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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.

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Version

Install

install.packages('bsplinePsd')

Monthly Downloads

34

Version

0.6.0

License

GPL (>= 3)

Maintainer

Matthew C. Edwards

Last Published

October 18th, 2018

Functions in bsplinePsd (0.6.0)

densityMixture

C++ function for building a density mixture, given mixture weights and functions.
uniformmax

Help function: Uniform maximum
unrollPsd

C++ help function to redundantly roll out a PSD to length n
bsplinePsd-package

Bayesian Nonparametric Spectral Density Estimation Using B-Spline Priors
lprior

Unnormalised log joint prior
gibbs_bspline

Metropolis-within-Gibbs sampler for spectral inference of a stationary time series using a B-spline prior
lpost

Unnormalised log posterior
logfuller

Help function: Fuller Logarithm
mixtureWeight

C++ function for computing mixture weights of Bernstein-Mixtures given the probabilities p, values w, and degree k.
pFromV

C++ function for generating p from v in Stick Breaking DP representation
dbspline

Generate a B-spline density basis of any degree
llike

log Whittle likelihood
psd_arma

Analytical spectral density for mean-centred ARMA(p,q) model
plot.psd

Plot method for psd class
qpsd

Compute unnormalised PSD using random mixture of B-splines
fast_ft

FFT: Compute F_n X_n with the real-valued Fourier matrix F_n