Sreedevi, E P; Dr.Sankaran, P G(Cochin University Of Science And Technology, April 9, 2010)
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Abstract:
there has been much research
on analyzing various forms of competing risks data. Nevertheless, there are several
occasions in survival studies, where the existing models and methodologies are
inadequate for the analysis competing risks data. ldentifiabilty problem and various
types of and censoring induce more complications in the analysis of competing risks
data than in classical survival analysis. Parametric models are not adequate for the
analysis of competing risks data since the assumptions about the underlying lifetime
distributions may not hold well. Motivated by this, in the present study. we develop
some new inference procedures, which are completely distribution free for the
analysis of competing risks data.
Description:
Department of Statistics, Cochin University of Science and
Technology
Maya, S S; Dr.Sunoj, S M(Cochin University of Science and Technology, October , 2007)
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Abstract:
The present study gave emphasis on characterizing continuous probability distributions
and its weighted versions in univariate set up. Therefore a possible work in this direction
is to study the properties of weighted distributions for truncated random variables in
discrete set up. The problem of extending the measures into higher dimensions as well as
its weighted versions is yet to be examined. As the present study focused attention to
length-biased models, the problem of studying the properties of weighted models with
various other weight functions and their functional relationships is yet to be examined.
Description:
Department of Statistics,
Cochin University of Science and Technology