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Testing for Parameter Variation in Non-Linear Regression Models

B. P. M. McCabe and S. J. Leybourne
Journal of the Royal Statistical Society. Series B (Methodological)
Vol. 55, No. 1 (1993), pp. 133-144
Published by: Wiley for the Royal Statistical Society
Stable URL: http://www.jstor.org/stable/2346070
Page Count: 12
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Testing for Parameter Variation in Non-Linear Regression Models
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Abstract

This paper addresses the problem of testing for purely random parameter variation in non-linear regression models. Based on different approximations to the true density of the data, score-type tests are constructed and their asymptotic distributions are derived. The local power of the tests is investigated both theoretically and via Monte Carlo simulation. An empirical testing example, involving a well-known non-linear aggregate demand for money function, is also given.

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