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. |