plot.hdpGLM: Plot
In hdpGLM: Hierarchical Dirichlet Process Generalized Linear Models

plot.hdpGLM

R Documentation

Plot

Description

Generic function to plot the posterior density estimation produced by the function hdpGLM

Usage

## S3 method for class 'hdpGLM'
plot(
  x,
  terms = NULL,
  j.label = NULL,
  j.idx = NULL,
  title = NULL,
  subtitle = NULL,
  true.beta = NULL,
  ncol = NULL,
  legend.position = "bottom",
  display.terms = TRUE,
  context.id = NULL,
  ylab = NULL,
  xlab = NULL,
  x.axis.size = 1.1,
  y.axis.size = 1.1,
  title.size = 1.2,
  panel.title.size = 1.5,
  legend.size = 1.1,
  rel.height = 0.01,
  fill.col = "#00000044",
  border.col = "white",
  ...
)

Arguments

`x`	an object of the class `hdpGLM` generted by the function hdpGLM
`terms`	string vector with the name of the individual-level covariates to plot. If `NULL` (default), all covariates are plotted.
`j.label`	string vector with the names of the contexts to plot. An alternative is to use the context indexes with the parameter `j.idx` instead of the context labels. If `NULL` (default) and j.idx is also `NULL`, the posterior distribution of all contexts are plotted. Note: if contexts to plot are selected using `j.label`, the parameter `context.id` must also be provided.
`j.idx`	integer vector with the index of the contexts to plot. An alternative is to use the context labels with the parameter `j.label` instead of the indexes. If `NULL` (default) and j.label is also `NULL`, the posterior distribution of all contexts are plotted
`title`	string, the title of the plot
`subtitle`	string, the subtitle of the plot
`true.beta`	a `data.frame` with the true values of the linear coefficients `beta` if they are known. The `data.frame` must contain a column named `j` with the index of the context associated with that particular linear coefficient `beta`. It must match the indexes used in the data set for each context. Another column named `k` must be provided, indicating the cluster of `beta`, and a column named `Parameter` with the name of the linear coefficients (`beta1`, `beta2`, ..., `beta_dx`, where `dx` is the number of covariates at the individual level, and beta1 is the coefficient of the intercept term). It must contain a column named `True` with the true value of the `betas`. Finally, the `data.frame` must contain columns with the context-level covariates as used in the estimation of the hdpGLM function (see Details below).
`ncol`	interger, the number of columns in the plot
`legend.position`	one of four options: "bottom" (default), "top", "left", or "right". It indicates the position of the legend
`display.terms`	boolean, if `TRUE` (default), the covariate name is displayed in the plot
`context.id`	string with the name of the column containing the labels identifying the contexts. This variable should have been specified when the estimation was conducted using the function `hdpGLM`.
`ylab`	string, the label of the y-axis
`xlab`	string, the label of the x-axis
`x.axis.size`	numeric, the relative size of the label in the x-axis
`y.axis.size`	numeric, the relative size of the label in the y-axis
`title.size`	numeric, the relative size of the title of the plot
`panel.title.size`	numeric, the relative size of the titles in the panel of the plot
`legend.size`	numeric, the relative size of the legend
`rel.height`	see ggridges::geom_density_ridges
`fill.col`	string with the color of the densities
`border.col`	string with the color of the border of the densities
`...`	Additional arguments accepted are: `true.beta`: a `data.frame` with the true values of the linear coefficients `beta` if they are known. The `data.frame` must contain a column named `j` with the index of the context associated with that particular linear coefficient `beta`. It must match the indexes used in the data set for each context. Another column named `k` must be provided, indicating the cluster of `beta`, and a column named `Parameter` with the name of the linear coefficients (`beta1`, `beta2`, ..., `beta_dx`, where `dx` is the number of covariates at the individual level, and beta1 is the coefficient of the intercept term). It must contain a column named `True` with the true value of the `betas`. Finally, the `data.frame` must contain columns with the context-level covariates as used in the estimation of the hdpGLM function (see Details below). `true.tau`: a `data.frame` with four columns. The first must be named `w` and it indicates the index of each context-level covariate, starting with 0 for the intercept term. The second column named `beta` must contain the indexes of the betas of individual-level covariates, starting with 0 for the intercept term. The third column named `Parameter` must be named `tau<w><beta>`, where `w` and `beta` must be the actual values displayed in the columns `w` and `beta`. Finally, it must have a column named `True` with the true value of the parameter.