Sentence examples for adequate probability from inspiring English sources

In this paper, we introduce and study the class of Bernoulli probability measures that we claim to be the simplest adequate probability measures on infinite traces.

SMC methods allow to recursively approximate the a posteriori probabilities of the transmitted symbols, as observations are sequentially collected, using samples from adequate probability distributions.

Consequently, we deduced analogous results in the light of the well-known Zipf Mandelbrot law, with the adequate probability mass functions and the adjusted form of the Csiszár functional.

Furthermore, for high fractions of censored data (as in single-cell qPCR), it is not clear how to derive adequate probability distributions (Ballenberger et al., 2012; Lubin et al., 2004).

If a patient is informed in detail, this protocol seems to have an adequate success probability and treatment of choice for specific situations and patient's need.

In addition, the observed transmission pairs and trios of Slovenian patients were also confirmed, with the exception of one trio, which did not reach an adequate posterior probability (0.8455).

We recommend that hypothesis testing analyses include no more than one or two prespecified subgroup analyses founded on adequate prior probability and power so that positive findings are more reliable and can thus be used to target treatment.

Our simulation results suggest that the superpopulation variance estimator [ 13] provides adequate coverage probabilities of the CI when using the time-dependent weights proposed in the WC model to estimate the effect of time-varying exposures in case-control studies.

Recently, Hájek (2007) has argued that no adequate conception of probability is immune to a reference class problem, so that this requirement cannot be met.

Although we assumed the ranges of validation data to be adequate for our probability distributions, we were not 100% confident in the distributions' shapes.

The presented approach considers control-oriented experiment design to ensure adequate model adaptation (in probability) in terms of an admissible control performance level.