var_generator: PRISM regressors generator

In PRISM.forecast: Penalized Regression with Inferred Seasonality Module - Forecasting Unemployment Initial Claims using 'Google Trends' Data

Description

Stage 1 of PRISM. The function generates prism seasonal components and seasonally adjusted lag components.

Usage

var_generator(
  data,
  data.early,
  stl = TRUE,
  n.lag = 1:52,
  s.window = 52,
  n.history = 700
)

Arguments

data	time series of interest as xts, last element can be NA.
data.early	historical time series of response variable before Google Trend data is available. (e.g., unemployment initial claim prior to 2004)
stl	if TRUE, use STL seasonal decomposition; if FALSE, use classic additive seasonal decomposition.
n.lag	the number of lags to be used as regressor in Stage 2 of PRISM (by default = 1:52 for weekly data)
s.window	seasonality span (by default = 52 for weekly data)
n.history	training period for seasonal decomposition. (by default = 700 wks)

Value

A list of following named objects

• y.lags seasonally adjusted components, z_lag, and seasonal components, s_lag.

PRISM.forecast documentation built on Oct. 23, 2020, 7:34 p.m.