I have a data set of the following figures
Acct Loss
A 250,000
B 325,000
C 450,000
D 125,000
E 680,000
F 110,000
G 997,000
H 500,000
I'd like to produce an output set of total loss by the following distributions at the 50th, 70th, 90th, 95th and 99th percentiles: Burr, Pareto and LogNormal.
In addition, I'd like to produce the K-S statistic, the A-D statistic and KS-Test p-values for the Burr, Pareto and LogNormal distributions (fit statistics for the distributions).
I thought I could use PROC SEVERITY in the following manner:
proc severity data=sample_set;
model loss;
dist burr;
dist pareto;
dist logn;
run;
Unfortunately, the code is not correct.
Any suggestions on how to tackle this challenge would be greatly appreciated. Thanks.
Your syntax is a bit off. Also, take out the comma from the numbers.
data a;
input Acct $ y;
datalines;
A 250000
B 325000
C 450000
D 125000
E 680000
F 110000
G 997000
H 500000
;
proc severity data=a crit=aicc;
loss y;
dist _predefined_;
run;
Note: you use LOSS to specify the response variable. The keyword _PREDEFINED_ is used to request fits for all the predefined distribution models. But a warning: n=8 is really very small for this type of analysis. It will be difficult to distinguish the models with 8 data points. But the above does "work"..
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