Question about bindata lib in high dimensions

even I tried to use another library mipfp to generate multivariate Bernoulli
*using the following:*
p.joint <- ObtainMultBinaryDist(corr = corr_mat[1:10,1:10], marg.probs =
probs[1:10])
*it Shows:*
Problematic pairs:
     row col
[1,]  10   9
[2,]   9  10
Warning messages:
1: In Corr2PairProbs(corr, marg.probs) :
  Correlation exceeds constrains set by marg.probs, i.e. pair.proba[i, j]
<= marg.probs[i]

2: In Ipfp(seed = seed, target.list = target.list, target.data =
target.data,  :
  Missing values allowed in the target margins.
             Computation of the covariance matrices set to FALSE!
3: In Ipfp(seed = seed, target.list = target.list, target.data =
target.data,  :
  IPFP did not converged after 1000 iteration(s)!
            This migh be due to 0 cells in the seed, maximum number
            of iteration too low or tolerance too small

*and even if I fix the problematic pair (9,10) with the following:*
corr_mat[9,10]=runif(1,max = min(probs[9],probs[10]),min  =
max(0,probs[10]+probs[9]-1))
corr_mat[9,10]
[1] 0.8551618
corr_mat[10,9]=0.8551618
*it still give me the same error.*
p.joint <- ObtainMultBinaryDist(corr = corr_mat[1:10,1:10], marg.probs =
probs[1:10])
Problematic pairs:
     row col
[1,]  10   9
[2,]   9  10
Warning messages:
1: In Corr2PairProbs(corr, marg.probs) :
  Correlation exceeds constrains set by marg.probs, i.e. pair.proba[i, j]
<= marg.probs[i]

2: In Ipfp(seed = seed, target.list = target.list, target.data =
target.data,  :
  Missing values allowed in the target margins.
             Computation of the covariance matrices set to FALSE!
3: In Ipfp(seed = seed, target.list = target.list, target.data =
target.data,  :
  IPFP did not converged after 1000 iteration(s)!
            This migh be due to 0 cells in the seed, maximum number
            of iteration too low or tolerance too small
Could anyone help me please?

?On Mon, 11 Feb 2019 at 13:10, ?????? ??????? ?????? <
emanismail.92 at gmail.com> wrote:?
*Here Sample of Code for 10 variables:*
probs_10 = probs[1:10]
probs_10
 [1] 9.795272e-01 9.331778e-01 6.764349e-01 9.884067e-02 9.522222e-05
3.499417e-03 2.380556e-05 9.826457e-01 9.628633e-01 8.874949e-01
corr_mat_10 = corr_mat[1:10,1:10]
corr_mat_10
               [,1]         [,2]         [,3]         [,4]
[,5]          [,6]          [,7]          [,8]          [,9]       [,10]
 [1,]  1.0000000000  0.540258943  0.209031764  0.047879233 -6.750092e-02
0.0085672057  7.053822e-04  0.7840635867  0.6694665745  0.40604770
 [2,]  0.5402589429  1.000000000  0.386910326  0.088622750 -3.646798e-02
-0.0454879132  1.305637e-03  0.4929722619  0.6613106007  0.61159373
 [3,]  0.2090317635  0.386910326  1.000000000  0.229052428 -1.410984e-02
-0.0434598161 -7.054666e-03  0.1909793458  0.2831488805  0.49337866
 [4,]  0.0478792330  0.088622750  0.229052428  1.000000000 -3.231892e-03
-0.0101705338 -1.615888e-03  0.0434012259  0.0646190283  0.11766286
 [5,] -0.0675009217 -0.036467977 -0.014109837 -0.003231892  1.000000e+00
-0.0005782943 -4.761395e-05 -0.0734320072 -0.0496901947 -0.02740859
 [6,]  0.0085672057 -0.045487913 -0.043459816 -0.010170534 -5.782943e-04
1.0000000000  8.233515e-02  0.0078752345  0.0095061395 -0.03886223
 [7,]  0.0007053822  0.001305637 -0.007054666 -0.001615888 -4.761395e-05
0.0823351499  1.000000e+00  0.0006484086  0.0009582161  0.00173719
 [8,]  0.7840635867  0.492972262  0.190979346  0.043401226 -7.343201e-02
0.0078752345  6.484086e-04  1.0000000000  0.6766830516  0.37325133
 [9,]  0.6694665745  0.661310601  0.283148881  0.064619028 -4.969019e-02
0.0095061395  9.582161e-04  0.6766830516  1.0000000000  0.55158959
[10,]  0.4060477004  0.611593731  0.493378657  0.117662862 -2.740859e-02
-0.0388622278  1.737190e-03  0.3732513255  0.5515895878  1.00000000
library(bindata)
r <- rmvbin(10,margprob = probs_10, bincorr = corr_mat_10)
Not all probabilities are between 0 and 1.
Error in Element ( 1 , 5 ): Admissible values are in [ 0 ,
9.5222224867284e-05 ].
Error in Element ( 1 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 3 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 4 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 5 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 6 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 3 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 4 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 5 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 6 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 8 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 9 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 7 , 10 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 8 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 9 , 7 ): Admissible values are in [ 0 ,
2.3805556216821e-05 ].
Error in Element ( 9 , 10 ): Admissible values are in [ 0.850358273621063
, 0.887494941319304 ].
Error in commonprob2sigma(commonprob, simulvals) :
  Matrix commonprob not admissible.

*Then I tried to fix wrong values to be within range with the following:*
corr_mat_10[1,5]=runif(1,min=0,max=9.5222224867284e-05)
corr_mat_10[1,5]
[1] 7.915036e-05
corr_mat_10[5,1]=7.915036e-05
*and did the same for all elements but the same error raised:*
r <- rmvbin(10,margprob = probs_10, bincorr = corr_mat_10)
Error in Element ( 9 , 10 ): Admissible values are in [ 0.850358273621063
, 0.887494941319304 ].
Error in commonprob2sigma(commonprob, simulvals) :
  Matrix commonprob not admissible.

*Finally I check the value of (9,10) it is within range but the same error
raised :*
corr_mat_10[9,10]
[1] 0.8793437

I don't know How to fix it?

On Mon, 11 Feb 2019 at 12:23, Eric Berger <ericjberger at gmail.com> wrote:

Hi Eman,
It helps if you create a small example that reproduces the problem and
then post the code with your question.
This will help people determine what is causing the problem.

Best,
Eric

?On Mon, Feb 11, 2019 at 11:52 AM ?????? ??????? ?????? <
emanismail.92 at gmail.com> wrote:?

I need to simulate data for 2000 binary variables given a vector of
marginal probabilities and a correlation matrix. I used bindata library,
but it give me

 Not all probabilities are between 0 and 1.
Error in Element ( i , j ): Admissible values are in [.....].
Error in commonprob2sigma(commonprob, simulvals) :
  Matrix commonprob not admissible.

 and I tried to get the elements within range but still have the same
problem

How can I fix the correlation matrix or how to track error ??

Thanks
Eman

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Question about bindata lib in high dimensions

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