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Semiparametric smoothing of discrete failure time data.
Biom J 2012; 54(1):5-19BJ

Abstract

An estimator of the hazard rate function from discrete failure time data is obtained by semiparametric smoothing of the (nonsmooth) maximum likelihood estimator, which is achieved by repeated multiplication of a Markov chain transition-type matrix. This matrix is constructed so as to have a given standard discrete parametric hazard rate model, termed the vehicle model, as its stationary hazard rate. As with the discrete density estimation case, the proposed estimator gives improved performance when the vehicle model is a good one and otherwise provides a nonparametric method comparable to the only purely nonparametric smoother discussed in the literature. The proposed semiparametric smoothing approach is then extended to hazard models with covariates and is illustrated by applications to simulated and real data sets.

Authors+Show Affiliations

School of Mathematics and Statistics, The University of Birmingham, Birmingham, B15 2TT, UK.No affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

22170332

Citation

Patil, Prakash N., and Dimitrios Bagkavos. "Semiparametric Smoothing of Discrete Failure Time Data." Biometrical Journal. Biometrische Zeitschrift, vol. 54, no. 1, 2012, pp. 5-19.
Patil PN, Bagkavos D. Semiparametric smoothing of discrete failure time data. Biom J. 2012;54(1):5-19.
Patil, P. N., & Bagkavos, D. (2012). Semiparametric smoothing of discrete failure time data. Biometrical Journal. Biometrische Zeitschrift, 54(1), pp. 5-19. doi:10.1002/bimj.201100058.
Patil PN, Bagkavos D. Semiparametric Smoothing of Discrete Failure Time Data. Biom J. 2012;54(1):5-19. PubMed PMID: 22170332.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Semiparametric smoothing of discrete failure time data. AU - Patil,Prakash N, AU - Bagkavos,Dimitrios, Y1 - 2011/12/14/ PY - 2011/03/07/received PY - 2011/07/22/revised PY - 2011/09/05/accepted PY - 2011/12/16/entrez PY - 2011/12/16/pubmed PY - 2012/8/11/medline SP - 5 EP - 19 JF - Biometrical journal. Biometrische Zeitschrift JO - Biom J VL - 54 IS - 1 N2 - An estimator of the hazard rate function from discrete failure time data is obtained by semiparametric smoothing of the (nonsmooth) maximum likelihood estimator, which is achieved by repeated multiplication of a Markov chain transition-type matrix. This matrix is constructed so as to have a given standard discrete parametric hazard rate model, termed the vehicle model, as its stationary hazard rate. As with the discrete density estimation case, the proposed estimator gives improved performance when the vehicle model is a good one and otherwise provides a nonparametric method comparable to the only purely nonparametric smoother discussed in the literature. The proposed semiparametric smoothing approach is then extended to hazard models with covariates and is illustrated by applications to simulated and real data sets. SN - 1521-4036 UR - https://www.unboundmedicine.com/medline/citation/22170332/Semiparametric_smoothing_of_discrete_failure_time_data_ L2 - https://doi.org/10.1002/bimj.201100058 DB - PRIME DP - Unbound Medicine ER -