emdi (version 1.1.1)

plot.emdi: Plots for an emdi object

Description

Diagnostic plots of the underlying model in the EBP approach (see also ebp) are obtained. These include Q-Q plots and density plots of residuals and random effects from the nested error regression model, a Cook's distance plot for detecting outliers and the log-likelihood of the estimation of the optimal parameter in Box-Cox transformations. The return depends on the transformation such that a plot for the optimal parameter is only returned in case a Box-Cox transformation is chosen. The range of the x-axis is optional but necessary to change if there are convergence problems. All plots are obtained by ggplot.

Usage

# S3 method for emdi
plot(x, label = "orig", color = c("blue", "lightblue3"),
  gg_theme = NULL, cooks = TRUE, range = NULL, ...)

Arguments

x

an object of type "emdi", "model", representing point and, if chosen, MSE estimates obtained by the EBP approach (see also ebp).

label

argument that enables to customize title and axis labels. There are four options to label the diagsnostic plot: (i) original labels ("orig"), (ii) axis lables but no title ("no_title"), (iii) neither axis labels nor title ("blank"), (iv) individual labels by a list that needs to have below structure. Six elements can be defined called qq_res, qq_ran, d_res, d_ran, cooks and box_cox for the six different plots and these list elements need to have three elements each called title, y_lab and x_lab. Only the labels for the plots that should be different to the original need to be specified.

list(

qq_res =

c(title="Error term", y_lab="Quantiles of pearson residuals", x_lab="Theoretical quantiles"),

qq_ran =

c(title="Random effect", y_lab="Quantiles of random effects", x_lab="Theoretical quantiles"),

d_res =

c(title="Density - Pearson residuals", y_lab="Density", x_lab="Pearson residuals"),

d_ran =

c(title="Density - Standardized random effects", y_lab="Density", x_lab="Standardized random effects"),

cooks =

c(title="Cook's Distance Plot", y_lab="Cook's Distance", x_lab="Index"),

box_cox =

c(title="Box-Cox - REML", y_lab="Log-Likelihood", x_lab="expression(lambda)"))

color

a character vector with two elements. The first element defines the color for the line in the QQ-plots, for the Cook's Distance plot and for the Box-Cox plot. The second element defines the color for the densities.

gg_theme

theme list from package ggplot2.

cooks

if TRUE, a Cook's distance plot is returned. The used method cooks.distance.lme struggles when data sets get large. In these cases, cooks should be set to FALSE. It defaults to TRUE.

range

optional sequence determining the range of the x-axis for plots of the optimal parameter that defaults to NULL. In that case a range of the optimal parameter +2/-1 is used for the plots of the optimal parameter. This leads in some cases to convergence problems such that is should be changed to e.g. the selected interval. This means for the default interval seq(-1, 2, by = 0.05).

...

optional arguments passed to generic function.

Value

Two Q-Q plots in one grid, two density plots, a Cook' distance plot and a likelihood plot for the optimal parameter of the Box-Cox transformation obtained by ggplot.

See Also

emdiObject, ebp

Examples

# NOT RUN {
# Loading data - population and sample data
data("eusilcA_pop")
data("eusilcA_smp")

# With default setting but na.rm = TRUE; with Box-Cox transformation
emdi_model <- ebp(fixed = eqIncome ~ gender + eqsize + cash + self_empl + 
unempl_ben + age_ben + surv_ben + sick_ben + dis_ben + rent + fam_allow + 
house_allow + cap_inv + tax_adj, pop_data = eusilcA_pop,
pop_domains = "district", smp_data = eusilcA_smp, smp_domains = "district", 
na.rm = TRUE)

# Example 1: Creation of default diagnostic plots
plot(emdi_model)

# Example 2: Creation of diagnostic plots without labels and titles, different colors 
# and without Cook's distance plot.
plot(emdi_model, label = "no_title", color = c("red", "yellow"), cooks = FALSE)

# Example 3: Creation of diagnostic plots where labels and title differs for 
# residual plot
plot(emdi_model, label = list(qq_res = c(title = "Pearson resid.", 
y_lab = "Quant.", x_lab = "Theo. Quant.")), color = c("red", "yellow"), 
cooks = FALSE)

# }