cont_cdfplot: Create a PDF file containing cumulative distribution functions (CDF) plots

Description

This function creates a PDF file containing CDF plots. Input data for the plots is provided by a data frame with the same structure as the "CDF" output from cont_analysis. Plots are produced for every combination of Type of population, Subpopulation within Type, and Indicator (every combination of subpopulations, subpopulation levels, and variables).

Usage

cont_cdfplot(
  pdffile = "cdf2x2.pdf",
  cdfest,
  units_cdf = "Percent",
  ind_type = rep("Continuous", nind),
  log = rep("", nind),
  xlab = NULL,
  ylab = NULL,
  ylab_r = NULL,
  legloc = NULL,
  cdf_page = 4,
  width = 10,
  height = 8,
  confcut = 0,
  cex.main = 1.2,
  cex.legend = 1,
  ...
)

Value

A PDF file containing the CDF plots.

Arguments

pdffile: Name of the PDF file. The default is "cdf2x2.pdf".
cdfest: Data frame with the same structure as the "CDF" output from cont_analysis.
units_cdf: Indicator for the label utilized for the left side y-axis and the values used for the left side y-axis tick marks, where "Percent" means the label and values are in terms of percent of the population, and "Units" means the label and values are in terms of units (count, length, or area) of the population. The default is "Percent".
ind_type: Character vector consisting of the values "Continuous" or "Ordinal" that controls the type of CDF plot for each indicator. The default is "Continuous" for every indicator.
log: Character vector consisting of the values "" or "x" that controls whether the x axis uses the original scale ("") or the base 10 logarithmic scale ("x") for each indicator. The default is "" for every indicator.
xlab: Character vector consisting of the x-axis label for each indicator. If this argument equals NULL, then indicator names are used as the labels. The default is NULL.
ylab: Character string providing the left side y-axis label. If argument units_cdf equals "Units", a value should be provided for this argument. Otherwise, the label will be "Percent". The default is "Percent".
ylab_r: Character string providing the label for the right side y-axis (and, hence, determining the values used for the right side y-axis tick marks), where NULL means a right side y-axis is not created. If this argument equals "Same", the right side y-axis will have the same label and tick mark values as the left side y-axis. If this argument equals a character string other than "Same", the right side y-axis label will be the value provided for argument ylab_r, and the right side y-axis tick mark values will be determined by the choice not utilized for argument units_cdf, which means that the default value of argument units_cdf (i.e., "Percent") will result in the right side y-axis tick mark values being expressed in terms of units of the population (i.e., count, length, or area). The default is NULL.
legloc: Indicator for location of the plot legend, where "BR" means bottom right, "BL" means bottom left, "TR" means top right, "TL" means top left, and NULL means no legend. The default is NULL.
cdf_page: Number of CDF plots on each page, which must be chosen from the values: 1, 2, 4, or 6. The default is 4.
width: Width of the graphic region in inches. The default is 10.
height: Height of the graphic region in inches. The default is 8.
confcut: Numeric value that controls plotting confidence limits at the CDF extremes. Confidence limits for CDF values (percent scale) less than confcut or greater than 100 minus confcut are not plotted. A value of zero means confidence limits are plotted for the complete range of the CDF. The default is 0.
cex.main: Expansion factor for the plot title. The default is 1.2.
cex.legend: Expansion factor for the legend title. The default is 1.
...: Additional arguments passed to the cdf_plot function.

Author

Tom Kincaid Kincaid.Tom@epa.gov

Examples

Run this code

if (FALSE) {
dframe <- data.frame(
  siteID = paste0("Site", 1:100),
  wgt = runif(100, 10, 100),
  xcoord = runif(100),
  ycoord = runif(100),
  stratum = rep(c("Stratum1", "Stratum2"), 50),
  ContVar = rnorm(100, 10, 1),
  All_Sites = rep("All Sites", 100),
  Resource_Class = rep(c("Good", "Poor"), c(55, 45))
)
myvars <- c("ContVar")
mysubpops <- c("All_Sites", "Resource_Class")
mypopsize <- data.frame(
  Resource_Class = c("Good", "Poor"),
  Total = c(4000, 1500)
)
myanalysis <- cont_analysis(dframe,
  vars = myvars, subpops = mysubpops,
  siteID = "siteID", weight = "wgt", xcoord = "xcoord", ycoord = "ycoord",
  stratumID = "stratum", popsize = mypopsize
)
cont_cdfplot("myanalysis.pdf", myanalysis$CDF, ylab_r = "Stream Length (km)")
}