Linearize the series with a fractional airline model

Usage

fractionalAirlineEstimation(
  y,
  periods,
  x = NULL,
  ndiff = 2,
  ar = FALSE,
  mean = FALSE,
  outliers = NULL,
  criticalValue = 6,
  precision = 1e-12,
  approximateHessian = FALSE,
  nfcasts = 0,
  log = FALSE,
  y_time = NULL
)

Arguments

y: input time series.
periods: vector of periods values of the seasonal component, any positive real numbers.
x: matrix of user-defined regression variables (see rjd3toolkit for building calendar regressors).
mean: add constant mean to y after differencing.
outliers: type of outliers sub vector of c("AO","LS","WO")
criticalValue: Critical value for automatic outlier detection
precision: Precision of the likelihood
approximateHessian: Compute approximate hessian (based on the optimizing procedure)
nfcasts: Number of forecasts
log: a logical
y_time: vector of times at which `y` is indexed