Tools for fitting and simulating mixtures of Watson distributions. 
             The random sampling scheme of the package offers two sampling 
             algorithms that are based of the results of Sablica, Hornik and Leydold (2022)
             <doi:10.1080/10618600.2024.2416521>.
             What is more, the package offers a smart tool to combine these two methods,
             and based on the selected parameters, it approximates the relative sampling
             speed for both methods and picks the faster one. In addition, the package
             offers a fitting function for the mixtures of Watson distribution, that
             uses the expectation-maximization (EM) algorithm. Special features are
             the possibility to use multiple variants of the E-step and M-step,
             sparse matrices for the data representation and state of the art methods
             for numerical evaluation of needed special functions using the results of
             Sablica and Hornik (2022) <doi:10.1090/mcom/3690> and 
             Sablica and Hornik (2024) <doi:10.1016/j.jmaa.2024.128262>.

Efficiently read and write Waveform (WAV) audio files <https://en.wikipedia.org/wiki/WAV>. 
  Support for unsigned 8 bit Pulse-code modulation (PCM), signed 12, 16, 24 and 32 bit 
  PCM and other encodings.

Computes Bayesian wavelet shrinkage credible intervals for
	nonparametric regression.
	The method uses cumulants to derive Bayesian credible intervals for
	wavelet regression estimates.
	The first four cumulants of the posterior distribution of the
	estimates are expressed in terms of the observed data and integer
	powers of the mother wavelet functions.
	These powers are closely approximated by linear combinations of
	wavelet scaling functions at an appropriate finer scale.
	Hence, a suitable modification of the discrete wavelet transform allows
	the posterior cumulants to be found efficiently for any data set.
	Johnson transformations then yield the credible intervals themselves.
	Barber, S., Nason, G.P. and Silverman, B.W. (2002)
	<doi:10.1111/1467-9868.00332>.