karma.fit: Fit ARIMA model to univariate time-series. Mostly a wrapper...

In snarf-snarf/karma: Complementary tools for automated time-series machine learning.

Description

Fit ARIMA model to univariate time-series. Mostly a wrapper to 'Arima' function in the 'forecast' package; the difference is that it facilitates fitting fixed term models.

Usage

karma.fit(y, order = c(0, 0, 0), seasonal = c(0, 0, 0), log = F,
  xreg = NULL, fixed = F, stdout = F)

Arguments

y	A univariate time-series vector; type <numeric> or <ts>.
order	Specification of the non-seasonal part of the ARIMA model (see documentation for Arima(), argument 'order').
log	Logarithmic transformation flag; Indicates whether the input series needs to be log-transformed for stationarity; T, F; type <logical>.
xreg	Optional vector or matrix of exogenous regressors; see documentation for Arima(), package 'forecast'.
fixed	Fixed term flag. Indicate whether the fixed term option in Arima() needs to be switched on during model selection; T, F; type <logical>.
stdout	Option to output optimisation diagnostics during local search; <logical>

Value

Object of class "karma.fit"; (extends class "ARIMA" from package 'forecast').

See Also

tseries, forecast

Examples

# Fit and summarise model:
summary(karma.fit(WWWusage, order=list(c(1,2), 1, c(3,4)), fixed=T))
# Using forecast() from package 'forecast':
plot(forecast( karma.fit(WWWusage, order=c(2,1,3), fixed=F) )) 

snarf-snarf/karma documentation built on May 24, 2019, 7:19 a.m.