Computational differences in R vs Excel

There are several problems here.   The first is that it's rather unlikely you
really need 10-place accuracy to fit your data.  This suggests you may be
doing something inappropriate such as fitting the wrong function or trying
to extrapolate.   Since you haven't explained what "process" you have that
isn't "converging," since clearly the fitting algorithms themselves have
converged.

Next,  you need to understand that both Excel and R have default convergence
tolerances which may not be identical (as well as default iteration limits).

And finally, of course, there's the question of machine precision limits,
although that is less likely to be a culprit in this instance.  


Soham wrote

Hello,
 I am working on fitting a non-linear time series. The results which I
found using R and Excel are not quite same up to 10-12 places after
decimal (i require high precision because otherwise the process might not
converge)
 For example, i am performing this simple arithmetic:
    23-(1.346493052*16)+(.663965156*11)+(.008569426*5)-15.23480728

R gives the result --> -6.432232271 
Excel gives the result ---> -6.432232266

The difference is negligible for all practical purposes but it leads to
entirely different outcomes for me. I read some of the materials available
online but none were of any help. What is the difference which prompts
such different results? Is there anything that can be used to solve this
problem ?

Please give suggestion if you can. Thanks

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