For a regression model θ = β, σ2, all probabilities are implicitly conditional on the set of all models being considered.
Because there are two different treatments, contract and cooperatives, that are mutually exclusive1, a bivariate probit model is used to estimate the probability for each treatment, conditional on the set of covariates X (Lechner 1999 , 2002.
This procedure enables to determine how many peaks of similar height might arise by chance conditional on the set of phenotypes being analysed, the marker map and the family structure.
We considered a Monte Carlo inference conditional on the set of all locations and on the local number of subjects.
Naive Bayes: classifiers calculate the posterior probability of the example label conditional on the set of observed features, under the (often unrealistic) assumption that features are independent.
In this way, the simulations assessed spatial variations in the local proportion of cases conditional on the set of all locations.
Several types of classifiers were trained on each type of feature sets (see Section 2 for details on training and parameter tuning): Naive Bayes: classifiers calculate the posterior probability of the example label conditional on the set of observed features, under the (often unrealistic) assumption that features are independent.
Compared to the socially efficient mechanism, the optimal mechanism features fewer participants, longer search conditional on the same set of participants, and inefficient sequence of entry.
Thus the expected value of the project conditional on the information set to date is positive if and only if the manager's quality is Good.
In other words, we require that probabilities of different values of parameters conditional on the same set of measurements are different.
The GPS is defined as the conditional probability of receiving a particular level of treatment 't' (hours of training) conditional on the same set of baseline covariates X used in section 6.1.
