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. |