CODEWITHSUNDEEP
rapplylapplysapplytapply
F.family
F.family

Reputation: 49

How to call a function using *apply with different data, where output is list and intput is list of 2x2 matrix?

I have data from 10 runs of a simulation, stored as a list. I want to call a function FUN1 with this data, without repeating the code 10 times. The output from FUN1 is a value of model parameter such that: 

               $theta=5
               $Theta= 0.5
               $pi_1 = 0.6
               $pi_2 = 0.4 
               $loglik_1 = 123.6
               $loglik_2 = 23.56

So, this how the output of FUN1 when I fit it to one of the 10 runs. I would like to have the output of all runs without refit my function for each run.

I know that we can use loop-family functions in R such as lapply (list) or tapply (vector) functions. I tried both of them but both did not work.

Here is my data:

   library(VineCopula)
   library(copula)
   Runs = 10
   Saveas = vector(mode = "list", length = Runs)
   pb <- txtProgressBar(min = 0, max = Runs, style = 3)

   for(j in 1:Runs) {
     setTxtProgressBar(pb, j)
     N=2000
     dim = dim
     U = runif(N, min=0,max=1)
     X = matrix(NA, nrow=N, ncol=2)

     inds <- U < 0.7

     X[inds, ]  <- rCopula(sum(inds),
                    claytonCopula(1, dim=2))

     X[!inds, ] <- rCopula(N - sum(inds),
                    frankCopula(4, dim=2))
     Saveas[[j]] = X
   }

This is my function:

      FUN1 <- EM_mixture_copula(data =   
          Saveas[[j]],pi_1=pi_1,pi_2=pi_2,theta = theta, 
          Theta=Theta, tol = .00001,     maxit = 1000)

Here is my tries with the errors that I got:

    > result <- tapply(X,FUN1,simplify = T)
    Error in tapply(X, FUN, simplify = T) : arguments must have same length.

    > Result <– lapply(X,FUN1)
    Error in get(as.character(FUN), mode = "function", envir = envir) : object 'F' of mode 'function' was not found.

Note that the output of copula is a matrix(nrow=N, ncol=2) (since the dimension of copula is 2). For example:

   xx <-            

        rCopula(N=4 ,claytonCopula(0.5))
            xx
                   [,1]        [,2]
      [1,] 0.6269311043 0.229429156
      [2,] 0.3257583519 0.268244546
      [3,] 0.7446442267 0.436335203
      [4,] 0.3186246504 0.163209827

Where 0.5 is copula parameter.

Any help, please?

Upvotes: 2

Views: 129

Answers (1)

Sathish
Sathish

Reputation: 12703

I guess dim inside sim_fun should be 1. Since, I do not have data or the libraries installed, this answer is an unverified post. However, it will help you figure out the solution from here.

sim_fun <- function( N )
{
  U=runif(N, min=0,max=1)
  inds <- U < 0.7
  X <- matrix(NA, nrow = N, ncol = 2)
  X[inds, 1:2] <- rCopula(sum(inds), claytonCopula(1, dim=2))
  X[!inds, 1:2] <- rCopula(N - sum(inds), frankCopula(4,dim=2))
  return( X )
}

set.seed(1L)  # set state of random number generator
sim_data <- replicate( n = 10, sim_fun( N = 2000 ))  # get simulated data 10 times

# apply EM function on the simulated data
apply( sim_data, 3, function( x ) EM_mixture_copula(data =  x,
                                                    pi_1 = pi_1,
                                                    pi_2=pi_2,
                                                    theta = theta, 
                                                    Theta=Theta, 
                                                    tol = .00001,
                                                    maxit = 1000))

Upvotes: 1

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