eta_cov: This creates an ETA covariance matrix which can be used to...

In ggPMX: 'ggplot2' Based Tool to Facilitate Diagnostic Plots for NLME Models

This creates an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage..

Description

This creates an ETA covariance matrix which can be used to define the co-relation between the parameters and its shrinkage..

Usage

eta_cov(
  labels,
  type = c("cats", "conts"),
  dname = NULL,
  show.correl = TRUE,
  correl = NULL,
  facets = NULL,
  point = NULL,
  covariates = NULL,
  is.strat.color = FALSE,
  ...
)

Arguments

labels	list of texts/titles used within the plot
type	box for cats or conts
dname	name of dataset to be used
show.correl	logical if TRUE add correlation to the plot
correl	list correl geom text graphical parameter
facets	list facetting graphical parameter
point	list geom point graphical parameter
covariates	pmxCOVObject pmx_cov
is.strat.color	logical if 'TRUE' use a different color for the spline stratification.
...	others graphics arguments passed to pmx_gpar internal object.

Details

labels is a list that contains:

• title: plot title default "EBE vs. covariates"

• x: x axis label default to "Etas"

• y: y axis label default to empty

Value

eta_cov object

See Also

Other plot_pmx: distrib(), eta_pairs(), individual(), plot_pmx.distrib(), plot_pmx.eta_cov(), plot_pmx.eta_pairs(), plot_pmx.individual(), plot_pmx.pmx_dens(), plot_pmx.pmx_gpar(), plot_pmx.pmx_qq(), plot_pmx.residual(), plot_pmx()

ggPMX documentation built on May 29, 2024, 1:40 a.m.