Sequential assumptions

Biclustering is a critical task for biomedical applications. Order-preserving biclusters, submatrices where the values of rows induce the same linear ordering across columns, capture local regularities with constant, shifting, scaling and sequential assumptions.

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The crucial assumption that allows as to solve the two-good model relatively simply is the ability of the shoppers to combine purchases from two stores without incurring additional cost. This assumption can be justied for internet shopping or the cases when as Stahl, II (1989) puts it \Casual empiricism suggests that there is a non-negligible measure of consumers who seem to derive enjoyment from shopping itself".

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More Topics in Linear Unobserved E¤ects Models This chapter continues our treatment of linear, unobserved e¤ects panel data models. We first cover estimation of models where the strict exogeneity Assumption FE.1 fails but sequential moment conditions hold. A simple approach to consistent estimation involves differencing combined with instrumental variables methods.

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