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We discuss the data and definite the variables in Data sources and defeinition of variables section.
The rest of the paper proceeds as follows: "PISA 2012 data and variables" section describes data and variables.
The dual problem is simpler to solve and its solution can be used to recover primal variables (Section "Recovery of optimal primal variables") with reduced computational complexity due to the inherently separable structure of the problem Lagrangians (Section "Separability").
The variables used for malaria prediction were described in the earlier Predictor Variables Section.
The control variables specified in Appendix "Control variables" section are themselves model parameters.
For further description of these variables see the outcome variables section below.
We aim to achieve the performance requirement by judicious choice of control variables, defined in Appendix "Control variables" section.
Further models were than adjusted to control for other potentially confounding factors described in the variables section.
Despite the stratification by soil type, data were pooled and soil type used as a candidate variable (See Predictor Variables section).
Drought indices were calculated using monthly rainfall data provided by the Australian Bureau of Meteorology (see Variables section below for more detail on the indices).
Thus, we develop a regression model for midsummer hypoxic area (as determined by LUMCON) using the annual mean stratification effects (Section 2.5) and one or more nutrient variables (Section 2.6).
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