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    <title>DSpace Collection:</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/720</link>
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    <dc:date>2026-04-29T12:22:55Z</dc:date>
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  <item rdf:about="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/722">
    <title>ADDITIVE SHARED INVERSE GAUSSIAN FRAILTY MODEL</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/722</link>
    <description>Title: ADDITIVE SHARED INVERSE GAUSSIAN FRAILTY MODEL
Authors: Lalpawimawha
Abstract: The study proposes additive hazard shared inverse Gaussian frailty model with generalized Pareto, generalized Rayleigh and xgamma distributions as baseline distribution to analyze the bivariate data set of McGilchrist and Aisbett (1991). The estimation of the parameters involved in the models was done by Bayesian approach of Markov Chain Monte Carlo technique. The true values and the estimated values of the parameters are compared by using simulation study. The proposed models are fitted to the real life data set and the best model suggested for the data.</description>
    <dc:date>2018-01-01T00:00:00Z</dc:date>
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  <item rdf:about="http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/721">
    <title>Comparison of shared frailty models: A Bayesian approach</title>
    <link>http://pucir.inflibnet.ac.in:8080/jspui/handle/123456789/721</link>
    <description>Title: Comparison of shared frailty models: A Bayesian approach
Authors: Lalpawimawha
Abstract: In this article, we propose gamma and inverse Gaussian frailty shared models with Akash distribution as baseline to analyze the bivariate survival data set of Mc Gilchrist and Aisbett (1991). Bayesian approach of Markov Chain Monte Carlo technique was employed to estimate the parameters involves in the models. The better model also suggested for the data.</description>
    <dc:date>2018-02-16T00:00:00Z</dc:date>
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