@rhermans gave you the answer in a comment.
data = Flatten[{595, 1431, 4347, 5554, 6279, 6887, Table[7100, {10}]},
1];
wcd = CensoredDistribution[{leftCensor, rightCensor}, WeibullDistribution[a, b]];
FindDistributionParameters[data, wcd]
(* {leftCensor -> 595.,rightCensor -> 7100.,a -> 1.1017281600526971,b -> 14712.282885780418} *)
DistributionFitTest[data, wcd, "PearsonChiSquare"]
(* 0.05125258285736953 *)
If leftCensor
is known to be zero, then you could use
wcd = CensoredDistribution[{0, rightCensor}, WeibullDistribution[a, b]];
FindDistributionParameters[data, wcd]
(* {rightCensor -> 7100.,a -> 1.3102715493177497,b -> 12977.89931682844} *)
DistributionFitTest[data, wcd, "PearsonChiSquare"]
(* 0.17573433564422514 *)
While for this particular distribution DistributionFitTest
chooses PearsonChiSquare
, one should make this explicit or at least determine which test was used. If you choose some of the other tests, you'll likely see a warning that the P-value is bogus due to the fact that you've had to estimate some of the parameters.
And, finally, if you only have 7 unique values, the best you can do when the P-value is large is to say "Well, maybe there aren't any gross departures observed."
EventData
. The solution probably goes in the lines ofFindDistributionParameters[cdata, CensoredDistribution[{leftCensor, rightCensor}, WeibullDistribution[a, b]]
$\endgroup$ – rhermans Nov 4 '14 at 11:49DistrubutionFitTest
accept data withHead == EventData
? $\endgroup$ – bobthechemist Nov 4 '14 at 13:07DistributionFitTest
does not work withEventData
. $\endgroup$ – Andy Ross Nov 4 '14 at 14:18