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Continuous empirical distribution

Valued Contributor
Valued Contributor

Dear community members,

I performed an analysis of customers inter-arrival times for my case and I have a list of 196 observations (each observation is the inter-arrival time between 2 customers). I used the data fit tool but no distribution fits the data. Then I’m trying to use an empirical continuous distribution.

The problem is that I should define the number of classes, the upper bound and the lower bound of each class.

I thought I could use as classes the same that the data fit creates (picture below)

temporaneo.PNG

It actually tells me that I could use 14 classes, but what about the lower and upper bound of each class?

Do you have any suggestion on that?

3 REPLIES 3

Re: Continuous empirical distribution

Siemens Phenom Siemens Phenom
Siemens Phenom

Hi Alessandro,

 

I'd recommend to choose for the boundaries the mid value of the intervals:

 

0, (210+350)/2, ~56

(210+350)/2, (350+490)/2, ~31

.

.

.

 

Regards,

Ralf
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Re: Continuous empirical distribution

Valued Contributor
Valued Contributor

Hi Ralf,

thanks for your reply.

I just saw that in the tab "evaluation" there is "frequency table".  This is the view

temporaneo.PNG

I guess it is the way the Datafit divided the input data, along with the the frequencies. Is this good for the empirical distribution? I mean, can I just insert these data instead of doing the calculation you suggested before?

Re: Continuous empirical distribution

Siemens Phenom Siemens Phenom
Siemens Phenom

Right, this is the better choice, since you can just copy these values.

Regards,

Ralf
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