get_peen_ts: Get time-series forecast using persistence ensemble (PeEn)...

In kdayday/ppnwp: Post-Process Numerical Weather Prediction ensembles

Description

This method enforces a set of training data of length training_window; if there is missing data, it continues back through the historical record until it has a full set (unless it runs out of data)

Usage

get_peen_ts(issue, t_idx_series, telemetry, sun_up, site, max_power,
  metadata)

Arguments

issue	A time stamp
t_idx_series	Series of time indices to forecast, relative to the telemetry time indices
telemetry	A list of data=vector of telemetry and validtime=vector of POSIXct times
sun_up	A vector of booleans, indexed by telemetry valid times
site	String, site name
max_power	Site's AC power rating or maximum load
metadata	A data.frame of forecast parameters

Value

A ts_forecast object

See Also

Other ts_training_forecast: get_binned_ts, get_bma_ts, get_chpeen_ts, get_clim_ts, get_emos_ts, get_raw_ts

kdayday/ppnwp documentation built on Oct. 8, 2020, 8:47 a.m.