New functions (written with Victor Ryan @VictorRyan12 ) :

`EllDistrDerivEst`

: nonparametric estimation of the derivatives of the generator of an elliptical distribution.`EllDistrEst.adapt`

: adaptive nonparametric estimation of the generator of an elliptical distribution.`estim_tilde_AMSE`

: estimate the component of the asymptotic mean-square error (AMSE) of the nonparametric estimator of the elliptical density generator that only depends on the parameter`a`

.

`EllDistrEst`

now works in a vectorized way, where`a`

and/or`h`

are vectors of the same length as the`grid`

on which the estimator is computed. Each value of the grid is then estimated with the corresponding tuning parameters (corresponding element of`a`

and of`h`

).New option

`averaging = "random"`

for the function`KTMatrixEst`

corresponding to the averaging of a random set of entries in the off-diagonal blocks.The output of

`KTMatrixEst`

now has colnames and rownames set to the names if available in`blockStructure`

.

Fixed a bug in

`KTMatrixEst`

(whose output did not have ones on the diagonal, contrary to the documentation).Fixed a bug in

`EllDistrEst`

when the variance matrix is not the identity.

Moving dependence

`Rmpfr`

from Import to Suggest.New dependence: Suggest:

`testthat`

.New dependence: Import:

`kStatistics`

.

- New dependence
`wdm`

instead of`pcaPP`

for fast computation of Kendallâ€™s tau.

Fixed a bug in

`EllDistrEst`

when`mu`

is not zero. (#1, thanks to Rutger van der Spek)`EllDistrEst`

gains two new arguments:`mpfr`

and`precBits`

, that allows to use the package`Rmpfr`

for multiple floating point precision (needed for dimensions larger than 250). (#2, thanks to Rutger van der Spek)New function

`KTMatrixEst`

for fast estimation of Kendallâ€™s tau matrix, potentially under structural assumptions. (#2, thanks to Rutger van der Spek)New dependencies: Import:

`Rmpfr`

,`pbapply`

. Suggest:`mvtnorm`

.

- Completed the documentation about returned values of the exported functions.

- Initial release