Response modeling methodology (RMM) - maximum likelihood estimation procedures
نویسنده
چکیده
Responsemodelingmethodology (RMM) is a new approach for empiricalmodeling.ML estimation procedures for theRMMmodel are developed. For relationalmodeling, theRMMmodel is estimated in two phases. In the first phase, the structure of the linear predictor (LP) is determined and its parameters estimated. This is accomplished by combining canonical correlation analysis with linear regression analysis. The former procedure is used to estimate coefficients in a Taylor series approximation to an unspecified response transformation. Canonical scores are then used in the latter procedure as response values in order to estimate coefficients of the LP. In the second phase, the parameters of the RMMmodel are estimated viaML, given the LP estimated earlier. Formodeling randomvariation, it is assumed that the LP is constant and a new simple percentile-based estimating procedure is developed. The new estimation procedures are demonstrated for some published data. © 2004 Elsevier B.V. All rights reserved.
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عنوان ژورنال:
- Computational Statistics & Data Analysis
دوره 49 شماره
صفحات -
تاریخ انتشار 2005