# gtop: Reconciliate individual predictions using GTOP In gtop: Game-Theoretically OPtimal (GTOP) Reconciliation Method

## Description

Uses a Game Theory approach to reconciliate hierarchical time series predicitons

## Usage

 ```1 2``` ```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`)

## 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.

## Value

A list with

• pred_indivs the reconciliated predictions for the individuals and the total,

• solution the solution to the associate minimisation problem.

## Examples

 ```1 2 3 4 5 6 7 8``` ```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)) ```

### Example output

```Loading required package: hts

Attaching package: 'gtop'

The following object is masked from 'package:hts':

hts

The following object is masked from 'package:stats':

proj

\$preds_indiv
 0.1818182 0.1818182 0.1818182 0.1818182 0.1818182 0.9090909

\$solution
[,1]
[1,] -0.1818182
```

gtop documentation built on May 2, 2019, 6:10 a.m.