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Exact(34)
Let be the random variable (r.v).
Let be the random variable such that.
Let Y be the random variable representing shadow fading.
Let X be the random variable representing this distribution.
Let N be the random variable "number of individuals in the firm waiting or being served".
Let be the random variable denoting the path loss of the desired link.
Similar(25)
In addition, let be the random variables with two-point distribution (2.2). where.
Let X and Y be the random variables described by the cluster assignments and class labels.
Assuming and, χ=α+β is the random variable of.
where E is the expectation operator and V is the random variable representing the vehicle speed.
where is the random variable modeling the Gaussian noise with mean and a standard deviation of.
More suggestions(18)
be the main variable
be the big variable
be the dependent variable
be the elusive variable
be the key variable
be the new variable
be the exclusive variable
be the same variable
be the tunable variable
be the influential variable
be the only variable
be the independent variable
be the central variable
be the prime variable
be the explanatory variable
be the symmetrical variable
be the critical variable
be the primary variable
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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