Sentence examples for marginal probability for from inspiring English sources

Here P1(b) is a marginal probability for a single fixed symbol to have tally b.

Fig. 10 Scatter plots of the estimates using the EM algorithm against MLE with the marginal probability for 100 repetitions.

Model 1 used an approximation of the marginal probability for each mention, that is, the probability that the mention is correct, to calculate the probability that the mention appears at least once in the abstract.

The most likely ancestral state of each site is then chosen by evaluating the marginal probability for each state.

Our question is how to effectively estimate the marginal probability for the given orthologous species sequence set without knowing the genotype of the ancestor and/or root.

The marginal probability for each node of this model thus becomes: (6) P (X [ t ] | X [ t − 1 ], …, X [ t − d ] ) = ∏ i = 1 n P (X i [ t ] | Pa (X i [ t ] ) ) The term Pa(X i [ t]) in the above equation represents the parents of gene X i at time t, which can be in the same time-slice or in one of the d previous time-slices (d is the maximum order of regulation) of gene X i at time t.

Whilst we discuss more readily interpretable marginal probabilities for selected results from the base model in detail shortly, it is worth noting here that we consistently find that couples are significantly less likely to migrate if the couple own (purchased or currently paying a mortgage on) their house across the three specifications in Table 3.

The cell and marginal probabilities for this cross-classification are shown in Tables 5 and 6.

The cell and marginal probabilities for this cross-classification are shown in Tables 3 and 4. We obtain the probabilities in two steps.

The marginal probabilities for the female and male are displayed in Table 2 and are plotted in Figure S1, B and C. The oscillations in the male X chromosome probabilities are interesting, but not particularly surprising.

Still, using equation 4 to compute marginal probabilities for N unknown genotypes of individual i requires recomputing the likelihood with g i = x for each of the N values of x.