Learn R Programming

gtop (version 0.2.0)

gtop: Reconciliate individual predictions using GTOP

Description

Uses a Game Theory approach to reconciliate hierarchical time series predicitons

Usage

gtop(preds_indiv, pred_total, weights_indiv, weight_total, bounds_indiv, solver = "quad")

Arguments

preds_indiv
vector contains the individual predictions
pred_total
prediction for the sum of individuals
weights_indiv
vector, contains the weights of the individuals
weight_total
weight of the total
bounds_indiv
vector, contains the bounds of the individuals
solver
string, use quadratic programming (quad) or Lasso-like solvers (lasso)

Value

A list with
  • pred_indivs the reconciliated predictions for the individuals and the total,
  • solution the solution to the associate minimisation problem.

Details

In hierarchical time series forecasts, one predicts individuals quantities and a global quantity. There exists a contraint that matches the sum of the individual quantities to the global quantity. However, forecasting models don't take into account this constraint. With GTOP you can reconciliate the individual and global quantities in order to match the aggregate consistency contraint.

Examples

Run this code
K <- 5
indiv <- rep(0, K)
total <- 1
gtop(preds_indiv   = indiv,
     pred_total = total,
     weights_indiv = rep(1, K),
     weight_total = 2,
     bounds_indiv  = rep(1 / K, K))

Run the code above in your browser using DataLab