Sentence examples for marginal probabilities and from inspiring English sources

3.00 2.54 3.90 Medicare part B payment ratio 10.77 3.42 2.05 *All calculated marginal probabilities and elasticities are based on coefficients that are statistically significant at p < .01.01

Table 3 Marginal probabilities and elasticities* of key policy variables: Percent change in dependent variable for a 10% increase in the independent variable   Cataract Knee degeneration Benign prostatic neoplasm Percent surgical episodes (mean) 17.9%14.0%6.9999% PCPs per 1000 pop.

The mutual information measures the dependency between two random variables and is mathematically defined as Ileft(X Yright)=sum_{xin varOmega}sum_{yin varOmega }Pleft x,yright){mathrm{log}}_2frac{Pleft x,yright)}{P x P y)}, (1 where P x) and P y) are the marginal probabilities and P x, y) is the joint probability and Ω is the set of nucleotides {A, C, G, U}.

We report both predicted marginal probabilities and odds ratios.

We calculated predicted marginal probabilities and 95% CIs in multivariate models.

Additional File 1 shows the predicted marginal probabilities and odds ratios of the legal variables and control variables on the use of diabetes preventive care measures considered.

The prior probability distribution is a necessary input in calculating the marginal probability and posterior probability.

An interesting anomaly with this approach is that the marginal probability, and subsequently the information content, of a single term (i.e. consistent graph with a single leaf term) calculated from a Bayesian network does not necessarily match the relative term frequency in the database (instead, the conditional probability tables are estimated as relative frequencies).

Bayes' theorem relates the conditional and marginal probabilities of events and, and it is expressed as (5).

Then we need the marginal probabilities, p q) and p(m) of the position and move occurring respectively.

The simulated data allow the estimation of two marginal probabilities, qj and ri say, the first giving a measure of the performance of each rater j (i.e. the probability of the rater being in the majority for a sample chosen at random) and the second giving a measure of the difficulty associated with grading each sample i (i.e. the proportion of raters giving the consensus grade for the sample).