啜泣
发表于 2025-3-30 09:23:24
Brief Review of Parametric Likelihood Inferences,Maximum likelihood estimation (MLE) under regular conditions can be found in most statistical books. In non-regular cases, however, it involves all kinds of problems, such as solution on the boundary of parameter space, multiple roots, non-existence, inconsistency in the presence of many incidental parameters, etc.
incarcerate
发表于 2025-3-30 13:39:03
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abduction
发表于 2025-3-30 17:04:13
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Desert
发表于 2025-3-30 21:09:45
Empirical Likelihood with Applications,The maximum likelihood method for regular parametric models has many optimality properties. As a result, it is one of the most popular methods in statistical inference. However, model mis-specification is a big concern since a misspecified model may lead to bias results.
解脱
发表于 2025-3-31 01:56:13
,Kullback–Leibler Likelihood and Entropy Family,Besides empirical likelihood, the Kullback–Leibler likelihood is another popular method to calibrate auxiliary information. The entropy family has also been used extensively in information theory. We mainly focus on discussions for continuous random variable cases. The discrete cases can be treated similarly.
GREG
发表于 2025-3-31 09:03:10
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LURE
发表于 2025-3-31 12:11:28
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蕨类
发表于 2025-3-31 16:58:57
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领袖气质
发表于 2025-3-31 20:22:32
Discrete Data Models,The logistic regression model has been widely used in statistical literature for analyzing categorical data. In this chapter we present many other useful discrete data models. If the data collection process is retrospective, then we end up with different biased sampling problems.
Obstruction
发表于 2025-4-1 00:10:15
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