function(mu = rep(0, times = 100), upsilon = rep(0.1, times = 100), tau = rep(0.01, times = 100), view.plot = 0)
{
#program compute.proportions.active()
#
#Computes proportion sexually active given forces of mortality (mu) and
#movement from inactive to active status (upsilon) and active to inactive
#status (tau), for an hypothetical cohort. These vectors must have the
#same length (but there is no check for this). Note that the force of new
#infection, a competing decrement for the sexually active population, is
#assumed equal to zero here before the model is initialized before the
#epidemic begins.
#
	x <- rep(0, length = length(mu))
	names(x) <- 0:(length(x) - 1)
	y <- x
	x[1] <- 1000
	y[1] <- 0
	xd <- xy <- yd <- yx <- rep(0, times = length(mu))
	for(i in 1:(length(x) - 1)) {
		xd[i] <- x[i] * (1 - exp( - (mu[i] + upsilon[i]))) * (mu[i]/(mu[i] + upsilon[i]))
		xy[i] <- x[i] * (1 - exp( - (mu[i] + upsilon[i]))) * (upsilon[i]/(mu[i] + upsilon[i]))
		yd[i] <- y[i] * (1 - exp( - (mu[i] + tau[i]))) * (mu[i]/(mu[i] + tau[i]))
		yx[i] <- y[i] * (1 - exp( - (mu[i] + tau[i]))) * (tau[i]/(mu[i] + upsilon[i]))
		x[i + 1] <- x[i] - (xd[i] + xy[i]) + yx[i]
		y[i + 1] <- y[i] - (yd[i] + yx[i]) + xy[i]
	}
	proportion.active <- y/(x + y)
	write.ascii(compute.proportions.active)
	proportion.active
}