| ExpoFit-class | R Documentation | 
ExpoFit Class
An ExpoFit object represents a robust fit to an exponential
distribution, in a form that can conveniently be used as part of an
Empirical Bayes approach to decompose the distributions of cycle
presistence or duration for a topological data analysis performed
using the TDA package.
ExpoFit(edata, resn = 200)
## S4 method for signature 'ExpoFit,missing'
plot(x, y, ...)
| edata | A numeric vector; the observed data that we think comes mainly from an exponential distribution. | 
| resn | A numeric vector of length 1; the resolution (number of breaks) used to estimate a histogram. | 
| x | An  | 
| y | Ignored. | 
| ... | The usual set of graphical parameters. | 
The ExpoFit function constructs and returns an object of the
ExpoFit class.
The plot method returns (invisibly) the ExpoFit object that was
its first argument.
edata:A numeric vector; the observed data that we think comes from an exponential distribution.
h0:A histogram object produced by the
hist function applied to the supplied edata.
X0:A numeric vector containing the midpoints of the breaks in the histogram object.
pdf:The empirical density function extracted from the histogram object.
mu:The observed mean of the putative exponential distribution.
lambda:The robustly estimated parameter of the exponential distribution. Originally crudely repesented by the reciprocal of the mean.
Produce a plot of a ExpoFit object.
Kevin R. Coombes <krc@silicovore.com>
EBexpo
data(cytof)
diag <- AML10.node287.rips[["diagram"]]
persistence <- diag[, "Death"] - diag[, "Birth"]
d1 <- persistence[diag[, "dimension"] == 1]
ef <- ExpoFit(d1) # should be close to log(2)/median? 
plot(ef)
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