Hazard rate function estimation using Erlang kernel
نویسندگان
چکیده
منابع مشابه
a non-parametric method for hazard rate estimation in acute myocardial infarction patients: kernel smoothing approach
background : kernel smoothing method is a non-parametric or graphical method for statistical estimation. in the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. methods : by employing non-parametric regression methods, the curve estimation, may have some complexity. in this article, four indices of epanechnikov, b...
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Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we st...
متن کاملA non-parametric method for hazard rate estimation in acute myocardial infarction patients: kernel smoothing approach.
BACKGROUND Kernel smoothing method is a non-parametric or graphical method for statistical estimation. In the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. METHODS By employing non-parametric regression methods, the curve estimation, may have some complexity. In this article, four indices of Epanechnikov, Biqu...
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In nonparametric curve estimation the decision about the type of smoothing parameter is critical for the practical performance. The nearest neighbor bandwidth as introduced by Gefeller and Dette 1992 for censored data in survival analysis is specified by one parameter, namely the number of nearest neighbors. Bandwidth selection in this setting is rarely investigated although not linked closely ...
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Practical estimation procedures for local linear estimation of an unrestricted failure rate when more information is available than just time are developed. This extra information could be a covariate and this covariate could be a time series. Time dependent covariates are sometimes called markers, and failure rates are sometimes called hazards, intensities or mortalities. It is shown through s...
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ژورنال
عنوان ژورنال: Pure Mathematical Sciences
سال: 2014
ISSN: 1314-7560
DOI: 10.12988/pms.2014.4616