similar to: distribution fitting

Hello, I have a data frame that looks like this (containing interarrival times): > str(df) 'data.frame': 18233 obs. of 1 variable: $ Interarrival: int 135 806 117 4 14 1 9 104 169 0 ... > head(df) Interarrival 1 135 2 806 3 117 4 4 5 14 6 1 > This corresponds to the time differences (in ms) of a poisson arrival

Can someone explain to me in what way the new (dpqr)gamma parameter can be interpreted as a rate (when shape != 1)? The only gamma rate that I am aware of is the hazard rate given by dgamma/(1-pgamma), the log of which is returned by my hgamma function (event library). Jim -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I was trying to generate random numbers with a gamma distribution. In R the function is: rgamma(n, shape, rate = 1, scale = 1/rate). My question is that if X~gamma(alpha, beta) and I want to generate one random number where do I plug alpha and beta in rgamma? and, what is the meaning and use of rate? Thanks for your attention, Jorge [[alternative HTML version deleted]]

Hi all, I'm looking into congestion control for Vorbis RTP and I'm wondering if it's not too early to define a mechanism which would help bitrate peeling. The client can send a standard receiver report stating the interarrival jitter and packets loss. Once a certain jitter/loss point is reached the server peels off a pre-determined bitrate fraction from the stream, eg 128k would

IM 2013 The 13th IFIP/IEEE Symposium on Integrated Network and Service Management Ghent, Belgium, 27-31 May 2013 http://www.im2013.org/ (Paper Submission Date: 16 August 2012) "Smart Management in a Virtualized World" The 13th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2013) will be held 27-31 May 2013 in the beautiful city center of Ghent, Belgium and

IM 2013 The 13th IFIP/IEEE Symposium on Integrated Network and Service Management Ghent, Belgium, 27-31 May 2013 http://www.im2013.org/ (Paper Submission Date: 16 August 2012) "Smart Management in a Virtualized World" The 13th IFIP/IEEE Symposium on Integrated Network and Service Management (IM 2013) will be held 27-31 May 2013 in the beautiful city center of Ghent, Belgium and

Asterisk 11.1.0 Various soft-phone SIP clients call center with 10-12 agents online at once using asterisk queue Occasionally an agent will get a call (or more often a series of calls in a row) where neither party can hear the other, or can only hear each other sporadically. A MixMonitor recording of the call plays only the caller - none of the agent's audio is heard in the recording.

Dear friends, Over the past weeks, I have been asking a lot of questions about how to use R in Bayesian analysis. I am brand new to R, but I am very pleased with it. I started with winbugs but I found winbugs to be a limited software, not bad but has several limitations. By contrast, R allows the analyst to tackle any problem with a huge set of tools for any kind of analysis. I love R. In