Tech Reports
Tech Report kmi-98-06 Abstract
Model Selection and Model Averaging with Missing Data
Techreport ID: kmi-98-06
Date: 1998
Author(s): Marco Ramoni and Paola Sebastiani
Missing data can impair the reliability of statistical inference as they may affect the representativity of the sample. Nonetheless, under some conditions guaranteeing that the missing data mechanism is ignorable, reliable conclusions can be still drawn from the incomplete sample. Ignorability conditions are well-understood for parameter estimation but when the inference task involves the computation of the posterior probability of a data model, as required by Bayesian model selection and prediction through model averaging, these conditions are not sufficient. This paper defines new ignorability conditions for model selection and model averaging from incomplete data. 1. Knowledge Media Institute, The Open University. 2. Department of Actuarial Science and Statistics, City University.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Narrative Hypermedia is...
Hypermedia is the combination of hypertext for linking and structuring multimedia information.
Narrative Hypermedia is therefore concerned with how all of the above narrative forms, plus the many other diverse forms of discourse possible on the Web, can be effectively designed to communicate coherent conceptual structures, drawing inspiration from theories in narratology, semiotics, psycholinguistics and film.
List all Narrative Hypermedia Projects
Check out these Hot Narrative Hypermedia Technologies:
List all Narrative Hypermedia Technologies
