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多元 Probit 模型最大似然估计的存在性与唯一性AI 解读

The multivariate probit model (MPM) is a particular case of the class of correlated prediction models. A correlated prediction model is especially useful when prediction or classification is envisaged into diagnostic classes that are combinations of binary responses. The parameter vector consists of a “location” part and an “association” part. The location part accounts for the effect the regressors have on the marginal probabilities of the binary responses. The association…

非平稳分类时间序列回归模型：渐近估计理论AI 解读

For the analysis of nonstationary categorical time series, a parsimonious and flexible class of models is proposed. These models are generalizations of regression models for stochastically independent categorical observations. Consistency, asymptotic normality and efficiency of the maximum likelihood estimator are shown under weak and easily verifiable requirements. Some models for binary time series are discussed in detail. To demonstrate asymptotic properties, a theorem is…

广义线性模型最大似然估计的一致性与渐近正态性AI 解读

Generalized linear models are used for regression analysis in a number of cases, including categorical responses, where the classical assumptions are violated. The statistical analysis of such models is based on the asymptotic properties of the maximum likelihood estimator. We present mild general conditions which, respectively, assure weak or strong consistency or asymptotic normality. Most of the previous work has been concerned with natural link functions. In this case…