Characterizing the Performance of the Conway-Maxwell Poisson Generalized Linear Model

Risk Analysis

Volumn 32, Issue 1, 2012, Pages 167-183

  Francis, Royce A ^a,b   Geedipally, Srinivas Reddy ^c   Guikema, Seth D ^b   Dhavala, Soma Sekhar ^e   Lord, Dominique ^d   Larocca, Sarah ^b  

^a The George Washington University   (United States)

^b Johns Hopkins University   (United States)

^c TEXAS A AND M UNIVERSITY SYSTEM   (United States)

^d Department of Electrical and Computer Engineering   (United States)

^e TEXAS A AND M UNIVERSITY   (United States)

Author keywords

Maximum likelihood estimation; Overdispersed count data; Regression; Underdispersed count data

Indexed keywords

DATA REGRESSION; DATA SETS; DISCRETE EVENTS; FLEXIBLE MODEL; GENERALIZED LINEAR MODEL; HEALTH OUTCOMES; INFRASTRUCTURE SYSTEMS; MAXIMUM LIKELIHOOD ESTIMATION METHOD; NEW MODEL; OVERDISPERSED COUNT DATA; PARAMETER ESTIMATE; PREDICTION ACCURACY; REGRESSION; SAMPLE MEANS; SIMULATED DATASETS; STATISTICAL PERFORMANCE; UNDERDISPERSED COUNT DATA; VARIANCE STRUCTURE;

ESTIMATION; HEALTH RISKS; MAXIMUM LIKELIHOOD ESTIMATION; MAXWELL EQUATIONS; PARAMETER ESTIMATION; REGRESSION ANALYSIS; RISK ANALYSIS; RISK ASSESSMENT; RISK PERCEPTION; SYSTEMS ENGINEERING;

POISSON DISTRIBUTION;

ACCURACY ASSESSMENT; DATA SET; DISCRETE CHOICE ANALYSIS; INFRASTRUCTURE; LINEARITY; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; POISSON RATIO; REGRESSION ANALYSIS; RISK ASSESSMENT;

ARTICLE; EPIDEMIOLOGY; FACTUAL DATABASE; HUMAN; POISSON DISTRIBUTION; REGRESSION ANALYSIS; RISK ASSESSMENT; STATISTICAL MODEL; STATISTICS;

BIAS (EPIDEMIOLOGY); DATABASES, FACTUAL; HUMANS; LIKELIHOOD FUNCTIONS; LINEAR MODELS; POISSON DISTRIBUTION; REGRESSION ANALYSIS; RISK ASSESSMENT;

EID: 84855304878     PISSN: 02724332     EISSN: 15396924     Source Type: Journal    
DOI: 10.1111/j.1539-6924.2011.01659.x     Document Type: Article

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