Version: 2.4.1
Date: 2021-10-06
Category: Updates
Text: accommodate changes of the required package 'Rcpp'

Version: 2.4.1
Date: 2021-10-06
Category: New Features
Text: 'emp.transf' has now the option "continuous". If TRUE it provides
        the classical (non-Monte-Carlo) transformation by the empirical
        distribution function, which is a reasonable choice for data of
        continuous distributions.

Version: 2.4.0
Date: 2020-12-10
Category: Updates
Text: extended/updated documentation

Version: 2.4.0
Date: 2020-12-10
Category: Updates
Text: adaptation to stricter checks of R submissions

Version: 2.4.0
Date: 2020-12-10
Category: Updates
Text: speedup of 'pearson_approx', 'multivariance.test' and some more

Version: 2.4.0
Date: 2020-12-10
Category: New Features
Text: 'multivariance.test' has now the p-value option "pearson_unif"
        for fast tests with precalculated paramters in the case of
        univariate unifomly distributed marginals, e.g. given by
        copulas

Version: 2.4.0
Date: 2020-12-10
Category: New Features
Text: 'Mcor' is an alias for 'multicorrelation'

Version: 2.4.0
Date: 2020-12-10
Category: New Features
Text: 'CMcor' is an alias for 'copula.multicorrelation'

Version: 2.4.0
Date: 2020-12-10
Category: Changes in version 2.X.X
Text:

Version: 2.3.0
Date: 2020-04-23
Category: Changes
Text: 'multicorrelation' the default options and available arguments
        have changed.

Version: 2.3.0
Date: 2020-04-23
Category: Changes
Text: 'multivariance.test' uses now the fast and approximately sharp
        'pearson_approx' as default for the p-value approximation,
        instead of the very fast and conservative 'distribution_free'.

Version: 2.3.0
Date: 2020-04-23
Category: New Features
Text: bias corrected estimators are now implemented (and standard) in
        'multicorrelation'

Version: 2.3.0
Date: 2020-04-23
Category: New Features
Text: functions using the "copula version of multivariance" are now
        included: 'emp.transf' Monte Carlo empirical transform,
        'copula.multivariance' copula multivariance,
        'copula.multicorrelation' copula multicorrelation,
        'copula.multicorrelation.test' tests for independence based on
        copula multivariance. Formally these act just alias for the
        standard functions applied to 'emp.transf' of the data.

Version: 2.3.0
Date: 2020-04-23
Category: New Features
Text: 'coins' has now an option 'type' which allows to switch the type
        of events considered.

Version: 2.3.0
Date: 2020-04-23
Category: Updates
Text: Some basic input checks

Version: 2.3.0
Date: 2020-04-23
Category: Updates
Text: documentation

Version: 2.3.0
Date: 2020-04-23
Category: Updates
Text: 'multicorrelation' provides for special cases now a more detailed
        error description

Version: 2.3.0
Date: 2020-04-23
Category: Outdated
Text: the function 'independence.test' is marked as depreciated,
        instead use: 'multivariance.test' as a general interface

Version: 2.2.0
Date: 2019-06-18
Category: New Features
Text: 'dependence.structure' has now a more detailed 'verbose' output.
        It provides also directly an estimate of the type I error for
        the detected structure. Moreover, the detection can now also be
        based on resampling ("type = 'resample'"), Pearson's
        approximation ("type = 'pearson_approx'") or a consistent
        estimator ("type = 'consistent'"). Instead of the clustered
        dependence structure also the full dependence structure
        ("structure.type = 'full'") can be detected.

Version: 2.2.0
Date: 2019-06-18
Category: New Features
Text: 'layout_on_circles' provides a special layout for dependence
        structure graphs. The variables are placed on an outer circle
        and the dependency nodes are placed on an inner circle. This
        seems in particular useful for the sometimes overwhelming full
        dependence structure.

Version: 2.2.0
Date: 2019-06-18
Category: New Features
Text: 'pearson.pvalue' allows now the option "type = 'all'" for
        simultaneous p-value computations of multivariance, 2-,
        3-multivariance and total multivariance

Version: 2.2.0
Date: 2019-06-18
Category: New Features
Text: The moment based tail estimate for positive Gaussian quadratic
        forms 'pearson.qf' has been extended, using the argument
        "verbose=TRUE" a warning is given if the data had to be
        sanitized.

Version: 2.2.0
Date: 2019-06-18
Category: Fixed
Text: when using the 'vec' argument in 'resample.multivariance' the
        resampled values are now always compared to the correct
        multivariance (using the same 'vec') - this also fixes the
        resampling tests in this setting.

Version: 2.2.0
Date: 2019-06-18
Category: Fixed
Text: 'multivariances.all' returned an overexcited warning in some
        special cases (in R 3.6.0). Moreover, due to different
        implementations multivariance and 2-multivariance could differ
        (within tolerance) in the case of 2 variables, now they return
        in this case the same value to avoid confusion. Similarly for
        multivariance and 3-multivariance in the case of 3 variables.

Version: 2.2.0
Date: 2019-06-18
Category: Updated
Text: updates in 'dependence.structure', 'find.cluster', 'clean.graph'

Version: 2.2.0
Date: 2019-06-18
Category: Updated
Text: further speed improvements (in Pearson's approximation)

Version: 2.2.0
Date: 2019-06-18
Category: Updated
Text: documentation

Version: 2.1.0
Date: 2019-03-19
Category: New Features
Text: 'sample.cols' and 'sample.cdms' have now the option "incl.first"
        to select if the first component should also be resampled. The
        resampling of the first component is not necessary for the
        methods here, but it might be useful in other cases. Moreover,
        now using both methods (started with the same seed and
        parameter) yield the same results.

Version: 2.1.0
Date: 2019-03-19
Category: New Features
Text: When using Pearson's approximation (e.g. in 'test.multivariance')
        for samples with constant random variables, now (besides the
        warning that constants are always independent) also a proper
        p-value approximation is computed.

Version: 2.1.0
Date: 2019-03-19
Category: Updated
Text: improved documentation

Version: 2.1.0
Date: 2019-03-19
Category: Fixed
Text: 'multivariances.all' produced an error if x was a list and vec
        contained NA.

Version: 2.0.0
Date: 2019-02-06
Category: New Features
Text: new function 'multivariance.test' which provides all
        multivariance related tests - providing a unified interface
        with return values as they are common for tests in R, in
        particular, the p.value and the value of the test statistic.
        The return value is of class "htest" (as it is standard for
        other hypothesis tests, e.g. ks.test, t.test).

Version: 2.0.0
Date: 2019-02-06
Category: New Features
Text: 'cdm' has now the argument "external.dm.fun" which can be used to
        pass an external function for the computation of the distance
        matrix (allowing major speed ups for non standard distances)

Version: 2.0.0
Date: 2019-02-06
Category: New Features
Text: 'multivariances.all' has now named return values

Version: 2.0.0
Date: 2019-02-06
Category: New Features
Text: 'resample.multivariance' works now also with 'type="all"', for
        simultaneous computation of p.values of multivariance,
        total-multivariance, 2-multivariance and 3-multivariance

Version: 2.0.0
Date: 2019-02-06
Category: New Features
Text: 'multicorrelation' computes now various types of
        multicorrelations.

Version: 2.0.0
Date: 2019-02-06
Category: New Features
Text: 'multivariance.timing' provides methods for detailed estimation
        of the computation time, which might be useful e.g. when
        planing simulation studies.

Version: 2.0.0
Date: 2019-02-06
Category: Changes
Text: 'multicorrelation' has now different defaults and new arguments.

Version: 2.0.0
Date: 2019-02-06
Category: Changes
Text: the centered distance matrices are now stored in a list rather
        than a 3-dim array. Thus the return value of 'cdms' was
        changed, and correspondingly the arguments of all
        '*.multivariance' functions.

Version: 2.0.0
Date: 2019-02-06
Category: Updated
Text: major speedup

Version: 2.0.0
Date: 2019-02-06
Category: Updated
Text: 'multivariance.pvalue' accepts and returns NA and NaN

Version: 2.0.0
Date: 2019-02-06
Category: Updated
Text: 'm.multivariance' returns NA when 3-multivariance is used for
        only 2 variables.

Version: 2.0.0
Date: 2019-02-06
Category: Fixed
Text: 'pearson.pvalue' partially ignored the option "type". It always
        used the test statistic of multivariance, despite the fact the
        parameters were computed for the given "type".

Version: 2.0.0
Date: 2019-02-06
Category: Fixed
Text: the option "verbose" in 'dependence.structure' now works as
        expected

Version: 1.2.1
Date: 2019-01-04
Category: Updates
Text: updated references

Version: 1.2.1
Date: 2019-01-04
Category: Updates
Text: various typos corrected

Version: 1.2.0
Date: 2018-09-13
Category: New Features
Text: 'independence.test' is now also implemented with type
        "pearson_approx". Providing the fast p-value approximation
        developed in <arXiv:1808.07280>. For this also the functions
        'pearson.qf' (a Gaussian quadratic form estimate based on mean,
        variance and skewness) and 'pearson.pvalue' (the corresponding
        p-value estimate based on new moment estimators) are
        introduced.

Version: 1.2.0
Date: 2018-09-13
Category: New Features
Text: In "cmd" one can now explicitly specify the use of "isotropic"
        continuous negative definite functions. This speeds up the
        calculation for this case by a factor of about 100.

Version: 1.2.0
Date: 2018-09-13
Category: Fixed
Text: the option "squared" works now also for multivariance with option
        "correlation=TRUE".

Version: 1.2.0
Date: 2018-09-13
Category: Fixed
Text: 'multivariances.all' returns NA for 3-multivariance if only two
        variables are given.

Version: 1.2.0
Date: 2018-09-13
Category: Updates
Text: speed up of various functions

Version: 1.2.0
Date: 2018-09-13
Category: Updates
Text: various typos corrected

Version: 1.1.0
Date: 2018-01-10
Category: New Features
Text: 'm.multivariance' a function to calculate the m-multivariance

Version: 1.1.0
Date: 2018-01-10
Category: New Features
Text: 'multivariances.all' a function to calculate
        standard/total/m-multivariance simultaneously

Version: 1.1.0
Date: 2018-01-10
Category: New Features
Text: 'resample.multivariance' implements the resampling method which
        can be used to get less conservative tests than the
        distribution-free methods

Version: 1.1.0
Date: 2018-01-10
Category: New Features
Text: 'dependence.structure' a function to generate a graphical model
        of the dependence structure

Version: 1.1.0
Date: 2018-01-10
Category: New Features
Text: various examples of the use of 'dependence.structure'

Version: 1.1.0
Date: 2018-01-10
Category: Changes
Text: The standard output of 'multivariance' is now (distance
        multivariance squared) scaled by the sample size. Use 'Nscale =
        FALSE' to get the value without this scaling. The reason for
        this was twofold: 1. it is now the same setting as for
        'total.multivariance'. 2. This is the only value which can
        (roughly) be interpreted without further calculations.

Version: 1.1.0
Date: 2018-01-10
Category: Updates
Text: improved documentation. In particular, it is now clearly stated
        that the squared values are the standard output of
        'multivariance' and 'total.multivariance'

Version: 1.1.0
Date: 2018-01-10
Category: Updates
Text: some speed up

Version: 1.0.5
Date: 2017-11-02
Category: Details
Text: Initial public release