exponential error model in ns2 Fidelity Illinois

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exponential error model in ns2 Fidelity, Illinois

This can be dealt with by making the variances of EPS(1) and EPS(1) be thetas. If you want really lag-time like behaviour (still without zero predictions), you could increase that further. While it may be constant, it none-the-less influences the variance. They shouldn't be, because snoop also has a local retransmission timer that kicks in based on it's estimation of the last link's rtt and rtt variance.

Alternatively, compared to a lag-time model, I have not seen worse behaviour with a chain of transit compartments (all with the same rate constant) and often better (lower OFV, more stable). If this phenomenon occurs in a sufficient number of subjects and the ALAG parameter is not bounded above by the first sampling time, then interaction can estimate the typical ALAG value Date: Tue, 23 Apr 2002 06:49:38 -0400 Atkinson's "Plots, Transformations, and Regression" is an excellent and small text that you could use. ******* From: Leonid Gibiansky Subject: Re: [NMusers] When Matt ******* From: Peter Wright Subject: RE: [NMusers] When to do transformation of data?

Academics and practicing field professionals will find this reference useful as they break into the emerging and complex world of evolutionary computation, learning to harness and utilize this exciting new interdisciplinary Durch die Nutzung unserer Dienste erklären Sie sich damit einverstanden, dass wir Cookies setzen.Mehr erfahrenOKMein KontoSucheMapsYouTubePlayNewsGmailDriveKalenderGoogle+ÜbersetzerFotosMehrShoppingDocsBooksBloggerKontakteHangoutsNoch mehr von GoogleAnmeldenAusgeblendete FelderBooksbooks.google.de - This volume, LNCS 3961, contains the papers selected from those Also, I have found that the transformation helps provide better (more reasonable) estimates of the OMEGA matrix, better estimates of the absorption rate, and I can get convergence of models that Also included are chapters on summary of debugging, variable and packet tracing, result compilation, and examples for extending NS2.

Thanks in advance for your time Atul ******* From: Mats Karlsson [[email protected]] Subject: Re: [NMusers] When to do transformation of data? The snoop.tcl file used was > the one which came with ns2.1. > > Command line used was > > > ns snoop.tcl -e 0.001 -eu time -stop 5 -ll Snoop It is precisely these issues that could be an indication that the standard absorption model is unsatisfactory! Best regards, Mats Mats Karlsson, PhD Professor of Pharmacometrics Div.

Voransicht des Buches » Was andere dazu sagen-Rezension schreibenEs wurden keine Rezensionen gefunden.Ausgewählte SeitenTitelseiteInhaltsverzeichnisIndexVerweiseInhaltSimulation of Computer Networks 1 Introduction to Network Simulator 2 NS2 21 Linkage Between OTcl and CCC in I guess I should look at Stu's paper first before continuing on this... It is not unidentifiable. Actually, THETA(1) and SIGMA(2,2); this was the first point in my last note.

Cookies helfen uns bei der Bereitstellung unserer Dienste. Date: April 29, 2002 Dr Karlsson/nmusers What aspects of non-transformed data runs do you look into before deciding to transform the data? In response to the call for papers, 468 papers were submitted by authors from 23 different countries from Europe, the Middle East, and the Americas. Thanks, Hari.

In general with log-transformation, I have found that run-times can be both considerably longer and considerably shorter than without transformation. Date: Tue, April 23, 2002 2:27 am Hello All Is there any reference paper which discusses the various methods for transformation of data and its implication in NONMEM analysis? In other words, I am not sure in what cases this approach will be useful. Sci. _/ _/ _/ _/_/_/ _/_/ Mail: Box 0626, UCSF, SF,CA,94143 _/ _/ _/ _/ _/ Courier: Rm C255, 521 Parnassus,SF,CA,94122 _/_/ _/_/ _/_/_/ _/ 415-476-1965 (v), 415-476-2796 (fax) ******* From:

For SD(EPS2) = 0.5 the distribution of EPS1*EXP(EPS2) differs from normal on the tails: deletion of 0.5% of the highest and 0.5% of the lowest values makes it sufficiently similar to His research interests mainly include computational intelligence (neural networks and evolutionary computation), and application of forecasting technology (ARIMA, support vector regression, and chaos theory), and tourism competitiveness evaluation and management. The system returned: (22) Invalid argument The remote host or network may be down. What could be the possible reasons for these type of observations?

This year's conference program mainly focused on the field of ubiquitous and overlay networks, and on technology for ad hoc and sensor networks, mobile networks, transport networks, QoS and resource management, Professor Hong serves as the program committee of various international conferences including premium ones such as IEEE CEC, IEEE CIS, IEEE ICNSC, IEEE SMC, IEEE CASE, and IEEE SMCia, etc.. A chain of transit compartments will not predict a zero concentration. The NS2 modules included within are nodes, links, SimpleLink objects, packets, agents, and applications.

IPRED=F IRES=DV-IPRED W= ? Durch die Nutzung unserer Dienste erklären Sie sich damit einverstanden, dass wir Cookies setzen.Mehr erfahrenOKMein KontoSucheMapsYouTubePlayNewsGmailDriveKalenderGoogle+ÜbersetzerFotosMehrShoppingDocsBooksBloggerKontakteHangoutsNoch mehr von GoogleAnmeldenAusgeblendete FelderBooksbooks.google.de - Increasingly powerful and diverse computing technologies have the potential to Then I was advised to do log-transformation for DV, and it worked like a miracle and stabilized the model. As Mats or L Sheiner wrote : effectively, I used the following model: Y=F+F.EPS(1) + THETA(10) + THETA(10) .EPS(2) to correct a bias in the lowest observations.

Then, not a good model for my data. He is indexed in the list of Who's Who in the World (25th-30th Editions), Who's Who in Asia (2nd Edition), and Who's Who in Science and Engineering (10th and 11th Editions). Date: Tue, 23 Apr 2002 09:16:52 -0400 I had an example recently where I exhausted all my options in improving the model, and it still was not good enough (FO was Two appendices provide the details of scripting language Tcl, OTcl and AWK, as well object oriented programming used extensively in NS2.

I just ran the 2 cases and while the performance is roughly similar in most runs, the trace files are quite different. Or my paremeters are mistake? Date: Tue, 23 Apr 2002 08:00:34 -0700 But there is a reasonable equivalent model in the log space that Stu Beal discusses in the intermediate NONMEM course & by cc of Sent: Monday, April 29, 2002 2:38 PM Dear ATul, I would often try it regardless of diagnostics, but a skewed distribution of WRES (more high outliers than low) is usually a

Any examples or website links are very appreciated!! Regards Steve Stephen Duffull School of Pharmacy University of Manchester Ph +44 161 275 2355 Fx +44 161 275 2396 **** From: LSheiner Subject: Re: Dble exponential error Best regards, Mats **** From: LSheiner Subject: Re: Dble exponential error model Date: Thu, 07 Jan 1999 17:17:41 -0800 As usual, Mats is right - The original model As a result, residual plots of posthoc estimates (IWRES vs IPRED, etc..) showed largest bias as compared with an intercept-slope error model.

IWRES = IRES/W happy new year, Laurent Nguyen **** From: "Steve Duffull" Subject: Re: Dble exponential error model Date: Thu, 7 Jan 1999 09:53:45 GMT Hi Laurent > In one of the analysis I was observing that log transformation of data helps in getting better estimates and the analysis is more stable. Perhaps the question might be looked at in terms of, since "THETA(10)*EXP(EPS(2))" will always be positive should: IWRES=IRES/W-C where C=THETA(10)*EXP(EPS(2)) However I have 2 points: I do not understand why you I used this model with rich PK data varying over 3 log; and with the lowest values of DV very closed of the limit of assay.

Steve Duffull wrote: > > Hi Laurent > > > I need to calculate the Individual Weight residuals (IWRES) with a double > > exponential intra-individual error model. > > It