### Abstract

Original language | English |
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Place of Publication | Amsterdam |

Publisher | Tinbergen Instituut |

Publication status | Published - 2008 |

### Publication series

Name | Discussion paper TI |
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No. | 08-100/1 |

### Fingerprint

### Cite this

*A K-sample Homogeneity Test based on the Quantification of the p-p Plot*. (Discussion paper TI; No. 08-100/1). Amsterdam: Tinbergen Instituut.

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**A K-sample Homogeneity Test based on the Quantification of the p-p Plot.** / Hinloopen, Jeroen; Wagenvoort, Rien; van Marrewijk, Charles.

Research output: Working paper › Professional

TY - UNPB

T1 - A K-sample Homogeneity Test based on the Quantification of the p-p Plot

AU - Hinloopen, Jeroen

AU - Wagenvoort, Rien

AU - van Marrewijk, Charles

PY - 2008

Y1 - 2008

N2 - We propose a quantification of the p-p plot that assigns equal weight to all distances between the respective distributions: the surface between the p-p plot and the diagonal. This surface is labelled the Harmonic Weighted Mass (HWM) index. We introduce the diagonal-deviation (d-d) plot that allows the index to be computed exactly under all circumstances. For two balanced samples absent ties the finite sample distribution of the HWM index is derived. Simulations show that in most cases unbalanced samples and ties have little effect on this distribution. The d-d plot allows for a straightforward extension to the K-sample HWM index. As we have not been able to derive the distribution of the index for K>2, we simulate significance tables for K=3,...,15. An example involving economic growth rates of the G7 countries illustrates that the HWM test can have better power than alternative Empirical Distribution Function tests.

AB - We propose a quantification of the p-p plot that assigns equal weight to all distances between the respective distributions: the surface between the p-p plot and the diagonal. This surface is labelled the Harmonic Weighted Mass (HWM) index. We introduce the diagonal-deviation (d-d) plot that allows the index to be computed exactly under all circumstances. For two balanced samples absent ties the finite sample distribution of the HWM index is derived. Simulations show that in most cases unbalanced samples and ties have little effect on this distribution. The d-d plot allows for a straightforward extension to the K-sample HWM index. As we have not been able to derive the distribution of the index for K>2, we simulate significance tables for K=3,...,15. An example involving economic growth rates of the G7 countries illustrates that the HWM test can have better power than alternative Empirical Distribution Function tests.

M3 - Working paper

T3 - Discussion paper TI

BT - A K-sample Homogeneity Test based on the Quantification of the p-p Plot

PB - Tinbergen Instituut

CY - Amsterdam

ER -