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. |