I got this list:
list={{0, 0}, {1, 0}, {2, 0}, {3, 0}, {4, 0}, {5, 1}, {6, 2}, {7, 3}, {8, 3}, {9, 8}, {10, 5}, {11, 7}, {12, 23}, {13, 11}, {14, 8}, {15, 10}, {16, 2}, {17, 2}, {18, 0}, {19, 1}, {20, 0}, {21, 1}}
I split this list in two:
listsize = Table[Part[list, i, 1], {i, 1, 22}];
listfreq = Table[Part[list, i, 2], {i, 1, 22}];
I used the WeightedData
on listsize and listfreq as:
weigthlist=WeightedData[listsize, listfreq]
I used this in aim to use the Mathematica Histogram
func as:
hist1=Histogram[weigthlist, 22, "PDF"]
First question, how can I have the same histogram without weighting? Second question, and it's the most important, how can I fit my histogram with the good distribution (Gaussian, Cauchy, etc.)? I read many answer but none of them helped me.
WeightedData[list[[All,1]], list[[All,2]]]
or evenWeightedData@@Transpose[list]
. You can reconstruct a set of observations and plot the histogram withFlatten[Table@@@list] // Histogram
. Probably you would also want to look at the documentation ofFindDistribution
(which can be directly applied likeFlatten[Table@@@list] // FindDistribution
for distribution fitting.) It's interesting that binning differs between these approaches! $\endgroup$ – kirma May 22 at 9:30