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S.Sample.correlation, S.Sample.covariance,
S.Correlation.pearson do not allocate temporary arrays.
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Variants of correlation which take two vectors as input are added:
S.Sample.correlation2, S.Sample.covariance2, S.Correlation.pearson2,
S.Correlation.spearman2.
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Contexts for S.Function.indexed, S.Correlation.spearman, S.pairedTTest,
S.Sample.correlation, S.Sample.covariance, reduced.
-
Computation of rSquare in linear regression has special case for case when
data variation is 0.
-
Doctests added.
-
Benchmarks using tasty-bench and tasty-papi added.
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Spurious test failures fixed.
Breaking update. It seriously changes parts of API. It adds new data types for
dealing with estimates, confidence intervals, confidence levels and
p-value. Also API for statistical tests is changed.
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Module Statistis.Types now contains new data types for estimates,
upper/lower bounds, confidence level, and p-value.
CL for representing confidence levelPValue for representing p-valuesEstimate data type moved here from Statistis.Resampling.Bootstrap and
now parametrized by type of error.NormalError — represents normal error.ConfInt — generic confidence intervalUpperLimit,LowerLimit for upper/lower limits.
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New API for statistical tests. Instead of simply return significant/not
significant it returns p-value, test statistics and distribution of test
statistics if it’s available. Tests also return Nothing instead of throwing
error if sample size is not sufficient. Fixes #25.
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Statistics.Tests.Types.TestType data type dropped
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New smart constructors for distributions are added. They return Nothing if
parameters are outside of allowed range.
-
Serialization instances (Show/Read, Binary, ToJSON/FromJSON) for
distributions no longer allows to create data types with invalid
parameters. They will fail to parse. Cached values are not serialized either
so Binary instances changed normal and F-distributions.
Encoding to JSON changed for Normal, F-distribution, and χ²
distributions. However data created using older statistics will be
successfully decoded.
Fixes #59.
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Statistics.Resample.Bootstrap uses new data types for central estimates.
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Function for calculation of confidence intervals for Poisson and binomial
distribution added in Statistics.ConfidenceInt
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Tests of position now allow to ask whether first sample on average larger
than second, second larger than first or whether they differ significantly.
Affects Wilcoxon-T, Mann-Whitney-U, and Student-T tests.
-
API for bootstrap changed. New data types added.
-
Bug fixes for #74, #81, #83, #92, #94
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complCumulative added for many distributions.
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The type classes Mean and Variance are split in two. This is
required for distributions which do not have finite variance or
mean.
-
The S.Sample.KernelDensity module has been renamed, and
completely rewritten to be much more robust. The older module
oversmoothed multi-modal data. (The older module is still
available under the name S.Sample.KernelDensity.Simple).
-
Histogram computation is added, in S.Sample.Histogram.
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Discrete Fourie transform is added, in S.Transform
-
Root finding is added, in S.Math.RootFinding.
-
The complCumulative function is added to the Distribution
class in order to accurately assess probabilities P(X>x) which are
used in one-tailed tests.
-
A stdDev function is added to the Variance class for
distributions.
-
The constructor S.Distribution.normalDistr now takes standard
deviation instead of variance as its parameter.
-
A bug in S.Quantile.weightedAvg is fixed. It produced a wrong
answer if a sample contained only one element.
-
Bugs in quantile estimations for chi-square and gamma distribution
are fixed.
-
Integer overflow in mannWhitneyUCriticalValue is fixed. It
produced incorrect critical values for moderately large
samples. Something around 20 for 32-bit machines and 40 for 64-bit
ones.
-
A bug in mannWhitneyUSignificant is fixed. If either sample was
larger than 20, it produced a completely incorrect answer.
-
One- and two-tailed tests in S.Tests.NonParametric are selected
with sum types instead of Bool.
-
Test results returned as enumeration instead of Bool.
-
Performance improvements for Mann-Whitney U and Wilcoxon tests.
-
Module S.Tests.NonParamtric is split into S.Tests.MannWhitneyU
and S.Tests.WilcoxonT
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sortBy is added to S.Function.
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Mean and variance for gamma distribution are fixed.
-
Much faster cumulative probability functions for Poisson and
hypergeometric distributions.
-
Better density functions for gamma and Poisson distributions.
-
Student-T, Fisher-Snedecor F-distributions and Cauchy-Lorentz
distribution are added.
-
The function S.Function.create is removed. Use generateM from
the vector package instead.
-
Function to perform approximate comparison of doubles is added to
S.Function.Comparison
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Regularized incomplete beta function and its inverse are added to
S.Function
