revdep/checks.noindex/ggResidpanel/old/ggResidpanel.Rcheck/ggResidpanel-Ex.R

In aloy/qqplotr: Quantile-Quantile Plot Extensions for 'ggplot2'

pkgname <- "ggResidpanel"
source(file.path(R.home("share"), "R", "examples-header.R"))
options(warn = 1)
library('ggResidpanel')

base::assign(".oldSearch", base::search(), pos = 'CheckExEnv')
base::assign(".old_wd", base::getwd(), pos = 'CheckExEnv')
cleanEx()
nameEx("resid_auxpanel")
### * resid_auxpanel

flush(stderr()); flush(stdout())

### Name: resid_auxpanel
### Title: Panel of Diagnostic Residual Plots.
### Aliases: resid_auxpanel

### ** Examples


# Fit a regression tree to the penguins data
penguin_tree <- rpart::rpart(heartrate ~ depth + duration, data = penguins)

# Obtain the predictions from the model on the observed data
penguin_tree_pred <- predict(penguin_tree)

# Obtain the residuals from the model
penguin_tree_resid <- penguins$heartrate - penguin_tree_pred

# Create a panel with the residual and index plot
resid_auxpanel(residuals = penguin_tree_resid,
             predicted = penguin_tree_pred,
             plots = c("resid", "index", "yvp"))



cleanEx()
nameEx("resid_compare")
### * resid_compare

flush(stderr()); flush(stdout())

### Name: resid_compare
### Title: Panel of Diagnostic Residual Plots Across Multiple Models.
### Aliases: resid_compare

### ** Examples


# Fit two models to the penguins data
penguin_model <- lme4::lmer(heartrate ~ depth + duration + (1|bird), data = penguins)
penguin_model_log2 <- lme4::lmer(log(heartrate) ~ depth + duration + I(duration^2) +
(1|bird), data = penguins)

# Compare the residuals from the model
resid_compare(list(penguin_model, penguin_model_log2))

# Adjust some options in the panel of plots
resid_compare(list(penguin_model, penguin_model_log2), plots = c("resid", "yvp"),
smoother = TRUE, theme = "grey")



cleanEx()
nameEx("resid_interact")
### * resid_interact

flush(stderr()); flush(stdout())

### Name: resid_interact
### Title: Panel of Interactive Versions of Diagnostic Residual Plots.
### Aliases: resid_interact

### ** Examples


# Fit a model to the penguin data
penguin_model <- lme4::lmer(heartrate ~ depth + duration + (1|bird), data = penguins)

# Create the default interactive panel
resid_interact(penguin_model)

# Select all plots to include in the panel and set the smoother option to TRUE
resid_interact(penguin_model, plots = "all", smoother = TRUE)

# Select only the residual plot and qq-plot to be included in the panel and
# set the number of rows to 2
resid_interact(penguin_model, plots = c("resid", "qq"), nrow = 2)

# Choose the SAS panel of plots, change the theme to classic, and remove the
# titles of the plots
resid_interact(penguin_model, plots = "SAS", theme = "classic", title.opt = FALSE)



cleanEx()
nameEx("resid_panel")
### * resid_panel

flush(stderr()); flush(stdout())

### Name: resid_panel
### Title: Panel of Diagnostic Residual Plots.
### Aliases: resid_panel

### ** Examples


# Fit a model to the penguin data
penguin_model <- lme4::lmer(heartrate ~ depth + duration + (1|bird), data = penguins)

# Create the default panel
resid_panel(penguin_model)

# Select all plots to include in the panel and set the smoother option to TRUE
resid_panel(penguin_model, plots = "all", smoother = TRUE)

# Select only the residual plot and qq-plot to be included in the panel,
# request confidence bands on the qq plot, and set the number of rows to 2
resid_panel(penguin_model, plots = c("resid", "qq"), qqbands = TRUE, nrow = 2)

# Choose the SAS panel of plots, change the theme to classic, and remove the
# titles of the plots
resid_panel(penguin_model, plots = "SAS", theme = "classic", title.opt = FALSE)



cleanEx()
nameEx("resid_xpanel")
### * resid_xpanel

flush(stderr()); flush(stdout())

### Name: resid_xpanel
### Title: Panel of Plots of Residuals or Response Variable versus
###   Predictor Variables.
### Aliases: resid_xpanel

### ** Examples


# Fit a model to the penguin data
penguin_model <- lme4::lmer(heartrate ~ depth + duration + (1|bird), data = penguins)

# Create plots of the residuals versus the predictor variables
resid_xpanel(penguin_model, theme = "classic")

# Create plots of the response variable versus the predictor variables
resid_xpanel(penguin_model, yvar = "response", theme = "classic", smoother = TRUE)



### * <FOOTER>
###
cleanEx()
options(digits = 7L)
base::cat("Time elapsed: ", proc.time() - base::get("ptime", pos = 'CheckExEnv'),"\n")
grDevices::dev.off()
###
### Local variables: ***
### mode: outline-minor ***
### outline-regexp: "\\(> \\)?### [*]+" ***
### End: ***
quit('no')