Journal of the Iranian Statistical Society
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Journal of The Iranian Statistical Society - Journal articles for year 2004, Volume 3, Number 1Yektaweb Collection - https://yektaweb.comen2004/3/11When Can Finite Testing Ensure Infinite Trustworthiness?
http://jirss.irstat.ir/browse.php?a_id=100&sid=1&slc_lang=en
<p dir="ltr">In this paper we contribute to the general philosophical question
as to whether empirical testing can ever prove a physical law. Problems that
lead to this question arise under several contexts, and the matter has been
addressed by the likes of Bayes and Laplace. After pointing out that a
Bayesian approach is the proper way to address this problem, we show that
the answer depends on what we start with. Namely, under certain prior
assumptions, a finite amount of testing can lead to the conclusion of total
trustworthiness, though such priors could be unrealistic. However, we do
produce a new class of priors under which a finite amount of testing can lead
to a high degree of trustworthiness, at a relatively fast pace. We use the
scenario of software testing as a way to motivate and discuss our development.</p>
Nozer D. SingpurwallaParameter Identifiability Issues in a Latent Ma- rkov Model for Misclassified Binary Responses
http://jirss.irstat.ir/browse.php?a_id=101&sid=1&slc_lang=en
Medical researchers may be interested in disease processes that are not
directly observable. Imperfect diagnostic tests may be used repeatedly to
monitor the condition of a patient in the absence of a gold standard. We
consider parameter identifiability and estimability in a Markov model for
alternating binary longitudinal responses that may be misclassified. Exactly
two distinct sets of parameter values are shown to generate the distribution
for the data in a common situation and we propose a restriction to
distinguishes the two. Even with the restriction, parameters may not be
estimable. Issues of sampling and correct model specification are discussed.Rhonda J. Rosychuk Moment Inequalities for Supremum of Empirical Processes of U-Statistic Structure and Application to Density Estimation
http://jirss.irstat.ir/browse.php?a_id=102&sid=1&slc_lang=en
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We derive moment inequalities for the supremum of empirical processes of
U-Statistic structure and give application to kernel type density
estimation and estimation of the distribution function for functions of
observations.</p>
B. L. S. Prakasa RaoA Conditional Test for Exponentiality Against Weibull DFR Alternatives Based on Censored Samples
http://jirss.irstat.ir/browse.php?a_id=106&sid=1&slc_lang=en
A conditional test based on quadratic form using type-2 censored sample for testing exponentiality against Weibull alternative is proposed. The simulated percentage points and powers are given. The proposed test performs well for identifying Weibull DFR alternative even for small sample. An example is also given.
K. Muralidharan