Fitting distributions directly from a frequency table

[Frootloops]

Hi there,

I was wondering if there is a way to fit a distribution directly from a frequency table without having the raw data. I've tried using proc univaraite but you can't use the weight

option with the histrogram option. I'm a bit stuck.

Thank you

[data_null__ · Accepted solution]

I think you would use FREQ statement.

data Plates;
   label Gap = 'Plate Gap in cm';
   input Gap @@;
   datalines;
0.746  0.357  0.376  0.327  0.485 1.741  0.241  0.777  0.768  0.409
0.252  0.512  0.534  1.656  0.742 0.378  0.714  1.121  0.597  0.231
0.541  0.805  0.682  0.418  0.506 0.501  0.247  0.922  0.880  0.344
0.519  1.302  0.275  0.601  0.388 0.450  0.845  0.319  0.486  0.529
1.547  0.690  0.676  0.314  0.736 0.643  0.483  0.352  0.636  1.080
;

proc freq data=plates noprint;
   tables gap / out=PlatesFreq;
   run;

title 'Distribution of Plate Gaps';
ods graphics off;
ods select ParameterEstimates GoodnessOfFit FitQuantiles MyHist;
proc univariate data=PlatesFreq;
   var Gap;
   freq count;
   histogram / midpoints=0.2 to 1.8 by 0.2
               lognormal
               weibull
               gamma
               vaxis   = axis1
               name    = 'MyHist';
   inset n mean(5.3) std='Std Dev'(5.3) skewness(5.3)
          / pos = ne  header = 'Summary Statistics';
   axis1 label=(a=90 r=0);
run;

[Frootloops]

Thanks I think that is what I was looking for!

Now just a smaller problem I hope you would be able to help me with (it looks like you know your stuff ):

Lets say I already have binned my data according to a certain format (unequal bins). Is there a way to suppress proc univariate from creating automatic bins for the data and fit the distribution according to my binning format?

[data_null__]

Not sure but perhaps one of the MIDPOINT related options is what you need.  Perhaps show an example of your data and univariate code.

[Frootloops]

The data is formatted and binned according to this:

LOW     <-    0       =  'X0'

0.00000 <-  0.00001 =  'X1'

0.00001 <-  0.00002 =  'X2'

0.00002 <-  0.00005 =  'X3'

0.00005 <-  0.00007 =  'X4'

0.00007 <-  0.00010 =  'X5'

0.00010 <-  0.00012 =  'X6'

0.00012 <-  0.00017 =  'X7'

0.00017 <-  0.00025 =  'X8'

0.00025 <-  0.00035 =  'X9'

0.00035 <-  0.00047 =  'X10'

0.00047 <-  0.00062 =  'X11'

0.00062 <-  0.00080 =  'X12'

.

.

.

0.50000 <-  0.65000 =  'X97'

0.65000 <-  0.80000 =  'X98'

0.80000 <-  1.00000 =  'X99'

1.00000 <- HIGH     =  'X101'

This formatting is applied and to spread out the data a little bit, otherwise everyhing is thrown into the first two or three bins. So I have my bins and I have a frequency in each and now I want to fit a distribution to the data.