This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 308
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #309204
Title: A Proposed Goodness-of-Fit Test for the Assumptions of a Poisson Process
Author(s): Bob McQuaid and Kellie Keeling and Robert Pavur*+
Companies: Pepperdine University and University of Denver and University of North Texas
Address: 1155 Union Circle #305249, Denton , TX, 76203-5017, USA
Keywords: Poisson Process ; Runs Test

The paper proposes a goodness of fit test procedure for departures of a renewal process from the standard assumptions of a homogeneous Poisson Process. This procedure makes use of a runs tests for one process that is known to be a Poisson Process and another process which is being examined its assumption of being generated by a Poisson process. A justification is presented for the proposed test. One advantage is that it is simpler to implement than other well known procedures to test for the assumptions of a Poisson Process. The usefulness of this test is important as applications of the Poisson Process abound in many business and scientific studies. A Monte Carlo simulation study demonstrates both the robustness and power of the proposed test.

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