Your English writing platform
Discover LudwigSuggestions(5)
Exact(59)
In both cases, z ij T is a vector of covariates, and G denotes the positive definite covariance matrix of the random effects.
Let z(t) = (x t), d 1 t), d 2 t)) denote the vector of covariates.
where Z is a vector of covariates in the scale function.
Xit represents a vector of covariates likely to affect access or cost.
Assume further that x it = (x 1t, …, x rt ) denote a vector of covariates.
Following Rosenbaum (1989), consider the problem of matching a treated unit to a control unit on a vector of covariates.
The first aspect is based on the notion of close matching in terms of a distance measure on the vector of covariates – for example, nearest neighbor matching.
where X i is the same vector of covariates as in Equation 1 and ε i is an error term with zero conditional mean.
where x i is a 1 × k vector of covariates (including intercept) that characterizes the study i and β is a k × 1 coefficient vector.
Given that this procedure requires including a very long vector of covariates, we select them according to the procedure suggested by Belloni et al. (2014).
These form a family of artificial neural networks, for which each neuron (a vertex on a lattice graph) carries a vector of covariates initialized to random values.
More suggestions(1)
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