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This paper presents a new methodology to solve problems resulting from missing data in large-scale item performance behavioral databases. Useful statistics corrected for missing data are described, an...
We study the asymptotic behavior of the least squares estimators of the unknown parameters of bifurcating autoregressive processes when some of the data are missing. We model the process of observed d...
Two techniques have emerged from the recent literature as candidate solutions to the problem of missing data imputation, and these are the Expectation Maximisation (EM) Algorithm and the auto-associ...
The deviance information criterion(DIC)introduced by Spiegelhalter et al. (2002) for model assessment and model comparison is directly inspired by linear and generalised linear models, but it is ope...

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