Sentence examples for a likelihood distribution from inspiring English sources

Analyses within the Bayesian framework involve data, a likelihood distribution, parameters, a model, and a prior distribution [ 15].

Analyses within the Bayesian framework involve data, a likelihood distribution, a model with parameters, and prior distributions for these parameters.

Within a Bayesian framework, analysis involves data, a likelihood distribution, a model with parameters, and prior distributions for these parameters [ 33].

As a result of this transformation, each descriptor in the taxonomic set has a likelihood distribution S comprising an S < 1 and an S = 1 fraction.

For each distribution, the probability that the descriptor takes a value less than or equal to a specified value was calculated as the cumulative distribution function (CDF) and transformed into a likelihood distribution function (LDF).

This approach combines a prior probability distribution (representing a prior belief of the possible values for parameter) with a likelihood distribution of the observed effect, resulting in a posterior probability distribution [ 12].

A regression model with a normal likelihood distribution relates the data from the individual studies to basic parameters reflecting the (pooled) treatment effect of each intervention compared to placebo.

We study the problem of projecting a distribution onto (or finding a maximum likelihood distribution among) Markov networks of bounded tree-width.

A binomial likelihood distribution of the incident events for every interval can be described according to: (10) r jkt ~ b i n p jkt, n jkt Where r jkt is the observed number of events in the mth interval ending at time point t m +1 for treatment k in study j.

A binomial likelihood distribution was used for the incident number of deaths for every two month interval, which was calculated based on the survival percentages from the Kaplan-Meier curves and the number of patients at risk at the beginning of the interval in each arm of each study, assuming a constant hazard rate within each interval (see Jansen and Cope [ 16] for more details).

In this analysis, a linear model with normal likelihood distribution was used for continuous outcomes and a Poisson likelihood with a log link was used for the dichotomous outcomes [ 31, 32].