cal_features {seer}

Calculate features for new time series instances

Description

Computes relevant time series features before applying them to the model

Usage

cal_features(
  tslist,
  seasonal = FALSE,
  m = 1,
  lagmax = 2L,
  database,
  h,
  highfreq
)

Arguments

tslist

a list of univariate time series

seasonal

if FALSE, restricts to features suitable for non-seasonal data

m

frequency of the time series or minimum frequency in the case of msts objects

lagmax

maximum lag at which to calculate the acf (quarterly series-5L, monthly-13L, weekly-53L, daily-8L, hourly-25L)

database

whether the time series is from mcomp or other

h

forecast horizon

highfreq

whether the time series is weekly, daily or hourly

Value

dataframe: each column represent a feature and each row represent a time series

Author(s)

Thiyanga Talagala