NLPwavelet-package: Bayesian Wavelet Analysis Using Non-local Priors

In NLPwavelet: Bayesian Wavelet Analysis Using Non-Local Priors

Bayesian Wavelet Analysis Using Non-local Priors

Description

Performs Bayesian wavelet analysis using individual non-local priors as described in Sanyal & Ferreira (2017) <DOI:10.1007/s13571-016-0129-3> and non-local prior mixtures as described in Sanyal (2025) <DOI:10.48550/arXiv.2501.18134>.

Details

The main function is BNLPWA, which has arguments for specifying analysis using individual non-local priors or non-local prior mixtures and various hyperparameter specifications for the wavelet coefficients and scale parameters of the non-local priors. See the manual of BNLPWA for examples.

Author(s)

Nilotpal Sanyal <[e-mail]>

Maintainer: Nilotpal Sanyal <[e-mail]>

References

Sanyal, Nilotpal. "Nonlocal prior mixture-based Bayesian wavelet regression." arXiv preprint arXiv:2501.18134 (2025).

Sanyal, Nilotpal, and Marco AR Ferreira. "Bayesian wavelet analysis using nonlocal priors with an application to FMRI analysis." Sankhya B 79.2 (2017): 361-388.

NLPwavelet documentation built on April 11, 2025, 6:09 p.m.