transform_fc_preds: For discrete series, Probability Integral Transform sampling...

In nicholasjclark/mvforecast: Tools to fit, interrogate and forecast multivariate statistical and machine learning timeseries models

Description

For discrete series, Probability Integral Transform sampling maps observations onto a Uniform distribution that is then mapped onto a Gaussian distribution for modelling. This is essentially a copula method where we assume the 'marginal' is a discrete distribution. This function takes an approximately Gaussian forecast object and back-transforms it to the discrete distribution that was originally estimated.

Usage

transform_fc_preds(forecast, orig_y, params)

Arguments

forecast	forecast object containing the approximately Gaussian predictions to be back-transformed
orig_y	vector containing the original untransformed y values
params	the original estimated discrete distribution parameter(s). If the original was Negative Binomially distributed, params will be a list of length 2.

Value

A forecast containing the estimated discrete predictions

nicholasjclark/mvforecast documentation built on Dec. 22, 2021, 2:11 a.m.