search for: mortality_prob

Displaying 5 results from an estimated 5 matches for "mortality_prob".

2017 Aug 04
2
Latin hypercube sampling from a non-uniform distribution
Hello, I am performing a sensitivity analysis using a Latin Hypercube sampling. However, I have difficulty to draw a Hypercube sample for one variable. I?ve generated this variable from a Poisson distribution as follows: set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2) barplot(mortality_probability, names.arg = seq(0, 7, by = 1), xlab = "Age class", ylab = "Probability") How can I draw a Hypercube sample for the variable ?mortality_probability? so that this variable exhibits the sa...
2017 Aug 07
0
Latin hypercube sampling from a non-uniform distribution
> How can I draw a Hypercube sample for the variable mortality_probability so > that this variable exhibits the same pattern as the observed distribution? One simple way is to use the uniform random output of randomLHS as input to the quantile function for your desired distribution(s). For example: q <- randomLHS(1000, 3) colnames(q) <- c("A"...
2017 Aug 07
2
Latin hypercube sampling from a non-uniform distribution
Thanks for your answer. However, my variable is simulated from the cumulative distribution function of the Poisson distribution. So, the pattern obtained from the function "qpois" is not the same as the observed pattern (i.e., obtained from the function "ppois") set.seed(5) mortality_probability <- round(ppois(seq(0, 7, by = 1), lambda = 0.9), 2) barplot(mortality_probability, names.arg = seq(0, 7, by = 1), xlab = "Age class", ylab = "Probability") library(lhs) set.seed(1) parm <- c("var1", "var2", "mortality_probability") X &...
2017 Aug 08
0
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
2017 Aug 08
1
Latin hypercube sampling from a non-uniform distribution
...lative 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 that. Thanks so much for your time Marine ________________________________ De : S Ellison <S.Ellison at L...