Sentence examples for type of predictor from inspiring English sources

We tested models using every combination of species-specific or shared effects for each type of predictor, as well as every combination with or without environment and competition effects (36 models in total).

To determine the final model form we generated a set of models which allows us to test whether each type of predictor should be species-specific or shared, and whether the extra model complexity added by including environmental and competition effects in the simple size model was justified by the improvement in fit.

Completely specifying the predictor means specifying all of these aspects of the predictor, the type of predictor, the genes included and the values of all parameters.

The results from both sets of analyses, 'Performance' (sensitivity and precision) and 'Agreement' (common hits), are reported in the following sections devoted to each type of predictor.

The absolute cortical regression weights for each type of predictor were averaged to create single maps for HMaxC1, HMaxC2, and semantic information.

As mentioned before, a completely different type of predictor uses keywords of protein preexisting annotations from databases such as SWISS-PROT to assess subcellular localization.

The Adams-Bashforth-Moulton method is a type of predictor-corrector methods and a relatively new approach to provide a numerical approximation to solve the fractional order differential equations.

However, a more severe problem exists when analyzing such disaster-related data because there is always a lack of information and/or data available describing such disasters is inaccurate and of poor quality; thus, the types of predictor variables available are not exhaustive.

These steps gave us for types of predictor variable: the constant α (Eqn (2)), dbh (Eqn (3)), the set of five non-linear environmental effects (Eqn (5)) and the non-linear competition effect (plot basal area: Eqn (7)).

Regression trees have several advantages as a modeling technique, including that various types of predictor and response variables can be analyzed simultaneously rather than in an iterative manner, missing values in data sets can be incorporated and therefore information loss minimized, and complex interactions between predictors can be quantified and modeled in a simple manner [44].

Two types of predictor attributes derived from those PPIs were used.