pfa.ets: PFA Formatting of Fitted Exponential Smoothing State Space...

In aurelius: Generates PFA Documents from R Code and Optionally Runs Them

Description

This function takes an Exponential smoothing state space model created using the ets() function from the forecast package and returns a list-of-lists representing in valid PFA document that could be used for scoring.

Usage

## S3 method for class 'ets'
pfa(object, name = NULL, version = NULL, doc = NULL,
  metadata = NULL, randseed = NULL, options = NULL, cycle_reset = TRUE,
  ...)

Arguments

object	an object of class "ets"
name	a character which is an optional name for the scoring engine
version	an integer which is sequential version number for the model
doc	a character which is documentation string for archival purposes
metadata	a list of strings that is computer-readable documentation for archival purposes
randseed	a integer which is a global seed used to generate all random numbers. Multiple scoring engines derived from the same PFA file have different seeds generated from the global one
options	a list with value types depending on option name Initialization or runtime options to customize implementation (e.g. optimization switches). May be overridden or ignored by PFA consumer
cycle_reset	a logical indicating whether to reset the state back to the last point of the trained model before forecasting or to continue cycling forward through trend and seasonality with every new call to the engine. The default is TRUE so that repeated calls yield the same forecast as repeated calls to forecast.
...	additional arguments affecting the PFA produced

Value

a list of lists that compose valid PFA document

Source

pfa_config.R avro_typemap.R avro.R pfa_cellpool.R pfa_expr.R pfa_utils.R

See Also

ets extract_params.ets

Examples

model <- forecast::ets(USAccDeaths, model="ZZZ")
model_as_pfa <- pfa(model)

aurelius documentation built on May 2, 2019, 3:43 a.m.