Expectation-maximization algorithms for learning a finite mixture of univariate survival time distributions from partially specified class values

No abstract is available for this paper.

• Publication year

  2013

• Venue

  Unknown venue

• Publication date

  2013-05-15

• Fields of study

  Mathematics, Computer Science, Medicine

• Identifiers
  DOI 10.31274/ETD-180810-3372
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Learning from Partial Labels

  2011cited by this paper
• Introducing Knowledge into Differential Expression Analysis

  2010cited by this paper
• Introduction to Semi-Supervised Learning

  2009cited by this paper
• Learning from ambiguously labeled images

  2009cited by this paper
• Learning from partially supervised data using mixture models and belief functions

  2009cited by this paper
• Medical Applications of Finite Mixture Models

  2009cited by this paper
• Mixture Model Estimation with Soft Labels

  2008cited by this paper
• Finite Mixture Models

  2008cited by this paper
• Multi-Label Classification: An Overview

  2007cited by this paper
• Learning Ontology-Aware Classifiers

  2005cited by this paper
• Probabilistic Reasoning with Hierarchically Structured Variables

  2005cited by this paper
• Partially Supervised Learning by a Credal EM Approach

  2005cited by this paper
• Learning Accurate and Concise Näıve Bayes Classifiers from Attribute Value Taxonomies and Data 1

  2005cited by this paper
• Parameter estimation of incomplete data in competing risks using the EM algorithm

  2005cited by this paper
• A Mixture Model and EM-Based Algorithm for Class Discovery, Robust Classification, and Outlier Rejection in Mixed Labeled/Unlabeled Data Sets

  2003cited by this paper
• Comparison of spark OES methods for analysis of inclusions in iron base matters

  2002cited by this paper
• Handling uncertain labels in multiclass problems using belief decision trees

  2002cited by this paper
• EM Algorithm for Partially Known Labels

  2000cited by this paper
• A Nonparametric Mixture Model for Cure Rate Estimation

  2000cited by this paper
• Survival with competing risks and masked causes of failures

  1998cited by this paper
• Coarsening at Random: Characterizations, Conjectures, Counter-Examples

  1997cited by this paper
• The EM algorithm and extensions

  1996cited by this paper
• Inference about defects in the presence of masking

  1996cited by this paper
• On Handling Tree-Structured Attributed in Decision Tree Learning

  1995cited by this paper
• Applications of the EM algorithm to the analysis of life length data

  1995cited by this paper
• System life data analysis with dependent partial knowledge on the exact cause of system failure

  1994cited by this paper
• Estimating system and component reliabilities under partial information on cause of failure

  1991cited by this paper
• Ignorability and Coarse Data

  1991cited by this paper
• Exponential survival trees.

  1989influential reference
• An iterative approach for estimating component reliability from masked system life data

  1989cited by this paper
• Maximum likelihood analysis of component reliability using masked system life-test data

  1988cited by this paper
• On Bayes Estimation for Mixtures of Two Exponential-Life-Distributions from Right-Censored Samples

  1986cited by this paper
• A mixture model for the regression analysis of competing risks data

  1985cited by this paper
• Mixture densities, maximum likelihood, and the EM algorithm

  1984cited by this paper
• Analysis of Incomplete Data in Competing Risks Model

  1984cited by this paper
• Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper

  1977influential reference
• A new look at the statistical model identification

  1974influential reference
• A Comparison of Iterative Maximum Likelihood Estimates of the Parameters of a Mixture of Two Normal Distributions Under Three Different Types of Sample

  1973cited by this paper
• PATTERN CLUSTERING BY MULTIVARIATE MIXTURE ANALYSIS.

  1970cited by this paper
• Estimating the components of a mixture of normal distributions

  1969cited by this paper
• Finite mixtures of distributions from the exponential family

  1969cited by this paper
• Estimation of parameters for a mixture of normal distributions

  1966cited by this paper
• THE METHOD OF MOMENTS APPLIED TO A MIXTURE OF TWO EXPONENTIAL DISTRIBUTIONS

  1961cited by this paper
• ESTIMATION OF PARAMETERS OF MIXED EXPONENTIALLY DISTRIBUTED FAILURE TIME DISTRIBUTIONS FROM CENSORED LIFE TEST DATA

  1958cited by this paper
• Nonparametric Estimation from Incomplete Observations

  1958cited by this paper

• Evidential Estimation of an Uncertain Mixed Exponential Distribution under Progressive Censoring

  2020cites this paper