Subject: [Fwd: [ippm] statistics techniques]

From: Sandrine Vaton <[email-masked]>
Date: Thu, 20 Feb 2003 15:37:38 +0100

Subject: Re: [ippm] statistics techniques
From: Sandrine Vaton <[email-masked]>
To: stanislav shalunov <[email-masked]>
Date: Wed, 19 Feb 2003 13:34:47 +0100

I suggest that you enrich your model as follows:

1/ the packet can be lost (with probability p) or delivered with probability
(1-p)
2/ if the packet is in the second class (the packets that have been delivered
or that will be delivered one day) then the rtt is a random variable whose
probability density function is f(x) (for example an exponential distribution
with mean 1/lambda). The domain of definition of f(x) being the real positive
line.

If you are in the second class then it is possible that the packet has not yet
arrived because the observation window is of finite size but you have the
information that rtt>rtt_max and this information should be taken into account
in your estimation procedure.

Sandrine Vaton
http://perso-info.enst-bretagne.fr/~vaton

stanislav shalunov a écrit :

> "gab.seun jones.ewulomi" <[email-masked]> writes:
>
> > Im doing a active test just using ping(via script). I have the script to
> > ping a device(100 counts) then send it to a file.
> >
> > My main question is what will give a more accurate rtt.
> >
> > 1)taking the mean of all 100 pings
> > 2)median
> > 3)mode
>
> How can you compute the mean when some of the values are close to
> infinity (losses)?
>
> Median and minimum make a lot more sense.
>
> --
> Stanislav Shalunov              http://www.internet2.edu/~shalunov/
>
> A fanatic is one who can't change his mind and won't change the
> subject.                                   -- Winston Churchill
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