VisualizeDesign {ExploreModelMatrix} | R Documentation |
Given a sample table and a design formula, generate a collection of
static plots for exploring the resulting design matrix graphically.
This function is called internally by ExploreModelMatrix()
, but
can also be used directly if interactivity is not required.
VisualizeDesign( sampleData, designFormula, flipCoordFitted = FALSE, flipCoordCoocc = FALSE, textSizeFitted = 5, textSizeCoocc = 5, textSizeLabsFitted = 12, textSizeLabsCoocc = 12, lineWidthFitted = 25, addColorFitted = TRUE, colorPaletteFitted = scales::hue_pal(), dropCols = NULL, designMatrix = NULL )
sampleData |
A |
designFormula |
A |
flipCoordFitted, flipCoordCoocc |
A |
textSizeFitted, textSizeCoocc |
A |
textSizeLabsFitted, textSizeLabsCoocc |
A |
lineWidthFitted |
A |
addColorFitted |
A |
colorPaletteFitted |
A |
dropCols |
A character vector with columns to drop from the design matrix, or NULL if no columns should be dropped. |
designMatrix |
A |
A list with the following elements:
sampledata
: A data.frame
, expanded from the input
sampleData
plotlist
: A list of plots, displaying the fitted values for
each combination of predictor values, in terms of the model coefficients.
designmatrix
: The design matrix, after removing any columns in
dropCols
pseudoinverse
: The pseudoinverse of the design matrix
vifs
: A data.frame
with calculated variance inflation
factors
colors
: A vector with colors to use for different model
coefficients
cooccurrenceplots
: A list of plots, displaying the
co-occurrence pattern for the predictors (i.e., the number of observations
for each combination of predictor values)
totnbrrows
: The total number of "rows" in the list of plots
of fiitted values. Useful for deciding the required size of the plot canvas.
Charlotte Soneson
VisualizeDesign( sampleData = data.frame(genotype = rep(c("A", "B"), each = 4), treatment = rep(c("treated", "untreated"), 4)), designFormula = ~genotype + treatment )