Thanks for your answer.

I have attached the plot for representing the variable. I think that I need to 
draw a Hypercube sample for each age class (i.e., for 0, 1, 2, 3, 4, 5, 6, 7) 
in a given simulation (i.e., N = 1) and the LHS values for all age classes 
should be like the observed cumulative distribution (see attached figure). 
Thus, the output of randomLHS should be a matrix with 100 rows (N = 100 
simulations) and 7 columns (7 age classes) containing LHS values and each row 
should exhibit the same pattern as the observed cumulative distribution.
With the command “qpois(X[, "mortality_probability"], 0.9)”, I don’t obtain a 
LHS value for each age class and the distribution is not a cumulative 
distribution as in the attached figure. So, I am afraid I don’t know how to do 
Thanks so much for your time

De : S Ellison <>
Envoyé : mardi 8 août 2017 14:48
À : Marine Regis;
Objet : RE: Latin hypercube sampling from a non-uniform distribution

> However, my variable is simulated from the cumulative distribution function
> of the Poisson distribution.
Then I am afraid I don't know what you're trying to achieve.
Or why.

However, the principle holds; write a function that maps [0,1] to the 'pattern' 
you want, do that and apply it to the result from randomLHS.
It happens that for generating data that follow a given probability 
distribution F, that function is the quantile function for F so you often do 
not need to write it.

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