scholarly journals Connectivity for 3 x 3 x K contingency tables

2011 ◽  
Vol 2 (1) ◽  
Author(s):  
Toshio Sumi ◽  
Toshio Sakata

We consider an exact sequential conditional test for three-way conditional test of nointeraction. At each time , the test uses as the conditional inference frame the set F(H ) of alltables with the same three two-way marginal tables as the obtained table H . For 33K tables,we propose a method to construct F(H ) from F(H􀀀1). This enables us to perform ecientlythe sequential exact conditional test. The subset S of F(H ) consisting of s + H 􀀀 H􀀀1 fors 2 F(H􀀀1) contains H , where the operations + and 􀀀 are dened elementwise. Our argumentis based on the minimal Markov basis for 3 3 K contingency tables and we give a minimalsubset M of some Markov basis which has the property that F(H ) = fs 􀀀 m j s 2 S ;m 2 Mg.

2010 ◽  
Vol 1 (1) ◽  
Author(s):  
Ruriko Yoshida

Abstract. Diaconis-Sturmfels developed an algorithm for sampling from conditional distributionsfor a statistical model of discrete exponential families, based on the algebraic theory of toricideals. This algorithm is applied to categorical data analysis through the notion of Markov bases.Initiated with its application to Markov chain Monte Carlo approach for testing statistical fittingof the given model, many researchers have extensively studied the structure of Markov bases formodels in computational algebraic statistics. In the Markov chain Monte Carlo approach fortesting statistical fitting of the given model, a Markov basis is a set of moves connecting allcontingency tables satisfying the given margins. Despite the computational advances, there areapplied problems where one may never be able to compute a Markov basis. In general, the numberof elements in a minimal Markov basis for a model can be exponentially many. Thus, it is importantto compute a reduced number of moves which connect all tables instead of computing a Markovbasis. In some cases, such as logistic regression, positive margins are shown to allow a set ofMarkov connecting moves that are much simpler than the full Markov basis. Such a set is calleda Markov subbasis with assumption of positive margins.In this paper we summarize some computations of and open problems on Markov subbases forcontingency tables with assumption of positive margins under specific models as well as developalgebraic methods for studying connectivity of Markov moves with margin positivity to developMarkov sampling methods for exact conditional inference in statistical models where the Markovbasis is hard to compute.


2019 ◽  
pp. 1362-1366
Author(s):  
Hussein S. Mohammed Hussein ◽  
Abdulrahman H. Majeed

In this paper, The Grobner basis of the Toric Ideal for - contingency tables related with the Markov basis B introduced by Hussein S. MH, Abdulrahman H. M in 2018 is found. Also, the Grobner basis is a reduced and universal Grobner basis are shown.


1993 ◽  
Vol 38 (8) ◽  
pp. 797-798
Author(s):  
Stephen E. Fienberg
Keyword(s):  

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