Your English writing platform
Discover LudwigSuggestions(1)
Exact(1)
A MJP is a family of discrete random variables indexed by time; it is characterised by its transition rates f (x'|x) defined as (3) Another important quantity is the marginal distribution p t (x) that the system is in a particular state at a certain time t.
Similar(59)
A color histogram-based observation model O t c is obtained through the marginal distribution p ( O t c | S t ).
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.
(S(T)) is related to the probability distribution (p(T)) with (p(T) = -dS(T /dT).
This conclusion is supported by examining the marginal distribution p(r) (Fig. 3b).
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.
Here: sample I. Figure 13 Marginal angular distribution p ˘ θ ( C T ) , p ˘ θ ( M ).
Here: sample II. Figure 14 Marginal angular distribution p ˘ α ( C T ) , p ˘ α ( M ).
Here: surrogate model, sample II. Figure 12 Marginal angular distribution p ˘ θ ( C T ) , p ˘ θ ( M ).
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com