customize: Plot customization
In SCGLR: Supervised Component Generalized Linear Regression

Parameters used to choose what to plot and how. These parameters are given to plot.SCGLR and pairs.SCGLR.

Parameter name can be abbreviated (e.g. pred.col will be understood as predictors.color).
Options can be set globally using options("plot.SCGLR"). It will then provide default values that can be further overriden by giving explicit parameter value.

*parameter name*	*type (default value). Description.*
`title`	string (NULL). Main title of plot (override built-in).
`labels.auto`	logical (TRUE). Should covariate or predictor labels be aligned with arrows.
`labels.offset`	numeric (0.01). Offset by which labels should be moved from tip of arrows.
`labels.size`	numeric (1). Relative size for labels. Use it to globally alter label size.
`expand`	numeric (1). Expand factor for windows size. Use it for example to make room for clipped labels.
`threshold`	numeric. All covariates and/or predictors whose sum of square correlations with the two components of the plane lower than this threshold will be ignored.
`observations`	logical (FALSE). Should we draw observations.
`observations.size`	numeric (1). Point size.
`observations.color`	character ("black"). Point color.
`observations.alpha`	numeric (1). Point transparency.
`observations.factor`	logical (FALSE). Paint observations according to factor (specify factor).
`predictors`	logical or array of characters (FALSE). Should we draw predictors and optionally which one (TRUE means all).
`predictors.color`	string ("red"). Base color used to draw predictors.
`predictors.alpha`	numeric (1). Overall transparency for predictors (0 is transparent, 1 is opaque).
`predictors.arrows`	logical (TRUE). Should we draw arrows for predictors.
`predictors.arrows.color`	string (predictors.color). Specific color for predictor arrows.
`predictors.arrows.alpha`	numeric (predictors.alpha). Transparency for predictor arrows.
`predictors.labels`	logical (TRUE). Should we draw labels for predictors.
`predictors.labels.color`	string (predictors.color). Specific color for predictor labels.
`predictors.labels.alpha`	numeric (predictors.alpha). Transparency for predictor labels.
`predictors.labels.size`	numeric (labels.size). Specific size for predictor labels.
`predictors.labels.auto`	logical (labels.auto). Should predictor labels be aligned with arrows.
`covariates`	logical or array of characters (TRUE). Should we draw covariates and optionally which one (TRUE means all).
`covariates.color`	string ("black"). Base color used to draw covariates.
`covariates.alpha`	numeric (1). Overall transparency for covariates (0 is transparent, 1 is opaque).
`covariates.arrows`	logical (TRUE). Should we draw arrows for covariates.
`covariates.arrows.color`	string (covariates.color). Specific color for covariate arrows.
`covariates.arrows.alpha`	numeric (covariates.alpha). Transparency for covariate arrows.
`covariates.labels`	logical (TRUE). Should we draw labels for predictors.
`covariates.labels.color`	string (covariates.color). Specific color for predictor labels.
`covariates.labels.alpha`	numeric (covariates.alpha). Transparency for covariate labels.
`covariates.labels.size`	numeric (labels.size). Specific size for covariate labels.
`covariates.labels.auto`	logical (labels.auto). Should covariate labels be aligned with arrows.
`factor`	logical or character (FALSE). Should we draw a factor chosen among additionnal variables (TRUE mean first one).
`factor.points`	logical (TRUE). Should symbol be drawn for factors.
`factor.points.size`	numeric (4). Symbol size.
`factor.points.shape`	numeric (13). Point shape.
`factor.labels`	logical (TRUE). Should factor labels be drawn.
`factor.labels.color`	string ("black"). Color used to draw labels.
`factor.labels.size`	numeric (labels.size). Specific size for factor labels.

## Not run: 
# setting parameters
plot(genus.scglr)
plot(genus.scglr, predictors=TRUE)
plot(genus.scglr, predictors=TRUE, pred.arrows=FALSE)

# setting global style
options(plot.SCGLR=list(predictors=TRUE, pred.arrows=FALSE))
plot(genus.scglr)

# setting custom style
myStyle <- list(predictors=TRUE, pred.arrows=FALSE)
plot(genus.scglr, style=myStyle)

## End(Not run)