maxEM {sonicLength} | R Documentation |
maximum likelihood estimates relative abundances
Description
From information about the lengths of sonicants of integration sites, infer the relative abundances of different clones and the distributon of sonicant lengths
Usage
maxEM(slmat, theta.var=FALSE, phi.update=NULL,
phi.deriv=NULL, lframe = NULL, glm.frm = NULL, iter.control=NULL, ... )
Arguments
slmat |
a matrix whose rows correspond to unique lengths with rownames indicating those lengths |
theta.var |
logical, return variance of theta estimates? |
phi.update |
a function of an object like |
phi.deriv |
function of theta and phi that returns derivatives of phi wrt beta (its parameters) |
lframe |
a |
glm.frm |
a formula like |
iter.control |
a list of default values for iteration control - see |
... |
possibly other args to pass to |
Details
The EM method is used to infer the relative abundances of different sites.
Value
theta |
a vector of the abundance estimates |
phi |
a vector of the probabilities of sonicant lengths |
call |
the call used |
Author(s)
Charles C. Berry ccberry@users.r-forge.r-project.org
See Also
Examples
mat0 <- matrix(0,nr=48,nc=140)
vals <- c(rep(1,100),2:40,100)
mat1 <- sapply( vals, function(x) as.numeric(is.element(1:200 ,rgeom(x,.02))))
mat <- rbind(mat0,mat1)
posVals <- colSums(mat) > 0
vals <- vals[ posVals ]
mat <- mat[, posVals ]
rownames(mat) <- 1:nrow(mat)
res <- maxEM(mat)
matplot( vals, cbind(res$theta, colSums(mat)), pch=1:2,
xlab='original values', ylab='estimated values',
main='Simulated Sonicants and Estimates')
legend( "bottomright", pch=1:2, col=1:2,
legend=c(expression(hat(theta)[j]),expression(sum(y[ij],i))))
abline(a=0,b=1,col='gray')