Exact(1)
So, if one has sequences of measurements of the gravitational constant from the Earth, the Moon, the 7 other planets, and, say, the Cavendish balance 10 sequences in total and in all cases except for Mercury, the gravitational constant is within some small value ε of g, then the higher order probability of the posit that the true value of the gravitational constant is within ε of g is 9/10.
Similar(59)
However, because we condition on exactly one or zero causal variants, these higher order probabilities need never be used.
Here the authors utilize the formalism of stochastic processes to develop a statistical definition of microstructure and develop measures of structural variance in terms of the measured variance of estimators of higher order probability distributions.
Most statistical based homogenization methods are limited to two-point probability function due to the lack of simple approximation of higher order probability functions that can be easily exploited.
However, second and higher order probability functions include the information of phase distribution and morphology.
The higher order conditional probability densities are complicated functions, and therefore one usually assumes a Markov chain.
However, cutoffs can be used to exclude the higher order terms, if their probability of occurrence becomes very small.
Unsung D.C. fiction of the higher order.
A model of higher-order probability consists of W, a set of possible worlds, together with a function that assigns to each world w a probability function μw.
Whether one agrees with the principles proposed in the literature on higher-order probabilities or not, the ability to represent them forces one to investigate the principles governing them.
The importance of higher-order probabilities is clear from the role they play in, for example, Miller's principle, which states that P1(ϕ | P2 = b) = b.
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