نتایج جستجو برای: dynamic equi correlation ispreferable to estimate value
تعداد نتایج: 10899229 فیلتر نتایج به سال:
objectives to investigate the correlation between t2* values of different regions of interest (rois) in myocardium with the means of semi quantitatively estimating the myocardiac iron content in the thalassemia major patients. in the same setting we tried to design a model to predict t2* value of interventricular septum (septum) based on t2* values of other convenient rois in myocardium. method...
Feature attributions based on the Shapley value are popular for explaining machine learning models. However, their estimation is complex from both theoretical and computational standpoints. We disentangle this complexity into two main factors: approach to removing feature information tractable strategy. These factors provide a natural lens through which we can better understand compare 24 disti...
We study the convergence of the false discovery proportion (FDP) of the Benjamini-Hochberg procedure in the Gaussian equi-correlated model, when the correlation ρm converges to zero as the hypothesis number m grows to infinity. By contrast with the standard convergence rate m1/2 holding under independence, this study shows that the FDP converges to the false discovery rate (FDR) at rate {min(m,...
Very often statisticians have to deal with the problem of sample size calculation. However this is one of the most difficult questions to be answered since it depends on many considerations, assumptions and restrictions on the real problem being solved. In this paper we develop some methods, based on credible intervals, to calculate sample sizes for proportions and correlations.
This paper proposes two types of stochastic correlation structures for Multivariate Stochastic Volatility (MSV) models, namely the constant correlation (CC) MSV and dynamic correlation (DC) MSV models, from which the stochastic covariance structures could be obtained easily. Both structures can be used for purposes of optimal portfolio and risk management, and for calculating Value-at-Risk (VaR...
abstract the purpose of this study was to find out the effect of applying the principles of group-dynamic assessment (g-da) on learning of conditional structures in english by iranian efl learners at the intermediate level, which according to the formal educational system in iran, includes students who are in their second year of studying in high schools of koohdasht city. this study was a qua...
Current database systems utilize histograms to approximate frequency distributions of attribute values of relations. These are used to efficiently estimate query result sizes and access plan costs. Even though they have been in use for nearly two decades, there has been no significant mathematical techniques (other than those used in statistics for traditional histogram approximations) to study...
in this study reference as one of the five cohesive devices in the achievement of textuality in english and persian narrative/descripitive written texts is focused on and analysed . to do so , the theoretical framework elaborated by halliday and hasan (1976) and its version adapted by the writer to match the sub-types of reference in farsi are applied to the analysis of reference in english and...
Strangles, the most frequently diagnosed infectious disease of horses worldwide, is caused by Streptococcus equi. Despite its prevalence, the global diversity and mechanisms underlying the evolution of S. equi as a host-restricted pathogen remain poorly understood. Here, we define the global population structure of this important pathogen and reveal a population replacement in the late 19th or ...
Systemic risk arises from simultaneous movement or correlations between market segments; Thus, systemic risk occurs when there is a high correlation between the risks and crises of different market segments or institutions operating in the economy, or when the risks of different segments in a market segment or a country are related to other segments and other countries. This paper presents a me...
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