quantile.lcens | R Documentation |
Computes sample or estimated quantiles corresponding to the given probabilities: methods for "lcens," "mcens," and "qw" data. The smallest observation (censored or uncensored) corresponds to a probability of 0 and the largest to a probability of 1.
## S3 method for class 'lcens' quantile(x, probs = seq(0, 1, 0.25), na.rm = FALSE, names = TRUE, method = "flipped K-M", type = 2, alpha = 0.4, ...) ## S3 method for class 'mcens' quantile(x, probs = seq(0, 1, 0.25), na.rm = FALSE, names = TRUE, method = "flipped K-M", type = 2, alpha = 0.4, ...) ## S3 method for class 'qw' quantile(x, probs = seq(0, 1, 0.25), na.rm = FALSE, names = TRUE, method = "flipped K-M", type = 2, alpha = 0.4, ...)
x |
an object of a censored-data class whose sample quantiles are
wanted. |
probs |
numeric vector of probabilities with values in [0,1]. |
na.rm |
logical; if |
names |
logical; if true, the result has a names attribute. |
method |
the method to use for computing quantiles. See Details. |
type |
an integer between 1 and 9 selecting one of the nine quantile
algorithms described in |
alpha |
the offset fraction to be used, depending on |
... |
not used, required for other methods. |
The methods available in the current version are "flipped K-M," "log ROS," "ROS," "log MLE," and "MLE." The method "flipped K-M" produces quantiles using the Kaplan-Meier method on flipped data described by Helsel (2012). The methods "log ROS" and "log MLE" are described by Helsel, 2012 and Helsel and Cohn (1988). The methods "ROS" and "MLE" are similar to "log ROS" and "log MLE" except that no log- and back-transforms are made on the data.
An optionally named vector of the requested probabilities. The names of values that would be left-censored are marked with "*."
Helsel, D.R. 2012, Statistics for censored environmental data
using Minitab and R: New York, Wiley, 324 p.
Helsel, D.R. and Cohn, T.A., 1988, Estimation of descriptive statistics for
multiply censored water quality data: Water Resources Research v. 24, n.
12, pp. 1997-2004
quantile
, censQuantile
set.seed(28) Xu <- rnorm(23) quantile(as.lcens(Xu, 0))
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