| 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. |