R: Bayesian Spectral Inference

# Bayesian Spectral Inference

## Documentation for package ‘bspec’ version 1.6

- DESCRIPTION file

## Help Pages

bspec-package | Bayesian Spectral Inference
acf | Posterior autocovariances
acf.bspec | Posterior autocovariances
acf.default | Posterior autocovariances
bspec | Computing the spectrum's posterior distribution
bspec.default | Computing the spectrum's posterior distribution
cosinewindow | Compute windowing functions for spectral time series analysis.
dposterior | Prior, likelihood and posterior
dposterior.bspec | Prior, likelihood and posterior
dprior | Prior, likelihood and posterior
dprior.bspec | Prior, likelihood and posterior
empiricalSpectrum | Compute the "empirical" spectrum of a time series.
expectation | Expectations and variances of distributions
expectation.bspec | Expectations and variances of distributions
expectation.bspecACF | Expectations and variances of distributions
hammingwindow | Compute windowing functions for spectral time series analysis.
hannwindow | Compute windowing functions for spectral time series analysis.
is.bspec | Computing the spectrum's posterior distribution
is.bspecACF | Posterior autocovariances
kaiserwindow | Compute windowing functions for spectral time series analysis.
likelihood | Prior, likelihood and posterior
likelihood.bspec | Prior, likelihood and posterior
marglikelihood | Prior, likelihood and posterior
marglikelihood.bspec | Prior, likelihood and posterior
matchedfilter | Filter a noisy time series for a signal of given shape
one.sided | Conversion between one- and two-sided spectra
one.sided.bspec | Conversion between one- and two-sided spectra
plot.bspec | Computing the spectrum's posterior distribution
plot.bspecACF | Posterior autocovariances
ppsample | Posterior predictive sampling
ppsample.bspec | Posterior predictive sampling
print.bspec | Computing the spectrum's posterior distribution
print.bspecACF | Posterior autocovariances
quantile.bspec | Quantiles of the posterior spectrum
sample | Posterior sampling
sample.bspec | Posterior sampling
sample.default | Posterior sampling
snr | Compute the signal-to-noise ratio (SNR) of a signal
squarewindow | Compute windowing functions for spectral time series analysis.
studenttfilter | Filter a noisy time series for a signal of given shape
temper | Tempering of (posterior) distributions
temper.bspec | Tempering of (posterior) distributions
temperature | Querying the tempering parameter
temperature.bspec | Querying the tempering parameter
trianglewindow | Compute windowing functions for spectral time series analysis.
tukeywindow | Compute windowing functions for spectral time series analysis.
two.sided | Conversion between one- and two-sided spectra
two.sided.bspec | Conversion between one- and two-sided spectra
variance | Expectations and variances of distributions
variance.bspec | Expectations and variances of distributions
variance.bspecACF | Expectations and variances of distributions
welchPSD | Power spectral density estimation using Welch's method.
welchwindow | Compute windowing functions for spectral time series analysis.