Parameter Shrinkage for Age-Period-Cohort Modeling of Opioid Mortality Rates

Statistical methods that shrink parameters towards zero can produce lower predictive variance than does maximum likelihood. This paper discusses an approach to doing this for age-period-cohort models, and applies it to fitting opioid mortality rates with a generalization of the Lee-Carter model including cohorts. Bayesian parameter shrinkage has some practical advantages over classical versions

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Year of publication:	2018
Authors:	Venter, Gary
Publisher:	[S.l.] : SSRN
Subject:	Sterblichkeit \| Mortality \| Drogenkonsum \| Drug consumption \| Schätztheorie \| Estimation theory \| Arzneimittel \| Pharmaceuticals

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Extent:	1 Online-Ressource (13 p)
Type of publication:	Book / Working Paper
Language:	English
Notes:	Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 4, 2018 erstellt
Other identifiers:	10.2139/ssrn.3117707 [DOI]
Classification:	C11 - Bayesian Analysis ; C51 - Model Construction and Estimation ; I12 - Health Production: Nutrition, Mortality, Morbidity, Substance Abuse and Addiction, Disability, and Economic Behavior ; J11 - Demographic Trends and Forecasts
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10014116617