Nothing
tpfit_ml <-
function(data, coords, direction, tolerance = pi/8, mle = "avg") {
# Estimation for matrix of transition rates
# ( Mean Length Method )
#
# data vector of data
# coords coordinates matrix
# direction vector (or versor) of choosen direction
# tolerance angle tolerance (in radians)
# mle argument to pass to the function tpfit
if (!is.factor(data)) data <- as.factor(data)
if (!is.matrix(coords)) coords <- as.matrix(coords)
n <- dim(coords)[1]
nc <- dim(coords)[2]
if (length(direction) != nc) stop("wrong length of direction vector")
nl <- nlevels(data)
if (n < (nl^2 + nl)) stop("there are not enough data to estimate the parameters")
loc.id <- which_lines(coords, direction, tolerance)
ml <- mlen(data, coords, loc.id, direction, mle)
res <- list()
res$coefficients <- embed_MC(data, coords, loc.id, direction)
diag(res$coefficients) <- -1
res$coefficients <- diag(1 / ml) %*% res$coefficients
res$prop <- table(data)
res$prop <- as.double(res$prop / sum(res$prop))
names(res$prop) <- levels(data)
colnames(res$coefficients) <- names(res$prop)
rownames(res$coefficients) <- names(res$prop)
res$tolerance <- as.double(tolerance)
class(res) <- "tpfit"
return(res)
}
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