Factorial domains

Factorial Design

Factorial Anova

But these experiments [2] will not give us any information about the dependence or independence of the two factors, namely study habit and home environment. In such cases, we resort to Factorial ANOVA which not only helps us to study the effect of two or more factors but also gives information about their dependence or independence in the same experiment. There are many types of factorial desig...

Factorial Anova

But these experiments [2] will not give us any information about the dependence or independence of the two factors, namely study habit and home environment. In such cases, we resort to Factorial ANOVA which not only helps us to study the effect of two or more factors but also gives information about their dependence or independence in the same experiment. There are many types of factorial desig...

The Strong Factorial Conjecture

In this paper, we present an unexpected link between the Factorial Conjecture ([8]) and Furter’s Rigidity Conjecture ([13]). The Factorial Conjecture in dimension m asserts that if a polynomial f in m variables Xi over C is such that L(f) = 0 for all k ≥ 1, then f = 0, where L is the C-linear map from C[X1, · · · , Xm] to C defined by L(X l1 1 · · ·X lm m ) = l1! · · · lm!. The Rigidity Conject...

Factorial Markov Random Fields

In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous to the extension from Hidden Markov Models (HMM’s) to Factorial HMM’s. We present an efficient EM-based algorithm for inference on Factorial MRF’s. Our algorithm makes use of the fact that layers are a priori independe...