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T2 control charts are used to monitor a process when more than one quality variable associated with process is being observed. Recent studies have shown that using variable sample size (VSS) schemes result in charts with more statistical power when detecting small to moderate shifts in the process mean vector. This paper presents an economic- statistical design of T2 control charts with variable sample size and control limits (VSSC). We build a cost model of a T2-VSSC control chart for the purpose of economic- statistical design using the model of Costa and Rahim (2001).This cost model is constructed that involves the cost of false alarms, the cost of finding and eliminating the assignable cause, the cost associated with production in an out-of-control state, and the cost of sampling and testing. We optimize this model using a genetic algorithm (GA) approach. Furthermore, T2-VSSC and T2-VSS charts are compared with respect to the expect cost per unit time.

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Logic regression is a generalized regression and classification method that is able to make Boolean combinations
as new predictive variables from the original binary variables. Logic regression was introduced for case control or
cohort study with independent observations. Although in various studies, correlated observations occur due to different
reasons, logic regression have not been studied in theory and application to analyze of correlated observations
and longitudinal data.
Due to the importance of identifying and considering the interactions between variables in longitudinal studies,
in this paper we propose Transition Logic Regression as an extension of Logic Regression to binary longitudinal
data. AIC of the models are used as score function of Annealing algorithm. In order to assess the performance of
the method, simulation study is done in various conditions of sample size, first order dependency and interaction
effect. According to results of simulation study, by increasing the sample size, percentage of identification of true
interactions and MSE of estimations get better. As an application, we assess interaction effect of some SNPs on
HDL level over time in TLGS study using our proposed model.

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‎Given the importance of Markov chains in information theory‎, ‎the definition of conditional probability for these random processes can also be defined in terms of mutual information‎. ‎In this paper‎, ‎the relationship between the concept of sufficiency and Markov chains from the perspective of information theory and the relationship between probabilistic sufficiency and algorithmic sufficiency is determined‎. 

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Methods of inferring the population structure‎, ‎its applications in identifying disease models as well as foresighting the physical and mental situation of human beings have been finding ever-increasing importance‎. ‎In this article‎, ‎first‎, ‎motivation and significance of studying the problem of population structure is explained‎. ‎In the next section‎, ‎the applications of inference of population structure in biology and the treatment of various diseases are described‎. ‎Afterward‎, ‎the methods of inferring the population structure as well as detecting the disease model correspond to each subpopulation‎, ‎for populations whose members are admixture or not‎, ‎are described separately‎. ‎To this end‎, ‎the methods of inferring the population structure through the Bayesian approach are emphasized and the reasons for the superiority of Bayesian methods are illustrated‎.