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Latin Hypercube Sampling when parameters are defined according to specific probability distributions
2017 May 27
2
Latin Hypercube Sampling when parameters are defined according to specific probability distributions
...tributions with different rates ?
>Here is the code used to perform a LHS when the parameter ?dispersal distance? is defined by one default value in the model:
>library(pse)
>factors <- c("distance")
>q <- c("qexp")
>q.arg <- list( list(rate=1/30) )
>uncoupledLHS <- LHS(model=NULL, factors, 50, q, q.arg)
>head(uncoupledLHS)
>Thanks a lot for your time.
>Have a nice day
>Nell
Nell,
I would like to suggest a slightly different method for generating the
sample using the lhs library, then I will try using the pse library.
Generally when you...
Latin Hypercube Sampling when parameters are defined according to specific probability distributions
2017 Jun 01
1
Latin Hypercube Sampling when parameters are defined according to specific probability distributions
...o one model simulation, I should have a value generated by the LHS for all distance classes at the first line of the data frame.
library(pse)
q <- list("qexp", "qunif", "qunif")
q.arg <- list(list(rate=exponential_rate), list(min=0, max=1),
list(min=0, max=1))
uncoupledLHS <- LHS(model=model_function, input_parameters, N, q, q.arg)
hist(uncoupledLHS$data$dispersal_distance, breaks=10)
tabLHS <- get.data(uncoupledLHS)
Sorry, it?s the first time that I perform a sensitivity analysis using the LHS.
Thank you very much for your time.
Have a nice day
Nell...
Latin Hypercube Sampling when parameters are defined according to specific probability distributions
2017 Jun 01
0
Latin Hypercube Sampling when parameters are defined according to specific probability distributions
...a value generated by the LHS for all distance classes at the first line of the data frame.
>
>
>
> library(pse)
> q <- list("qexp", "qunif", "qunif")
> q.arg <- list(list(rate=exponential_rate), list(min=0, max=1),
> list(min=0, max=1))
> uncoupledLHS <- LHS(model=model_function, input_parameters, N, q, q.arg)
> hist(uncoupledLHS$data$dispersal_distance, breaks=10)
>
> tabLHS <- get.data(uncoupledLHS)
>
>
>
> Sorry, it?s the first time that I perform a sensitivity analysis using the LHS.
>
>
> Thank you very...