graphcompcens  R Documentation 
cdfcompcens
plots the empirical cumulative distribution against fitted distribution functions,
qqcompcens
plots theoretical quantiles against empirical ones,
ppcompcens
plots theoretical probabilities against empirical ones.
cdfcompcens(ft, xlim, ylim, xlogscale = FALSE, ylogscale = FALSE, main, xlab, ylab, datacol, fillrect, fitlty, fitcol, fitlwd, addlegend = TRUE, legendtext, xlegend = "bottomright", ylegend = NULL, lines01 = FALSE, Turnbull.confint = FALSE, NPMLE.method = "Wang", add = FALSE, plotstyle = "graphics", ...) qqcompcens(ft, xlim, ylim, xlogscale = FALSE, ylogscale = FALSE, main, xlab, ylab, fillrect, fitcol, fitlwd, addlegend = TRUE, legendtext, xlegend = "bottomright", ylegend = NULL, line01 = TRUE, line01col = "black", line01lty = 1, ynoise = TRUE, NPMLE.method = "Wang", plotstyle = "graphics", ...) ppcompcens(ft, xlim, ylim, xlogscale = FALSE, ylogscale = FALSE, main, xlab, ylab, fillrect, fitcol, fitlwd, addlegend = TRUE, legendtext, xlegend = "bottomright", ylegend = NULL, line01 = TRUE, line01col = "black", line01lty = 1, ynoise = TRUE, NPMLE.method = "Wang", plotstyle = "graphics", ...)
ft 
One 
xlim 
The xlimits of the plot. 
ylim 
The ylimits of the plot. 
xlogscale 
If 
ylogscale 
If 
main 
A main title for the plot, see also 
xlab 
A label for the xaxis, defaults to a description of 
ylab 
A label for the yaxis, defaults to a description of 
datacol 
A specification of the color to be used in plotting data points. 
fillrect 
A specification of the color to be used for filling rectanges
of non uniqueness of the empirical cumulative distribution
(only used if 
fitcol 
A (vector of) color(s) to plot fitted distributions. If there are fewer colors than fits they are recycled in the standard fashion. 
fitlty 
A (vector of) line type(s) to plot fitted distributions.
If there are fewer values than fits they are recycled in the standard fashion.
See also 
fitlwd 
A (vector of) line size(s) to plot fitted distributions.
If there are fewer values than fits they are recycled in the standard fashion.
See also 
addlegend 
If 
legendtext 
A character or expression vector of length ≥q 1 to appear
in the legend, see also 
xlegend, ylegend 
The x and y coordinates to be used to position the legend.
They can be specified by keyword.
If 
lines01 
A logical to plot two horizontal lines at 
Turnbull.confint 
if TRUE confidence intervals will be added to the Turnbull plot.
In that case NPMLE.method is forced to 
NPMLE.method 
Three NPMLE techniques are provided, 
add 
If 
line01 
A logical to plot an horizontal line y=x for

line01col, line01lty 
Color and line type for 
ynoise 
A logical to add a small noise when plotting empirical
quantiles/probabilities for 
plotstyle 

... 
Further graphical arguments passed to graphical functions used in 
See details of plotdistcens
for a detailed description of provided goddnessoffit plots.
MarieLaure DelignetteMuller and Christophe Dutang.
Turnbull BW (1974), Nonparametric estimation of a survivorship function with doubly censored data. Journal of American Statistical Association, 69, 169173.
Wang Y (2008), Dimensionreduced nonparametric maximum likelihood computation for intervalcensored data. Computational Statistics & Data Analysis, 52, 23882402.
Wang Y and Taylor SM (2013), Efficient computation of nonparametric survival functions via a hierarchical mixture formulation. Statistics and Computing, 23, 713725.
DelignetteMuller ML and Dutang C (2015), fitdistrplus: An R Package for Fitting Distributions. Journal of Statistical Software, 64(4), 134.
plotdistcens
, survfit.formula
, legend
and par
.
# (1) Plot various distributions fitted to bacterial contamination data # data(smokedfish) Clog10 < log10(smokedfish) fitsfn < fitdistcens(Clog10,"norm") summary(fitsfn) fitsfl < fitdistcens(Clog10,"logis") summary(fitsfl) dgumbel < function(x,a,b) 1/b*exp((ax)/b)*exp(exp((ax)/b)) pgumbel < function(q,a,b) exp(exp((aq)/b)) qgumbel < function(p,a,b) ab*log(log(p)) fitsfg<fitdistcens(Clog10,"gumbel",start=list(a=3,b=3)) summary(fitsfg) # CDF plot cdfcompcens(list(fitsfn,fitsfl,fitsfg)) cdfcompcens(list(fitsfn,fitsfl,fitsfg),datacol="orange",fillrect = NA, legendtext=c("normal","logistic","Gumbel"), main="bacterial contamination fits", xlab="bacterial concentration (CFU/g)",ylab="F", xlegend = "bottom",lines01 = TRUE) # alternative Turnbull plot for the empirical cumulative distribution # (default plot of the previous versions of the package) cdfcompcens(list(fitsfn,fitsfl,fitsfg), NPMLE.method = "Turnbull.middlepoints") # customizing graphical output with ggplot2 if (requireNamespace ("ggplot2", quietly = TRUE)) { cdfcompcens < cdfcompcens(list(fitsfn,fitsfl,fitsfg),datacol="orange",fillrect = NA, legendtext=c("normal","logistic","Gumbel"), xlab="bacterial concentration (CFU/g)",ylab="F", xlegend = "bottom",lines01 = TRUE, plotstyle = "ggplot") cdfcompcens + ggplot2::theme_minimal() + ggplot2::ggtitle("Bacterial contamination fits") } # PP plot ppcompcens(list(fitsfn,fitsfl,fitsfg)) ppcompcens(list(fitsfn,fitsfl,fitsfg), ynoise = FALSE) par(mfrow = c(2,2)) ppcompcens(fitsfn) ppcompcens(fitsfl) ppcompcens(fitsfg) par(mfrow = c(1,1)) if (requireNamespace ("ggplot2", quietly = TRUE)) { ppcompcens(list(fitsfn,fitsfl,fitsfg), plotstyle = "ggplot") ppcompcens(list(fitsfn,fitsfl,fitsfg), plotstyle = "ggplot", fillrect = c("lightpink", "lightblue", "lightgreen"), fitcol = c("red", "blue", "green")) } # QQ plot qqcompcens(list(fitsfn,fitsfl,fitsfg)) qqcompcens(list(fitsfn,fitsfl,fitsfg), ynoise = FALSE) par(mfrow = c(2,2)) qqcompcens(fitsfn) qqcompcens(fitsfl) qqcompcens(fitsfg) par(mfrow = c(1,1)) if (requireNamespace ("ggplot2", quietly = TRUE)) { qqcompcens(list(fitsfn,fitsfl,fitsfg), ynoise = FALSE, plotstyle = "ggplot") qqcompcens(list(fitsfn,fitsfl,fitsfg), ynoise = FALSE, plotstyle = "ggplot", fillrect = c("lightpink", "lightblue", "lightgreen"), fitcol = c("red", "blue", "green")) }
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