function(x, t, a, g)
{
	x <- as.matrix(x)
	sum.total <- as.matrix(colSums(x))
	So <- colSums(sum.total > 0)
	freq.species <- table(colSums(x))
	m.s <- data.frame(occurrences = as.numeric(names(freq.species)), frequency = as.vector(
		freq.species))
	if(m.s[1, 1] == 0)
		stop("There is(are) species in the data with no occurrence in the sampling units. Remove column(s) and start again."
			)
	if(m.s[1, 1] > 1)
		print("warning: no species with one occurrence. Computations were done using the lowest value of occurrence as n1, see formula"
			)
	constant <<- m.s[1, 2]
	library(nls)

	m.s.nls <- nls(frequency ~ (constant * (gamma(occurrences + alp)) * I(gam^(occurrences - 1)))/(gamma(
		occurrences+1) * (gamma(1 + alp))), data = m.s, start = list(alp = a, gam = g))
	matrix.param <- c(So, constant, summary(m.s.nls)$param[,1])
	nb0 <- ( - constant * (((1 + matrix.param[4] * t)^( - matrix.param[3])) - 1))/(matrix.param[3] * 
		matrix.param[4])
	nb <- as.vector(nb0 + So)
	ls0 <- (constant/matrix.param[4]) * log(1 + matrix.param[4] * t)
	ls <- as.vector(ls0 + So)
	names(matrix.param) <- c("Spp.obs", "Spp.with.one.occur.", "alpha", "gamma")
	result <- list(m.s, matrix.param, nb, ls)
	result.names <- c("obs.ditribution", "param", "nb", "ls")
	names(result) <- result.names
	result
}