README.md

In bsplinePsd: Bayesian Nonparametric Spectral Density Estimation Using B-Spline Priors

Why should I use bsplinePsd?

This package allows the user to flexibly estimate the spectral density of a stationary time series using a Bayesian nonparametric B-spline prior (of any degree). It works particularly well for complicated spectral structures (compared to the Bernstein polynomial prior).

How do I use bsplinePsd?

The primary function gibbs_bspline is straightforward to use. Most of the arguments are defaults (i.e., a noninformative prior). All you need to do is input a numeric vector (your time series), the number of iterations to run the MCMC algorithm for, and the amount of burn-in.

How do I get bsplinePsd?

Download from CRAN. Use install.packages("bsplinePsd") in R.

bsplinePsd documentation built on May 2, 2019, 5:56 a.m.