Sentence examples for prior commonly from inspiring English sources

Other than the flat prior commonly used in Bayesian inference, prior information for the sojourn density could be estimated from annotation or previous studies, thus it can be effectively utilized together with positional information of features to guide the estimation of the most likely state sequence.

Finally, although the analyses presented here used Gaussian priors for marker effects, the multi-threshold model used in this study can be implemented with any of the priors commonly used in GS, including those that induce differential shrinkage of estimates of effects or a combination of variable selection and shrinkage.

Given their latency, prior investigations commonly use a time-lagged design of consecutive stressor exposition and data recording.

The spike slab prior is commonly formed by mixing two normal densities.

Two types of prior are commonly employed, Laplace (sparse data and less features) and Gaussian (approximate normal distribution).

Moreover, prior studies commonly relied on a variety of self-report surveys which are known to overestimate the prevalence of depression [ 5].

Although such priors are commonly obtained through a pilot study, in this paper we provide a simple alternative in which the analyst depends only on their own expert judgement and possibly on parameter estimates obtained from the literature.

In contrast, subgroup analyses with low priors are commonly conducted, perhaps because they are perceived as being essentially free, but as is shown below, conducting multiple subgroup analyses is statistically costly.

Thus, we cannot exclude the alternative hypothesis that the species highly represented in zoos worldwide have better chance to be preferred by the respondents because of their higher rate of prior experience with commonly exhibited species.

In addition to the standard attribute distance measures, we have also introduced attribute distances based on prior knowledge of commonly occurring mistakes.

In short, an appealing property of ANN is that they do not require most of the prior assumptions that commonly underlie parametric statistical models.