This package contains functions to perform a wide variety of statistical analyses.

Function | Description |
---|---|

AIC | Generic function for calculating the Akaike
information criterion for one or several fitted model objects
for which a log-likelihood value can be obtained, according to
the formula −2 ∗ log-likelihood + k ∗
n_{par}, where
n_{par} represents the
number of parameters in the fitted model, and k
= 2 for the usual AIC, or k =
log(n) (n is the
number of observations) for the so-called Bayesian information
criterion (BIC) or Schwarz’s Bayesian criterion (SBC). |

ARMAacf | Computes the theoretical autocorrelation function or partial autocorrelation function for an autoregressive moving average (ARMA) process. |

ARMAtoMA | Converts an ARMA process to an infinite moving average (MA) process. |

Box.test | Computes the Box-Pierce or Ljung-Box test statistic for examining the null hypothesis of independence in a given time series. These are sometimes known as “portmanteau” tests. |

C | Sets the `"contrasts"`
attribute for the factor. |

D | Computes derivatives of simple expressions, symbolically. |

Gamma | Family object for Gamma distributions (used by functions
such as `glm` ). |

HoltWinters | Computes Holt-Winters filtering of a given time series. Unknown parameters are determined by minimizing the squared prediction error. |

IQR | Computes the interquartile range of the `x` values. |

KalmanForecast, KalmanLike, KalmanRun, KalmanSmooth | Use Kalman filtering to find the (Gaussian) log-likelihood, or for forecasting or smoothing. |

NLSstAsymptotic ... |

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