plot_sim_pdf_ext: Plot Simulated Probability Density Function and Target PDF of...
In SimMultiCorrData: Simulation of Correlated Data with Multiple Variable Types

Description Usage Arguments Value References See Also Examples

This plots the pdf of simulated continuous or count data and overlays the target pdf computed from the given external data vector. The external data is a required input. The simulated data is centered and scaled to have the same mean and variance as the external data set. If the user wants to only plot simulated data, plot_sim_theory should be used instead (with overlay = FALSE). It returns a ggplot2-package object so the user can modify as necessary. The graph parameters (i.e. title, power_color, target_color, target_lty) are ggplot2-package parameters. It works for valid or invalid power method pdfs.

plot_sim_pdf_ext(sim_y, title = "Simulated Probability Density Function",
  ylower = NULL, yupper = NULL, power_color = "dark blue", ext_y = NULL,
  target_color = "dark green", target_lty = 2, legend.position = c(0.975,
  0.9), legend.justification = c(1, 1), legend.text.size = 10,
  title.text.size = 15, axis.text.size = 10, axis.title.size = 13)

`sim_y`	a vector of simulated data
`title`	the title for the graph (default = "Simulated Probability Density Function")
`ylower`	the lower y value to use in the plot (default = NULL, uses minimum simulated y value)
`yupper`	the upper y value (default = NULL, uses maximum simulated y value)
`power_color`	the histogram color for the simulated variable (default = "dark blue")
`ext_y`	a vector of external data (required)
`target_color`	the histogram color for the target pdf (default = "dark green")
`target_lty`	the line type for the target pdf (default = 2, dashed line)
`legend.position`	the position of the legend
`legend.justification`	the justification of the legend
`legend.text.size`	the size of the legend labels
`title.text.size`	the size of the plot title
`axis.text.size`	the size of the axes text (tick labels)
`axis.title.size`	the size of the axes titles

A ggplot2-package object.

Please see the references for plot_cdf.

Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2009.

ggplot2-package, geom_density

## Not run: 
# Logistic Distribution: mean = 0, variance = 1

seed = 1234

# Simulate "external" data set
set.seed(seed)
ext_y <- rlogis(10000)

# Find standardized cumulants
stcum <- calc_theory(Dist = "Logistic", params = c(0, 1))

# Simulate without the sixth cumulant correction
# (invalid power method pdf)
Logvar1 <- nonnormvar1(method = "Polynomial", means = 0, vars = 1,
                      skews = stcum[3], skurts = stcum[4],
                      fifths = stcum[5], sixths = stcum[6],
                      n = 10000, seed = seed)

# Plot pdfs of simulated variable (invalid) and external data
plot_sim_pdf_ext(sim_y = Logvar1$continuous_variable,
                 title = "Invalid Logistic Simulated PDF", ext_y = ext_y)

# Simulate with the sixth cumulant correction
# (valid power method pdf)
Logvar2 <- nonnormvar1(method = "Polynomial", means = 0, vars = 1,
                      skews = stcum[3], skurts = stcum[4],
                      fifths = stcum[5], sixths = stcum[6],
                      Six = seq(1.5, 2, 0.05), n = 10000, seed = 1234)

# Plot pdfs of simulated variable (valid) and external data
plot_sim_pdf_ext(sim_y = Logvar2$continuous_variable,
                 title = "Valid Logistic Simulated PDF", ext_y = ext_y)

# Simulate 2 Poisson distributions (means = 10, 15) and correlation 0.3
# using Method 1
Pvars <- rcorrvar(k_pois = 2, lam = c(10, 15),
                  rho = matrix(c(1, 0.3, 0.3, 1), 2, 2), seed = seed)

# Simulate "external" data set
set.seed(seed)
ext_y <- rpois(10000, 10)

# Plot pdfs of 1st simulated variable and external data
plot_sim_pdf_ext(sim_y = Pvars$Poisson_variable[, 1], ext_y = ext_y)


## End(Not run)