# Calculating the accuracy of hierarchical estimation

L.W.G. Strijbosch, J.J.A. Moors

Research output: Contribution to journalArticleScientificpeer-review

### Abstract

Instead of forecasting demand for individual items separately, hierarchical forecasting is often used: total demand is forecasted for a collection of items; this total forecast then is broken down to produce the desired individual demand forecasts. To allow analytical analyses, we considered in a previous paper the simpler problem of hierarchical estimation. So from a random sample of demand periods, we estimated both the total demand for a number of items and the fraction of this total that an individual item takes; multiplying these two quantities gives the hierarchical estimate for each individual demand. From the joint distribution of the individual demands, we here present a fast and general method for finding the bias and variance of the corresponding hierarchical estimator. The method is compared with our previous results and two new applications are added.
Original language English 303-315 IMA Journal of Management Mathematics 21 3 Published - 2010

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Forecast
Demand Forecasting
Joint Distribution
Forecasting
Demand
Estimator
Estimate
Demand forecasting
Hierarchical forecasting
Demand forecast
Joint distribution

### Cite this

Strijbosch, L. W. G., & Moors, J. J. A. (2010). Calculating the accuracy of hierarchical estimation. IMA Journal of Management Mathematics, 21(3), 303-315.
Strijbosch, L.W.G. ; Moors, J.J.A. / Calculating the accuracy of hierarchical estimation. In: IMA Journal of Management Mathematics. 2010 ; Vol. 21, No. 3. pp. 303-315.
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Strijbosch, LWG & Moors, JJA 2010, 'Calculating the accuracy of hierarchical estimation', IMA Journal of Management Mathematics, vol. 21, no. 3, pp. 303-315.

Calculating the accuracy of hierarchical estimation. / Strijbosch, L.W.G.; Moors, J.J.A.

In: IMA Journal of Management Mathematics, Vol. 21, No. 3, 2010, p. 303-315.

Research output: Contribution to journalArticleScientificpeer-review

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T1 - Calculating the accuracy of hierarchical estimation

AU - Strijbosch, L.W.G.

AU - Moors, J.J.A.

PY - 2010

Y1 - 2010

N2 - Instead of forecasting demand for individual items separately, hierarchical forecasting is often used: total demand is forecasted for a collection of items; this total forecast then is broken down to produce the desired individual demand forecasts. To allow analytical analyses, we considered in a previous paper the simpler problem of hierarchical estimation. So from a random sample of demand periods, we estimated both the total demand for a number of items and the fraction of this total that an individual item takes; multiplying these two quantities gives the hierarchical estimate for each individual demand. From the joint distribution of the individual demands, we here present a fast and general method for finding the bias and variance of the corresponding hierarchical estimator. The method is compared with our previous results and two new applications are added.

AB - Instead of forecasting demand for individual items separately, hierarchical forecasting is often used: total demand is forecasted for a collection of items; this total forecast then is broken down to produce the desired individual demand forecasts. To allow analytical analyses, we considered in a previous paper the simpler problem of hierarchical estimation. So from a random sample of demand periods, we estimated both the total demand for a number of items and the fraction of this total that an individual item takes; multiplying these two quantities gives the hierarchical estimate for each individual demand. From the joint distribution of the individual demands, we here present a fast and general method for finding the bias and variance of the corresponding hierarchical estimator. The method is compared with our previous results and two new applications are added.

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EP - 315

JO - IMA Journal of Management Mathematics

JF - IMA Journal of Management Mathematics

SN - 1471-678X

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