emg.mle {emg} | R Documentation |
Maximum Likelihood estimate of parameters
Description
Compute the maximum likelihood model for the parameters given a set of observations. Returns a model with estimates for mu, sigma, and lambda.
Usage
emg.mle(x, lower=NULL, upper=NULL, start=NULL, ...)
Arguments
x |
vector of observations to estimate parameters for. |
lower |
list of lower bounds for parameters. |
upper |
list of upper bounds for parameters. |
start |
list of starting parameters for search. |
... |
optional parameters to pass to 'mle'. |
Value
An object of class mle-class
.
Author(s)
Shawn Garbett
See Also
Examples
emg.mle(remg(200))
## a example involving fitting
data(pc9_3um_erlotinib)
intermitotic.time <- subset(pc9_3um_erlotinib, end.of.movie=='N' & died=='N')$observed
hist(intermitotic.time, freq=FALSE, main="PC9 in 3um erlotinib", xlab='intermitotic time (hours)')
fit <- emg.mle(intermitotic.time)
pdf <- function(x) demg(x, coef(fit)['mu'], coef(fit)['sigma'], coef(fit)['lambda'])
curve(pdf, from=0, to=170, add=TRUE, col='red')
[Package emg version 1.0.9 Index]