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R in a Nutshell, 2nd Edition by Joseph Adler

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stats

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

Functions

FunctionDescription
AICGeneric 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 + knpar, where npar 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).
ARMAacfComputes the theoretical autocorrelation function or partial autocorrelation function for an autoregressive moving average (ARMA) process.
ARMAtoMAConverts an ARMA process to an infinite moving average (MA) process.
Box.testComputes 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.
CSets the "contrasts" attribute for the factor.
DComputes derivatives of simple expressions, symbolically.
GammaFamily object for Gamma distributions (used by functions such as glm).
HoltWintersComputes Holt-Winters filtering of a given time series. Unknown parameters are determined by minimizing the squared prediction error.
IQRComputes the interquartile range of the x values.
KalmanForecast, KalmanLike, KalmanRun, KalmanSmoothUse Kalman filtering to find the (Gaussian) log-likelihood, or for forecasting or smoothing.
NLSstAsymptotic ...

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