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Articles 1 - 16 of 16
Full-Text Articles in Mathematics
The Pitman Inequality For Exchangeable Random Vectors, J. Behboodian, Naveen Bansal, Gholamhossein Hamedani, Hans Volkmer
The Pitman Inequality For Exchangeable Random Vectors, J. Behboodian, Naveen Bansal, Gholamhossein Hamedani, Hans Volkmer
Naveen Bansal
In this short article the following inequality called the “Pitman inequality” is proved for the exchangeable random vector (X1,X2,…,Xn)(X1,X2,…,Xn) without the assumption of continuity and symmetry for each component XiXi:
P(|1n∑i=1nXi|≤|∑i=1nαiXi|)≥12 ,
where allαi≥0 are special weights with∑i=1nαi=1.
Randomized Detection Of Extraneous Factors, Manfred Minimair
Randomized Detection Of Extraneous Factors, Manfred Minimair
Manfred Minimair
A projection operator of a system of parametric polynomials is a polynomial in the coefficients of the system that vanishes if the system has a common root. The projection operator is a multiple of the resultant of the system, and the factors of the projection operator that are not contained in the resultant are called extraneous factors. The main contribution of this work is to provide a randomized algorithm to check whether a factor is extraneous, which is an important task in applications. A lower bound for the success probability is determined which can be set arbitrarily close to one. …
Bayesian Analysis Of Hypothesis Testing Problems For General Population: A Kullback–Leibler Alternative, Naveen Bansal, Gholamhossein Hamedani, Ru Sheng
Bayesian Analysis Of Hypothesis Testing Problems For General Population: A Kullback–Leibler Alternative, Naveen Bansal, Gholamhossein Hamedani, Ru Sheng
Naveen Bansal
We consider a hypothesis problem with directional alternatives. We approach the problem from a Bayesian decision theoretic point of view and consider a situation when one side of the alternatives is more important or more probable than the other. We develop a general Bayesian framework by specifying a mixture prior structure and a loss function related to the Kullback–Leibler divergence. This Bayesian decision method is applied to Normal and Poisson populations. Simulations are performed to compare the performance of the proposed method with that of a method based on a classical z-test and a Bayesian method based on the …
Creating Composite Age Groups To Smooth Percentile Rank Distributions Of Small Samples, Francesca Lopez, Amy Olson, Naveen Bansal
Creating Composite Age Groups To Smooth Percentile Rank Distributions Of Small Samples, Francesca Lopez, Amy Olson, Naveen Bansal
Naveen Bansal
Individually administered tests are often normed on small samples, a process that may result in irregularities within and across various age or grade distributions. Test users often smooth distributions guided by Thurstone assumptions (normality and linearity) to result in norms that adhere to assumptions made about how the data should look. Test users, however, may come across particular tests or sets of data in which the Thurstone assumptions are untenable. When users expect deviations from normality within age or grade, an alternate method is desirable. The authors present a relatively simple procedure that allows the user to treat observed raw …
Decision Diagrams And Dynamic Programming, John Hooker
Decision Diagrams And Dynamic Programming, John Hooker
John Hooker
No abstract provided.
Mixed Integer Programming Vs Logic-Based Benders Decomposition For Planning And Scheduling, John Hooker, Andre Cire
Mixed Integer Programming Vs Logic-Based Benders Decomposition For Planning And Scheduling, John Hooker, Andre Cire
John Hooker
No abstract provided.
Integrated Methods For Optimization, 2nd Ed, John Hooker
Integrated Methods For Optimization, 2nd Ed, John Hooker
John Hooker
No abstract provided.
Business Ethics As Rational Choice, John Hooker
Open Source Surveys With Asset, Bert Wachsmuth
Constraint Programming, John Hooker
Working Across Cultures, John Hooker
Logic, Optimization And Constraint Programming, John Hooker
Logic, Optimization And Constraint Programming, John Hooker
John Hooker
No abstract provided.
Interactive Real Analysis. / Glossary, Bert Wachsmuth
Interactive Real Analysis. / Glossary, Bert Wachsmuth
Bert Wachsmuth
No abstract provided.
Logic-Based Methods For Optimization: Combining Optimization And Constraint Satisfaction, John Hooker
Logic-Based Methods For Optimization: Combining Optimization And Constraint Satisfaction, John Hooker
John Hooker
No abstract provided.
Optimization Methods For Logical Inference, Vijay Chandru, John Hooker
Optimization Methods For Logical Inference, Vijay Chandru, John Hooker
John Hooker
No abstract provided.
Constraint Satisfaction Methods For Generating Valid Cuts, John Hooker
Constraint Satisfaction Methods For Generating Valid Cuts, John Hooker
John Hooker
No abstract provided.