Your English writing platform
Discover LudwigSuggestions(4)
Exact(3)
Let be the joint probability density function of and.
Let (mathbb {P}_{t}) be the joint probability measure for the collection of random variables {X0,X n,Y n }1≤n≤t.
For two features, { x r,x r + 1}, ranked in order of P ̄ r and P ̄ r + 1 values, let p( x r ) and p(x r + 1) be the probability density functions, and p( x r,x r + 1) be the joint probability density function, where r∈[1,L] is the rank of a feature in X corresponds to an index j in the original feature space.
Similar(56)
where p y, x) is the joint probability distribution.
where is the joint probability density of and.
where g is the joint probability density of ((A^{delta }_{1}(t),X^{delta }_{1}(t))).
where is the joint probability between and, is the conditional probability of sound given concept, and is defined similarly.
where γ is the maximum prime number in A+B and p is the joint probability function on.
where γ is the maximum prime number in 2 · N and p is the joint probability function on.
Here, f Y,h (Y,h) is the joint probability density function of the observations and the channel coefficients.
In addition to the previously introduced notation, π ij is the joint probability of inclusion for unit i and j.
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