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Efficient Estimation of Approximate Factor Models via Regularized Maximum Likelihood
High dimensionality unknown factors principal components sparse matrix conditional sparse thresholding cross-sectional correlation penalized maximum likelihood adaptive lasso heteroskedasticity
2012/11/23
We study the estimation of a high dimensional approximate factor model in the presence of both cross sectional dependence and heteroskedasticity. The classical method of principal components analysis ...
Likelihood Estimation with Incomplete Array Variate Observations
Likelihood Estimation Incomplete Array Variate Observations
2012/11/22
Missing data estimation is an important challenge with high-dimensional data arranged in the form of an array.In this paper we propose a probability model for partially observed multi-way array data. ...