RPointCloud (version 0.8.0)

EBexpo-class: The EBexpo Class

Description

The EBexpo object represents the results of an Empirical Bayes approach to estimate a distribution as a mixture of a (more or less) known exponential distribution along with a completely unknown "interesting" distribution. The basic method was described by Efron and Tibshirani with an application to differential expression in microarray data.

Usage

EBexpo(edata, resn = 200)
cutoff(target, prior, object)
# S4 method for EBexpo,missing
plot(x, prior = 1, significance = c(0.5, 0.8, 0.9),
                 ylim = c(-0.5, 1), xlab = "Duration",
                 ylab = "Probability(Interesting | Duration)", ...)
# S4 method for EBexpo
hist(x, ...)

Value

The EBexpo function constructs and returns an object of the

EBexpo class

The plot and hist methods return (invisibly) the EBexpo object that was their first argument.

Arguments

edata

A numeric vector; the observed data that we think comes mainly from an exponential distribution.

resn

A numeric vector; the resolution used to estimate a histogream.

x

An EBexpo object.

prior

A numeric vector of length 1; the prior probability of an observed data point coming from the known exponential distribution.

significance

A numeric vector with values between 0 and 1; the target posterior probabiltiites.

ylim

A numeric vector of length two.

xlab

A character vector; the label for the x-axis.

ylab

A character vector; the label for the y-axis.

...

The usual set of graphical parameters.

target

The target posterior probability.

object

An EBexpo object.

Slots

xvals:

Inherited from MultiWilcoxonTest

statistics:

Inherited from MultiWilcoxonTest, Here, these are the same a the edata slot from an link{ExpoFit} object.

pdf:

Inherited from MultiWilcoxonTest

theoretical.pdf:

Inherited from MultiWilcoxonTest

unravel:

Inherited from MultiWilcoxonTest

groups:

Inherited from MultiWilcoxonTest, but not used

call:

Inherited from MultiWilcoxonTest

h0:

See ExpoFit

lambda:

See ExpoFit

mu:

See ExpoFit

Methods

plot(x, prior, post = c(0.5, 0.8, 0.9), ...):

Produce a plot of a EBexpo object.

hist(x, ...):

Produce a histogram of the observed distibution, with overlays.

Author

Kevin R. Coombes <[e-mail]>

References

Efron B, Tibshirani R. Empirical bayes methods and false discovery rates for microarrays. Genet Epidemiol. 2002 Jun;23(1):70-86. doi: 10.1002/gepi.1124.

Examples

data(cytof)
diag <- AML10.node287.rips[["diagram"]]
persistence <- diag[, "Death"] - diag[, "Birth"]
d1 <- persistence[diag[, "dimension"] == 1]
eb <- EBexpo(d1, 200)
hist(eb)
plot(eb, prior = 0.56)
cutoff(0.8, 0.56, eb)