Greets,

I'm using nlminb() to estimate the parameters of a multivariate normal random 
sample with missing values and ran into an unexpected result from my call to 
dmvnorm() within the likelihood function. Particular details are provided 
below. It appears that dmvnorm() makes a call to log(eigen(sigma)). Whereas 
eigen(sigma) is returning a negative number, I understand log()'s complaint. 
However, it is a mystery to me why this data set should produce such a result.

Any suggestions?

Best Regards,
Steven

> complete
             [,1]      [,2]
 [1,]  0.84761637  3.994261
 [2,]  0.91487059  4.952595
 [3,]  0.84527267  4.521837
 [4,]  2.53821358  8.374880
 [5,]  1.16646209  6.255022
 [6,]  0.94706527  4.169510
 [7,]  0.48813564  3.349230
 [8,]  3.71828469  9.441518
 [9,]  0.08953357  1.651497
[10,]  0.68530515  5.498403
[11,]  1.52771645  8.484671
[12,]  1.55710697  5.231272
[13,]  1.89091603  4.152658
[14,]  1.08483541  5.401544
[15,]  0.58125385  5.340141
[16,]  0.24473250  2.965046
[17,]  1.59954401  8.095561
[18,]  1.57656436  5.335744
[19,]  2.73976992  8.572871
[20,]  0.87720252  6.067468
[21,]  1.18403087  3.526790
[22,] -1.03145244  1.776478
[23,]  2.88197343  7.720838
[24,]  0.60705218  4.406073
[25,]  0.58083464  3.374075
[26,]  0.87913427  5.247637
[27,]  1.10832692  3.534508
[28,]  2.92698371  8.682130
[29,]  4.04115277 11.827360
[30,] -0.57913297  1.476586
[31,]  0.84804365  7.009075
[32,]  0.79497940  3.671164
[33,]  1.58837762  5.535409
[34,]  0.63412821  3.932767
[35,]  3.14032433  9.271014
[36,] -0.18183869  1.666647
[37,]  0.57535770  6.881830
[38,]  3.21417723 10.901636
[39,]  0.29207932  4.120408
[40,]  0.65938218  5.209301
> u
[1] 1.267198 5.475045
> sigma
          [,1]     [,2]
[1,] 0.6461647 2.228951
[2,] 2.2289513 5.697834
> dmvnorm(x=complete,mean=u,sigma=sigma)
 [1] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN 
NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
[30] NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN
Warning message:
In log(eigen(sigma, symmetric = TRUE, only.values = TRUE)$values) :
  NaNs produced
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