R in a Nutshell

stats

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

Functions

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 ∗ npar, 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).
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 ...