Constrained Maximum Likelihood

被引：27

作者：

Schoenberg R. ^{[1
,2
]}

机构：

[1] Aptech Systems, Inc., University of Washington

[2] Aptech Systems, Inc., Maple Valley, WA 98038

来源：

Computational Economics | 1997年 / 10卷 / 3期

关键词：

Inequality constraints; Maximum likelihood; Profile likelihood; Statistical inference;

D O I：

10.1023/A:1008669208700

中图分类号：

学科分类号：

摘要：

Constrained Maximum Likelihood (CML), developed at Aptech Systems, generates maximum likelihood estimates with general parametric constraints (linear or nonlinear, equality or inequality), using the sequential quadratic programming method. CML computes two classes of confidence intervals, by inversion of the Wald and likelihood ratio statistics, and by simulation. The inversion techniques can produce misleading test sizes, but Monte Carlo evidence suggests this problem can be corrected under certain circumstances.

引用

页码：251 / 266

页数：15

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