The phrase "a given set of variables" is correct and usable in written English.
It can be used when referring to a specific collection of variables that are predetermined or specified in a particular context, often in mathematical, scientific, or programming discussions.
Example: "In this experiment, we will analyze the effects of temperature and pressure on the reaction rate, using a given set of variables."
Alternatives: "a specified group of variables" or "a defined set of variables."
The aim of the present work is to provide a straightforward and simple way to compute the asperity temperature rise for a given set of variables.
Explain the differences among various statistical techniques and identify an appropriate technique for a given set of variables and research questions.
Factor analysis aims at generating a set of orthogonal (uncorrelated) latent variables, the so-called factors, which reproduce the correlation or covariance matrix of a given set of variables as closely as possible.
As a result, our method generates an improved simulation of expert assessments of perceived age for a given set of variables.
The goal of a cluster analysis is to sort cases (here, individual class periods) into an arbitrary number of relatively homogenous clusters based on a given set of variables (here, COPUS codes).
There are several structure learning algorithms that can be used to infer the network structure underlying a given set of correlated variables, assuming that conditional independencies in the joint probability distribution of these variables mirror d-separations in the causal structure (for more details, see [ 6, 23]).
The NIPC expansions provide a means to efficiently and accurately compute statistical information for a given set of input variables with associated probability distribution.
This issue of global or structural identifiability is essential during nonlinear first principles model development where for a given set of measured variables it is desirable to investigate which parameters may be estimated prior to spending computational effort on the actual estimation.
This approach allows modelling the cross-dependencies between a given set of input variables and generating a vector prediction.
This approach allows modelling the cross-dependencies between a given set of input variables and generating a vectorial prediction.
Of the models evaluated, ANN model was best for predicting the release of ADI and total protein for a given set of operating variables.
