Journal of Probability and Statistics
Special Issue on
Conditional Likelihood and its Applications
Call for Papers
The method of maximum likelihood estimation is widely
used in probability-based statistical inference. Usually, the
assumed probability model for the observed data defines
the likelihood. When the data are collected under more
complex designs such as two-phase cohort sampling designs,
or when the data are of special type such as genotype data
and missing data, modeling even unobserved data becomes
essential and also attractive. However, in many situations
inference might be better approached by using conditional
likelihood, which is defined by the probability model for a
subset of the original collection of variables conditioned on
its complement. These sets are defined based on the inference
question that is estimation of unknown quantities of interest.
This approach is better in the sense that it is simplified
because of discarding part of the data which may contain
information about the parameters of interest. Literature on
conditional likelihood inference is sparse and is also confused
with marginal, pseudo- and partial likelihoods. It would also
be of importance to justify the use of conditional likelihood
in Bayesian approach.
We invite authors to present original research articles and
review articles on conditional likelihood-based inference and
related theory and applications. Potential topics include, but
are not limited to:
Manuscript Due
September 1, 2011
First Round of Reviews
December 1, 2011
Publication Date
March 1, 2012
Lead Guest Editor
Sangita Kulathinal, Indic Society for Education and
Development (INSEED), Swami Enterprises Complex,
Tigrania road, Tapovan Bridge, Nashik 422 011,
Maharashtra, India; sangita.kulathinal@inseed.org
Guest Editors
Dario Gasbarra, Department of Mathematics and
Statistics, University of Helsinki, 00014 Helsinki, Finland;
dario.d.gasbarra@jyu.fi
Kari Auranen, Department of Mathematics and Statistics,
University of Helsinki, 00014 Helsinki, Finland;
kari.auranen@thl.fi
• Theoretical development under conditional likelihood
• Applications of conditional likelihood in:
• Infectious disease data
• Genetic data
• Diffusion magnetic resonance images (MRI),
with applications to neuroscience
• Complex designs
Before submission authors should carefully read over the
journal’s Author Guidelines, which are located at http://www
.hindawi.com/journals/jps/guidelines/. Prospective authors
should submit an electronic copy of their complete
manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/ according to the following
timetable:
Hindawi Publishing Corporation
http://www.hindawi.com/