On Wed, 27 Apr 2011, Joshua Wiley wrote:
Hi,
I am not incredibly knowledgeable about gamma distributions, but
looking at your data, you have a tiny mean:variance ratio, which, I
believe, means that the bulk of the distribution will be near 0 and
you may run into computational problems (again I think. I would
gladly be corrected).
No, the data are well-fitted by an exponential of mean about 2000.
This all makes me think it might be a
convergence issue. Perhaps you can transform your data for estimation
and then transform it back (not sure if this would yield equivalent
results)?
fitdist(test + 10^4, "gamma")
No.
fitdist(test/10^4, "gamma")
Yes. This indeed a scaling issue: the estimated rate is very small.
Good luck,
Josh
On Wed, Apr 27, 2011 at 9:42 PM, vioravis <viora...@gmail.com> wrote:
There was a small error in the data creation step and have fixed it as below:
test <- c(895.1358,2915.7447,335.5472,1470.4022,194.5461,1814.2328,
1056.3067,3110.0783,11441.8656,142.1714,2136.0964,1958.9022,
891.89,352.6939,1341.7042,167.4883,2502.0528,1742.1306,
837.1481,867.8533,3590.4308,1125.9889,1200.605,4321.0011,
1873.9706,323.6633,1912.3147,865.6058,2870.8592,236.7214,
580.2861,350.9269,6842.4969,1886.2403,265.5094,199.9825,
1215.6197,7241.8075,2381.9517,3078.1331,5461.3703,2051.3997,
751.6575,714.3536,598.4539,425.6656,215.2103,608.785,
369.4744,2398.6506,918.6844,525.6925,2549.3694,4108.8983,
2824.0758,1068.7508,249.995,3863.9839,1152.1506,531.6844)
Any help would be appreciated. Thank you.
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--
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
http://www.joshuawiley.com/
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--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (self)
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