RE: [R] Discussion: Spam on R-help
Well ... I have SpamCop on my incoming e-mail, and it snagged every one of the beasts ... *And* reported them to whatever authorities SpamCop has available to handle spam reports. Those few ISPs that listen to SpamCop reports will chastise the spammers for their aggression. SpamCop costs $30US a year. If there's a way to hook it up to the incoming port on the R-help mailing list, I'd be willing to contribute $30. It also catches viruses for those of us blessed (?) with Windows. -- M. Edward (Ed) Borasky mailto:[EMAIL PROTECTED] http://www.borasky-research.net Suppose that tonight, while you sleep, a miracle happens - you wake up tomorrow with what you have longed for! How will you discover that a miracle happened? How will your loved ones? What will be different? What will you notice? What do you need to explode into tomorrow with grace, power, love, passion and confidence? -- L. Michael Hall, PhD __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Dismal R performance of Athlon moble CPU?
I haven't gotten around to assembling the toolset required to build R on Windows, since most of what I do is smallish interactive problems. However, another possibility would be to load CygWin/XFree86 on your laptop (which I've done), then download Atlas 3.5.7 from SourceForge (which I've done), then build Atlas with CygWin(which I've done) and then build a second version of R under CygWin using Atlas, and use the CygWin/Atlas R for the heavy number-crunching jobs. This last I haven't done, so I can't say whether there are any gotchas, but everything else I've done with CygWin/XFree86 has worked. My laptop is a Compaq Presario with a 1.67 GHz Athlon XP. Atlas screams on it; the Atlas folks were grinning when I sent them the log. Atlas has an assembly language kernel for Athlons (and P4s as well IIRC). Oh, yeah ... If you do try my scheme, make sure you don't have spaces in the paths ... Atlas still isn't immune to that sort of thing under CygWin. -- M. Edward (Ed) Borasky mailto:[EMAIL PROTECTED] http://www.borasky-research.net Suppose that tonight, while you sleep, a miracle happens - you wake up tomorrow with what you have longed for! How will you discover that a miracle happened? How will your loved ones? What will be different? What will you notice? What do you need to explode into tomorrow with grace, power, love, passion and confidence? -- L. Michael Hall, PhD -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Jason Liao Sent: Wednesday, July 23, 2003 1:44 PM To: [EMAIL PROTECTED] Subject: [R] Dismal R performance of Athlon moble CPU? I have been using a laptop computer of Pentium III 1.13 Ghz. I heard that AMD's Athlon has excellent floating point capacity. So I bought a Athlon 2200+ laptop yesterday. I expected that new Athlon 2200+ will be twice as fast as the P III 1.13 GB. I ran a R simulation program and the new computer is only 30% faster, in fact slightly slower than a Celeron 1.50 GB laptop. I am very disappointed by this. What is your experience with Athlon? Should I stick to Intel in the future? Thanks. By the way, the OS is Windows XP home edtion. Jason = Jason G. Liao, Ph.D. Division of Biometrics University of Medicine and Dentistry of New Jersey 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-8611, fax (732) 235-9777 http://www.geocities.com/jg_liao __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo /r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] bug?
To be more precise, the decimal number 0.1 does not have an exact binary equivalent. A long time ago, there was a book called, IIRC, Pascal with Style or something of that ilk, which set out the warning Never compare floating point numbers for equality. -- M. Edward (Ed) Borasky mailto:[EMAIL PROTECTED] http://www.borasky-research.net Suppose that tonight, while you sleep, a miracle happens - you wake up tomorrow with what you have longed for! How will you discover that a miracle happened? How will your loved ones? What will be different? What will you notice? What do you need to explode into tomorrow with grace, power, love, passion and confidence? -- L. Michael Hall, PhD -Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] On Behalf Of Uwe Ligges Sent: Monday, July 14, 2003 1:10 AM To: Marc Vandemeulebroecke Cc: [EMAIL PROTECTED] Subject: Re: [R] bug? Marc Vandemeulebroecke wrote: Dear R programmers, is there a sensible explanation for the following behaviour? The second command seems not to be interpreted correctly. seq(0.6, 0.9, by=0.1) == 0.8 [1] FALSE FALSE TRUE FALSE seq(0.7, 0.9, by=0.1) == 0.8 [1] FALSE FALSE FALSE c(0.7, 0.8, 0.9) == 0.8 [1] FALSE TRUE FALSE seq(0.9, 0.7, by=-0.1) == 0.8 [1] FALSE TRUE FALSE I am running R version 1.7.1 on XP and NT. Thanks, Marc -- __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help It is correct, just an instability of the representation of that floating point number, because (regularly) floating point numbers cannot be represented exactly. Uwe Ligges __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo /r-help __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Fitting inter-arrival time data
Unfortunately, the data are *non-negative*, not strictly positive. Zero is a valid and frequent inter-arrival time. It is, IIRC, the most likely value of a (negative) exponential distribution. -- M. Edward (Ed) Borasky mailto:[EMAIL PROTECTED] http://www.borasky-research.net Suppose that tonight, while you sleep, a miracle happens - you wake up tomorrow with what you have longed for! How will you discover that a miracle happened? How will your loved ones? What will be different? What will you notice? What do you need to explode into tomorrow with grace, power, love, passion and confidence? -- L. Michael Hall, PhD -Original Message- [snip] if you data are positive, you could use sm.density(..., positive=TRUE) __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
RE: [R] Fitting inter-arrival time data
Thanks!! It does look like the easiest thing is direct ML; the code for a normal mixture is in the book, so all I have to do is modify that for a sum of a hyper-exponential, for which I have an approximate mean and CV, and a normal, for which I have an approximate mean and SD. I have two big peaks, one near zero which is probably hyperexponential with a CV about 3, and the other near 600 seconds (a refresh that happens every ten minutes) which looks Gaussian with a very small standard deviation. I think what I'm going to do is fit the two peaks using ML, since I know where they are, then subtract them out and look at the structure of the residuals. The stuff over 600 seconds is sparse and totally uninteresting. After I'm done with this, I get to look at the distribution of the network traffic. The good news is that I get those inter-arrival times to the nearest microsecond. :) -- M. Edward (Ed) Borasky mailto:[EMAIL PROTECTED] http://www.borasky-research.net Suppose that tonight, while you sleep, a miracle happens - you wake up tomorrow with what you have longed for! How will you discover that a miracle happened? How will your loved ones? What will be different? What will you notice? What do you need to explode into tomorrow with grace, power, love, passion and confidence? -- L. Michael Hall, PhD -Original Message- [snip] For all of these see MASS (the book) and its on-line complements. __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
[R] Fitting inter-arrival time data
I have a collection of data which includes inter-arrival times of requests to a server. What I've done so far with it is use sm.density to explore the distribution, which found two large peaks. However, the peaks are made up of Gaussians, and that's not really correct, because the inter-arrival time can never be less than zero. In fact, the leftmost peak is centered at somewhere around ten seconds, and quite a bit of it extends into negative territory. What I'd like to do is fit this dataset to a mixture (sum) of exponentials, hyper-exponentials and hypo-exponentials. My preference is to use the well-known branching Erlang approximation (exponential stages) to the hyper- and hypo-exponentials. In this approximation, a distribution is specified by its mean and coefficient of variation. So far, what I've been able to come up with in a literature search has been something called the Expectation Maximization algorithm. And I haven't been able to locate R code for this. So my questions are: 1. Is EM the right way to go about this, or is there something better? 2. Is there some EM code in R that I could experiment with, or do I need to write my own? 3. Is there a way this could be done using the existing R kernel density estimators and some kind of kernel that is zero for negative values of its argument? -- M. Edward (Ed) Borasky mailto:[EMAIL PROTECTED] http://www.borasky-research.net Suppose that tonight, while you sleep, a miracle happens - you wake up tomorrow with what you have longed for! How will you discover that a miracle happened? How will your loved ones? What will be different? What will you notice? What do you need to explode into tomorrow with grace, power, love, passion and confidence? -- L. Michael Hall, PhD __ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help
