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Exact(1)
The goal is to arrive at a formula describing the distribution of possible observations, under the assumption that they were produced while the muscle was in any given mechanical state.
Similar(58)
An actual reference date was assigned for each subject without diabetes by randomly sampling from the subset of subjects with diabetes in the same stratum, thereby ensuring that the distribution of possible observation times for subjects without diabetes corresponded precisely with those of their matched subjects with diabetes.
The basic task of sampling is to draw a representative sample from a universe of possible observations.
Instead, there's a range of possible observations each with a different probability.
Rather, there's a range of possible observations each with a different probability.
According to one interpretation, each of these possible observations corresponds to a different universe (the "multiverse").
Monte Carlo simulations produce distributions of possible outcome values.
A spatial hidden Markov model uses the posterior probability distribution for modeling reservoir categorical variables and the distribution of the possible states F. Given the observations w, the posterior probability is computed by using the following formula { Pr }(f|w) = frac{{{ Pr }(w|f){ Pr }(f)}}{{sumnolimits_{f} {{ Pr }(w|f){ Pr }(f)} }} (6).
Analysis of frequency distribution of the observations also provides information about the character of random processes.
We collect all SLR observations made during a 1-year period from July 2014 to June 2015 to see the ratio of successful ranging observations with respect to all possible observations.
In the common case where one expects an equal distribution of observations among the two groups (E1 = E2 = n/2), this maximum possible value is equal to n (see Methods), making equation (1) correct.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com