- User level changes
- more argument types supported in bcdcor, dcov, dcor, pdcov, pdcor functions and tests
- mutualIndep.test test of mutual independence (new)
- is.dmatrix() utility function is now exported
- calc_dist() (Rcpp export) is exported

- Internal changes
- C functions dCOVtest() and dCOV() simplified, now expect distance matrices, exponent handled in R
- unused C function dCovtest() removed
- .arg2dist.matrix() utility to convert valid types of args to distance matrices

- update email address in docs

- bug fix in normal.test
- pdcor.test now gives p.value=NA in degenerate case
- DCOR is deprecated; use dcor or dcov

- User level changes:
- Poisson goodness-of-fit tests
- EVnormal (data) issue fixed
- gsl package required

- Internal changes
- mvnorm.e: use gsl::hyperg_1F1

- poisMstat in energy.c moved to Rcpp poisMstat.cpp

- mvnorm.e: use gsl::hyperg_1F1

- User level changes:
- dcorT.test replaces dcor.ttest, now deprecated.
- dcorT replaces dcor.t, now deprecated.
- edist method “discoF” removed

- Internal changes
- BCDCOR function (used in the high dim. dcorT test) has been revised.
- edist method “discoB” correction
- changes for compatibility with R 4.0.0

- User level changes:
- normal.test (new) implements the energy test of univariate normality based on the null limit distribution for the composite hypothesis (estimated parameters).
- dataset EVnormal (new) of eigenvalues for energy test of normality.
- mvnorm.test replaces mvnorm.etest, and mvnorm.etest now is a wrapper for mvnorm.test.

- User level changes:
- kgroups: (new) implements energy clustering for a specified number k classes by energy distance criterion, analogous to the k classes of the k-means algorithm.
- dcov2d and dcor2d: (new) O(n log n) methods to compute the U or V statistics for real x and y
- sortrank() function added (a utility)

- Internal changes:
- B-tree.cpp: Btree_sum and other internal functions implement binary tree search for faster O(n log n) calculation of paired distances in dcov2d
- kgroups.cpp: Rcpp implementation of k-groups algorithm
- energy.hclust implementation: replaced C++ code with call to stats::hclust; since R > 3.0.3 it is now equivalent for alpha = 1 with method = “ward.D”. Input and return value unchanged except heights from hclust are half.

- User level changes
- disco: handle the case when the user argument x is dist with conflicting argument distance=FALSE
- dcor.t and dcor.ttest: handle the cases when class of argument x or y conflicts with the distance argument
- Split manual page of dcovU into two files.
- indep.etest and indep.e removed now Defunct (were Deprecated since Version 1.1-0, 2008-04-07; replaced by indep.test).

- Internal changes
- BCDCOR: handle the cases when class of argument x or y conflicts with the distance argument

- User level changes
- Provided new dcor.test function, similar to dcov.test but using the distance correlation as the test statistic.
- Number of replicates R for Monte Carlo and permutation tests now matches the argument of the boot::boot function (no default value, user must specify).
- If user runs a test with 0 replicates, p-value printed is NA

- Internal changes
- energy_init.c added for registering routines

- Partial Distance Correlation statistics and tests added
- pdcov, pdcor, pdcov.test, pdcor.test
- dcovU: unbiased estimator of distance covariance
- bcdcor: bias corrected distance correlation
- Ucenter, Dcenter, U_center, D_center: double-centering and U-centering utilities
- U_product: inner product in U-centered Hilbert space

- updated NAMESPACE and DESCRIPTION imports, etc.
- revised package Title and Description in DESCRIPTION
- package now links to Rcpp
- mvnorm c code ported to c++ (mvnorm.cpp); corresponding changes in Emvnorm.R
- syntax for bcdcor: “distance” argument removed, now argument can optionally be a dist object
- syntax for energy.hclust: first argument must now be a dist object
- default number of replicates R in tests: for all tests, R now defaults to 0 or R has no default value.

- inserted GetRNGstate() .. PutRNGState around repl. loop in dcov.c.

- replace Depends with Imports in DESCRIPTION file

- implementation of high-dim distance correlation t-test introduced in JMVA Volume 117, pp. 193-213 (2013).
- new functions dcor.t, dcor.ttest in dcorT.R
- minor changes to tidy other code in dcov.R
- removed unused internal function .dcov.test

- NAMESPACE: insert UseDynLib; remove zzz.R, .First.Lib()

- NAMESPACE added.
- (dcov.c, Eindep.c) Unused N was removed.
- (dcov.c) In case dcov=0, bypass the unnecessary loop that generates replicates (in dCOVtest and dCovTest). In this case dcor=0 and test is not significant. (dcov=0 if one of the samples is constant.)
- (Eqdist.R) in eqdist.e and eqdist.etest, method=“disco” is replaced by two options: “discoB” (between sample components) and “discoF” (disco F ratio).
- (disco.R) Added disco.between and internal functions that compute the disco between-sample component and corresponding test.
- (utilities.c) In permute function replaced rand_unif with runif.
- (energy.c) In ksampleEtest the pval computation changed from ek/B to (ek+1)/(B+1) as it should be for a permutation test, and unneeded int* n removed.

In distance correlation, distance covariance functions (dcov, dcor, DCOR) and dcov.test, arguments x and y can now optionally be distance objects (result of dist function or as.dist). Matrices x and y will always be treated as data.

Functions in dcov.c and utilities.c were modified to support arguments that are distances rather than data. In utilities.c the index_distance function changed. In dcov.c there are many changes. Most importantly for the exported objects, there is now an extra required parameter in the dims argument passed from R. In dCOVtest dims must be a vector c(n, p, q, dst, R) where n is sample size, p and q are dimensions of x and y, dst is logical (TRUE if distances) and R is number of replicates. For dCOV dims must be c(n, p, q, dst).

- disco (distance components) added for one-way layout.
- A method argument was added to ksample.e, eqdist.e, and eqdist.etest, method = c(“original”, “disco”).
- A method argument was added to edist, which summarizes cluster distances in a table: method = c(“cluster”,“discoB”,“discoF”))