Adaptive trimmed likelihood estimation in regression
نویسندگان
چکیده
منابع مشابه
Modified Maximum Likelihood Estimation in Poisson Regression
In Generalized Linear Models, likelihood equations are intractable and do not have explicit solutions; thus, they must be solved by using Newton-type algorithms. Solving these equations by iterations, however, can be problematic: the iterations might converge to wrong values or the iterations might not converge at all. In this study, we derive the modified maximum likelihood estimators for Pois...
متن کاملModified Maximum Likelihood Estimation in Poisson Regression
In Generalized Linear Models, likelihood equations are intractable and do not have explicit solutions; thus, they must be solved by using Newton-type algorithms. Solving these equations by iterations, however, can be problematic: the iterations might converge to wrong values or the iterations might not converge at all. In this study, we derive the modified maximum likelihood estimators for Pois...
متن کاملApproximate Maximum Likelihood Estimation in Linear Regression*
A b s t r a c t. The application of the ML method in linear regression requires a parametric form for the error density. When this is not available, the density may be parameterized by its cumulants (~i) and the ML then applied. Results , (i+2)/2 are obtained when the standardized cumulants (~/~) satisfy ~/~ = ~i+2/~2 = O(v i) as v-~ 0 for i > 0.
متن کاملBayesian and Iterative Maximum Likelihood Estimation of the Coefficients in Logistic Regression Analysis with Linked Data
This paper considers logistic regression analysis with linked data. It is shown that, in logistic regression analysis with linked data, a finite mixture of Bernoulli distributions can be used for modeling the response variables. We proposed an iterative maximum likelihood estimator for the regression coefficients that takes the matching probabilities into account. Next, the Bayesian counterpart...
متن کاملThe Development of Maximum Likelihood Estimation Approaches for Adaptive Estimation of Free Speed and Critical Density in Vehicle Freeways
The performance of many traffic control strategies depends on how much the traffic flow models are accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive loop d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Discussiones Mathematicae Probability and Statistics
سال: 2010
ISSN: 1509-9423,2084-0381
DOI: 10.7151/dmps.1128