A relative weighting method for estimating parameters and variances in multiple data sets

Computational Statistics and Data Analysis

Volumn 22, Issue 2, 1996, Pages 119-135

  Bell, Bradley M ^a   Burke, James V ^a   Schumitzky, Alan ^b  

^a UNIVERSITY OF WASHINGTON   (United States)

^b UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

Author keywords

Asymptotic statistics; Nonlinear least squares

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; DATA STRUCTURES; ERRORS; ESTIMATION; MATHEMATICAL MODELS; NONLINEAR PROGRAMMING; NONLINEAR SYSTEMS; OPTIMIZATION; PARAMETER ESTIMATION; STATISTICAL METHODS;

ASYMPTOTIC STATISTICS; DATA VARIANCES; MAXIMUM LIKELIHOOD ESTIMATION; MULTIPLE DATA SETS; NONLINEAR LEAST SQUARES; NONLINEAR MODEL FUNCTION; PARAMETER VECTOR; RELATIVE WEIGHTING METHOD; STANDARD SUCCESSIVE APPROXIMATION ALGORITHM; VARIANCE ESTIMATORS;

LEAST SQUARES APPROXIMATIONS;

EID: 0030196598     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/0167-9473(95)00043-7     Document Type: Article

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