor distribution with a given number of degrees
of freedom.

create [Distributions.ChiSquared] 
Creates chisquared distribution.

create [Distributions.Exponential] 
Creates exponential distribution.

create [Distributions.Uniform] 
Creates uniform distribution over a given interval.

create [Distributions.LogNormal] 
Creates lognormal distribution from parameters.

create [Distributions.Normal] 
Creates normal distribution from parameters.

cumulative [Base] 
O(n) Calculates a cumulative statistic over a given array.

cumulative_probability [Distributions.ContinuousDistribution] 
Computes cumulative probability function for a given value
n ,
i.

cumulative_probability [Distributions.DiscreteDistribution] 
Computes cumulative probability function for a given value
n ,
i.

D  
density [Distributions.ContinuousDistribution] 
Computes probability density function for a given value
n , i.

E  
empty [Sample.Summary] 
Empty data set.

estimate_pdf [Sample.KDE] 
O(n * points) Simple kernel density estimator.

exponential [Distributions]  
F  
f [Distributions]  
G  
gamma [Distributions]  
geometric [Distributions]  
goodness_of_fit [Tests.KolmogorovSmirnov] 
Onesample KolmogorovSmirnov test for goodness of fit, which
evaluates the distribution
G(x) of the observed random variable
against a given distribution F(x) .

goodness_of_fit [Tests.ChiSquared]  
H  
histogram [Sample] 
O(n) Computes histogram of a data set.

hypergeometric [Distributions]  
I  
independence [Tests.ChiSquared]  
iqr [Sample.Quantile] 
O(n log n) Estimates interquantile range of a given sample,
using the continuous sample method with given parameters.

iqr [Sample] 
O(n log n) Estimates interquantile range of a given sample,
using the continuous sample method with given parameters.

J  
jackknife [Resampling] 
Repeatidly computes a statistical estimate over the data set, leaving
out a single observation at a time.

K  
kurtosis [Sample.Summary] 
Returns the excess kurtosis of the values that have been added
or
nan if the data set is empty.

kurtosis [Sample] 
O(n) Computes the excess kurtosis of a sample, which is a
measure of a "peakedness" of its distribution.

kurtosis [Distributions.Features.S]  
kurtosis_opt [Distributions.Features.Opt]  
L  
log_normal [Distributions]  
logistic [Distributions]  
M  
mappend [Algebra.Monoid.S] 
Associative binary operation.

max [Sample.Summary] 
Returns the maximum added value or
nan if the data set is empty.

max [Sample]  
mean [Sample.Summary] 
Returns the arithmetic mean of the values that have been added
or
nan if the data set is empty.

mean [Sample] 
O(n) Computes sample's arithmetic mean.

mean [Distributions.Features.S]  
mean_opt [Distributions.Features.Opt]  
mempty [Algebra.Monoid.S] 
Identity, subject to
mappend mempty x = mappend x mempty = x .

min [Sample.Summary] 
Returns the minimum added value or
nan is the data set is empty.

min [Sample]  
minmax [Sample]  
mle [Distributions.Categorical.S] 
Creates a categorical distribution with a MLE of parameters,
estimated from given data.

mle [Distributions.Bernoulli] 
Creates a Bernoulli distribution with a MLE of parameters, estimated
from given data.

mle [Distributions.Poisson] 
Creates a Poisson distribution with a MLE of parameters, estimated
from given data.

mle [Distributions.Exponential] 
Creates exponential distribution with a MLE of parameters, estimated
from given data.

mle [Distributions.Uniform] 
Creates uniform distribution with a MLE of parameters, estimated
from given data.

mle [Distributions.LogNormal] 
Creates lognormal distribution with a MLE of parameters, estimated
from given data.

mle [Distributions.Normal] 
Creates normal distribution with a MLE of parameters, estimated
from given data.

mme [Distributions.NegativeBinomial] 
Creates negative Binomial distribution with parameters, estimated
with method of moments.

mme [Distributions.Geometric] 
Creates Geometric distribution with parameters, estimated with
method of moments.

mme [Distributions.Binomial] 
Creates binomial distribution with parameters, estimated with
method of moments.

mme [Distributions.Logistic] 
Creates logistic distribution with parameters, estimated with method
of moments.

mme [Distributions.Beta] 
Creates beta distribution with parameters, estimated with method
of moments.

mme [Distributions.Gamma] 
Creates gamma distribution with parameters, estimated with method
of moments.

mme [Distributions.T] 
Creates Student's tdistribution with parameters, estimated with
method of moments.

mme [Distributions.F] 
Creates FisherSnedecor distribution with parameters, estimated
with method of moments.

mme [Distributions.ChiSquared] 
Creates chisquared distribution with parameters, estimated with
method of moments.

moments [Sample] 
O(n k) Computes an array of sample moments of order 1 to k, i.

N  
negative_binomial [Distributions]  
normal [Distributions]  
O  
one_sample [Tests.Sign] 
Sign test, which evaluates the null hypothesis that sample median is
equal to the specified
shift .

one_sample [Tests.WilcoxonT] 
Wilcoxon signedrank test, which evaluates the null hypothesis
that sample median is equal to the specified
shift .

one_sample [Tests.T] 
One sample Student's ttest, which evaluates the null hypothesis
that a
mean of a normally distributed variable is equal to the
specified value.

P  
pearson [Sample.Correlation.Auto] 
O(n^2) Computes autocorrelation, using Person productmoment
correlation coefficient.

pearson [Sample.Correlation] 
O(n) Computes Pearson productmoment correlation coefficient
for two given samples.

poisson [Distributions]  
probability [Distributions.DiscreteDistribution] 
Computes probability mass function for a given value
n , i.

Q  
quantile [Sample] 
O(n log n) Estimates sample quantile corresponding to the given
probability
p , using the continuous sample method with default
parameters.

quantile [Distributions.ContinuousDistribution] 
Computes inverse cumulative probability function for a given
probability
p .

R  
range [Sample] 
O(n) Computes sample's range, i.

range [Base] 
Creates an array of integers given a semiopen range
[a, b) .

rank [Sample] 
O(n log n) Computes sample's ranks,
ties_strategy controls
which ranks are assigned to equal values:

reorder [Base] 
O(n) Reorders values in
src into dst , according to a given
permutation of indices.

resample [Resampling] 
Repeatidly resamples a given data set with replacement, computing a
statistical estimate over the resampled data.

run_test [Tests] 
Assess significance of the statistical test at a given
significance_level , which defaults to 0.05 .

S  
sample [Distributions.ContinuousDistribution] 
Samples
size data points from the distribution.

sample [Distributions.DiscreteDistribution] 
Samples
size data points from the distribution.

sample [Base] 
O(n) Takes a sample of the specified
size from the given
array either with or without replacement.

sd [Sample.Summary] 
Returns the standard deviation of the values that have been added
or
nan if the data set is empty.

sd [Sample] 
O(n) Computes sample's standard deviation.

search_sorted [Base] 
O(log n) Searches for the index of a given element
v in array
vs , sorted with a given comparison function cmp .

shuffle [Base] 
O(n) Shuffles a given array using FisherYates shuffle.

size [Sample.Summary] 
Returns the number of available values.

skewness [Sample.Summary] 
Returns the skewness of the values that have been added or
nan if
the data set is empty.

skewness [Sample] 
O(n) Computes the skewness of a sample, which is a measure of
asymmetry of its distribution.

skewness [Distributions.Features.S]  
skewness_opt [Distributions.Features.Opt]  
spearman [Sample.Correlation] 
O(n log n) Computes Spearman rank correlation coefficient for
two given samples, which is essentially Pearson correlation
calculated for sample ranks.

standard [Distributions.Cauchy] 
CauchyLorentz distribution with 0
location and scale equal to 1.

standard [Distributions.Normal] 
Standard normal distribution with 0
mean and sd equal to 1.

T  
t [Distributions]  
two_sample [Tests.KolmogorovSmirnov] 
Twosample KolmogorovSmirnov test, which evaluates the null
hypothesis, that two independent samples are drawn from the
same continious distribution.

two_sample_independent [Tests.MannWhitneyU] 
MannWhitney U test (also known as MannWhitneyWilcoxon test and
Wilcoxon rank sum test) is a nonparamteric test, which evaluates
the null hypothesis that two independent samples have equal
medians.

two_sample_independent [Tests.T] 
Two sample ttest, which evaluates the null hypothesis that the
difference of means of two independent normally distributed
populations is equal to the specified value.

two_sample_paired [Tests.Sign] 
Dependent samples sign test, which evaluates the null hypothesis
that the median difference between observations from two related
samples is zero.

two_sample_paired [Tests.WilcoxonT] 
Wilcoxon paired signedrank test, which evaluates the null hypothesis
that two related samples have equal medians.

two_sample_paired [Tests.T] 
Paired two sample ttest, which evaluates the null hypothes that
the difference of means of the two paired normally distributed
populations is equal to the specified value.

U  
uniform [Distributions]  
V  
variance [Sample.Summary] 
Returns the variance of the available values or
nan if the
data set is empty.

variance [Sample] 
O(n) Computes unbiased estimate of a sample's variance, also
known as the sample variance, where the denominator is
n  1 .

variance [Distributions.Features.S]  
variance_opt [Distributions.Features.Opt] 