Hello,

I am using CentOS Linux 6.0, R 2.14.1 and nlme 3.1-103

I am trying to fit some models using nlme, and what was happening was that it would get to some datasets and just "stall", the memory usage would grow and grow and eventually crash.

I looked carefully into one of the datasets and ran it separately. It worked.  After narrowing down on all possibilities, I found that the main difference between both was in the initial values. If one subtracts them:

> initialValuesOriginal - initialValuesThatWorks
          A.R           A.a           A.y           B.R           B.a
-3.194922e-08  0.000000e+00  0.000000e+00 -9.249630e-08  0.000000e+00
          B.y           C.R           C.a           C.y           D.R
 0.000000e+00 -1.713935e-06 -8.639821e-09  1.032083e-09  3.716880e-08
          D.a           D.y           E.R           E.a           E.y
 0.000000e+00  0.000000e+00  1.766460e-06  0.000000e+00  0.000000e+00

How come such a small difference can have such a big effect?  (working ok, versus stalling the entire computer)

I also just played with rounding to 10 decimal digits and it worked fine.

I will look into what nlme is doing tomorrow, but was wondering if perhaps there is something that I don't know about how R works, or using numbers with many decimals in nlme for initial values, that would create such a phenomenon.

Thanks in advance,
Ramiro

	[[alternative HTML version deleted]]

