Sentence examples for marginal distribution p from inspiring English sources

A color histogram-based observation model O t c is obtained through the marginal distribution p ( O t c | S t ).

The pseudo code of Gibbs Sampler is given in Algorithm 3 where the case of three random variables, x, y and z, is considered and the marginal distribution p(x) is of interest to us.

Then, the basic problem is to obtain an estimate of the predictive distribution p y k |y 1 k−1,θ) from the PF we have designed in Section 3.1 and use it in conjunction with p to infer the marginal distribution p(θ|y 1 T ) of interest.

This conclusion is supported by examining the marginal distribution p(r) (Fig. 3b).

However, we stress that the marginal distribution P(x t e ) as defined above is actually a mixture distribution, with the assignment s c determining the mixture component.

Conversely, the marginal distribution p V (x ) (44) p V (x ) = ∫ Σ dΣ   p (x, σ ), is proportional to the total density of MTs that reach the observation point x from the entire boundary.

For the marginal distributions, p = Gamma α0 = 0.5,β0=20), p u)=U 0,1), and p v) is the distribution of the order statistics of m IID U a,b0) random variables.

Hence, the posterior marginal distributions p ( x n, u n | y ) are computable and so are the interesting probabilities p ( x n | y ).

Although the result of this fusion is not necessarily a Markov chain, it is a marginal of a TMC [14] and hence, the posterior marginal distributions p x n | y are computable.

The posterior marginal distributions p ( v n | y ) and p ( x n | y ) can then be computed as follows p ( v n | y ) = α n ( v n ) β n ( v n ) (17).

The joint distribution p ξ, z) is defined in terms of marginal distribution p z) and conditional distribution p(ξ| z) given byp z p(ξ| z).