Sentences with phrase «parameter as a probability»

«Representing each parameter as a probability distribution allows us to account for experimental uncertainty, and it also allows us to suss out which parameters are covarying.»

Not exact matches

There's no real progress in our evaluation of climate sensitivity, rather the demonstration that real progress will be very difficut to reach (worse even, the range should enlarge as we include more and more parameters for evaluation of f, so more and more uncertainty because each new parameter will have its own distribution of probability).

This model could be used as a starting point in the development of a GCM parameterization of a the ice mixing - ratio probability distribution function and cloud amount, if a means of diagnosing the depth of the saturated layer and the standard deviation of cloud depth from basic large - scale meterological parameters could be determined.

In the model used by Groisman et al. (1999), the mean total precipitation is also proportional to the shape and scale parameters of the gamma distribution as well as to the probability of precipitation on any given day.

One can easily prove theoretically that the probability that the credible interval based on the posterior CDF will contain the true parameter value will always be exactly as specified, if you average over true parameter values drawn from the prior used to construct the posterior.

Sea ice conditions, such as September extent, maps of sea ice probability and first ice - free day, or any other sea ice parameter based on early - season data.

Where genuine prior information exists, one can suppose that it is equivalent to a notional observation with a certain probability density, from which a posterior density of the parameter given that observationhas been calculated using Bayes» theorem with a noninformative «pre-prior», with the thus computed posterior density being employed as the prior density (Hartigan, 1965).

That the «objective» Bayesian method using Jeffreys» prior will produce perfect probability matching is most easily seen as being due to the general fact that an analysis using the Jeffreys» prior is not affected by applying some monotonic transformation to the parameter (and then interpreting the results as transformed, of course).

A quick answer to your query: A confidence interval is intended to indicate the reliability of an estimate, in terms of the probability that the true value of the parameter being estimated falling below the lower confidence limit, inside the confidence interval, or above its upper limit, as the case may be.