Error code 100 fitting exp distribution using fitdist in r

Question

I am trying to fit an exponential distribution to my data but I get the error below

\"Error in fitdist(x41, \"exp\", method = \"mle\") : 
  the function mle          


        

Answer 1

Assuming this is fitdist from fitdistrplus package, I can duplicate your error:

> fitdist(x41, "exp", method="mle")
<simpleError in optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data,     gr = gradient, ddistnam = ddistname, hessian = TRUE, method = meth,     lower = lower, upper = upper, ...): non-finite finite-difference value [1]>
Error in fitdist(x41, "exp", method = "mle") : 
  the function mle failed to estimate the parameters, 
                with the error code 100

but there's some large numbers in your data... maybe if we scale it all down by a factor...

> fitdist(x41/10000, "exp", method="mle")
Fitting of the distribution ' exp ' by maximum likelihood 
Parameters:
     estimate Std. Error
rate   7.1417   1.683315

Well that seemed to work. Let's scale by a bit less:

> fitdist(x41/1000, "exp", method="mle")
Fitting of the distribution ' exp ' by maximum likelihood 
Parameters:
     estimate Std. Error
rate  0.71417  0.1683312

Right. Divide by a thousand works. Let's keep going:

> fitdist(x41/100, "exp", method="mle")
Fitting of the distribution ' exp ' by maximum likelihood 
Parameters:
     estimate Std. Error
rate 0.071417 0.01682985

Fine.

> fitdist(x41/10, "exp", method="mle")
Fitting of the distribution ' exp ' by maximum likelihood 
Parameters:
      estimate  Std. Error
rate 0.0071417 0.001649523

So scaling the data by 1/10 works, and you can see how the estimate and SE scale. Let's go one more step:

> fitdist(x41/1, "exp", method="mle")
<simpleError in optim(par = vstart, fn = fnobj, fix.arg = fix.arg, obs = data,     gr = gradient, ddistnam = ddistname, hessian = TRUE, method = meth,     lower = lower, upper = upper, ...): non-finite finite-difference value [1]>
Error in fitdist(x41/1, "exp", method = "mle") : 
  the function mle failed to estimate the parameters, 
                with the error code 100

Crunch. It looks like some numerical stability problem with the underlying algorithm. If its taking exponentials of your data at any point then maybe it hits something indistinguishable from infinity. Like:

> exp(x41)
 [1]           Inf 2.100274e+132           Inf           Inf           Inf
 [6]           Inf 3.757545e+152  5.096228e+47 4.064401e+199  5.776191e+05
[11]  1.033895e+00           Inf           Inf           Inf  9.145540e+40
[16]  3.323969e+06 1.195135e+118 2.638092e+205

But scale by ten and the maths can cope, just about (E+256!!!)

> exp(x41/10)
 [1] 2.552833e+121  1.706977e+13 1.032728e+121 1.367817e+256 1.907002e+190
 [6]  1.459597e+51  1.809216e+15  5.898273e+04  9.139021e+19  3.768462e+00
[11]  1.003339e+00  5.727429e+36 4.184491e+160  2.094645e+66  1.247731e+04
[16]  4.489166e+00  6.423056e+11  3.484408e+20