similar to: R-beta: extreme value dose-response fit

This practical problem in maximum likelihood estimation must be encountered quite a bit. What do you do when a data point has a probability that comes out in numerical evaluation to zero? In calculating the log likelihood you then have a log(0) problem. Here is a simple example (probit) which illustrates the problem: x<-c(1,2,3,4,100) ntrials<-100 yes<-round(ntrials*pnorm((x-3)/1))

Hi, I have some problems when using AlgDesign->optFederov() generating designs. I have 6 variables, all factors. 3^2 and 4^4, I want to have a design that can take care of main effects and two interactions within 2 pair of variables v3-v4 and v5-v6, the following is the code ################ require(AlgDesign) set.seed(1) levels = c(v1=3,v2=3, v3=4,v4=4,v5=4,v6=4)

Hi all, I have a problem in including my plot in a loop. Here is a simple example for one plot: # Plot simple graph with super- and subscript a<-c(1,2,3,4) b<-c(1,2,3,4) plot(x=a,y=b, ylab=expression(paste("Apple"["P"])), xlab=expression(paste("Banana"^"th")),

Hello all I have done some fitting of pnorm functions to dose-response data, so I could calculate EC50 values (dose where the response is 0.5). I used the nlm function for this, so I did not get any information about the confidence intervals of the fitted parameters. What would be a good way to do such a probit fit, or is there a package which I could use? Best regards Johannes Ranke

I can not understand why this fails > > faicoutput2 <- list(stuff21 = as.numeric(faicout$coefficients[2]), + stuff31=as.numeric(faicout$coefficients[3]), + stuff41=as.numeric(faicout$coefficients[4]), + stuff32=(stuff21-stuff31), + stuff42=(stuff21-stuff41), +

Dear R users, I?m trying to optimize simultaneously two binomials inequalities used to acceptance sampling, which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

I am trying to do a MLE fit of the weibull to some data, which I attach. fitweibull<-function() { rt<-scan("r/rt/data2/triam1.dat") rt<-sort(rt) plot(rt,ppoints(rt)) a<-9 b<-.27 fn<-function(p) -sum( log(dweibull(rt,p[1],p[2])) ) cat("starting -log like=",fn(c(a,b)),"\n") out<-nlm(fn,p=c(a,b), hessian=TRUE)

Dear R users, I have used the AlgDesign package to construct a D-optimal exp. design from a file containing a set of allowed runs. The code for the optFederov call is below: #Using optFederov ------------------------------ library(AlgDesign) options(contrasts=c("contr.sum","contr.poly")) file<- read.table("C:/Upstream/Designs/Vodacom Tanzania phase1

Dear R users, I?m trying to optimize simultaneously two binomials inequalities (used in acceptance sampling) which are nonlinear solution, so there is no simple direct solution. Please, let me explain shortly the the problem and the question as following. The objective is to obtain the smallest value of 'n' (sample size) satisfying both inequalities: (1-alpha) <= pbinom(c, n, p1)

Hi CentOS users, The centos-promo team is looking for your help. Is anyone interested in creating nice CentOS screenshots ? We can have them on the wiki as well for future articles or presentations. A good screenshot should: + Be clear on what it is showing - applications like eg. inkscape should have a file opened - files opened in applications should make clear what the

I'm analysing some ID50 data for 2 different groups and had already calculated this by hand using Reed-Muench formula, when I came across the dose.p function in R. I have 2 queries: 1) dose.p gives me a different answer to Reed-Muench, and actually I suspect wrong answer, given that the dose.p result dosage stated to infect 50% is actually stronger than the dose used in my experiments caused

I have the following problem. I have measured a dose response curve (binary response, continuous dose) on a grid of x,y positions. I would like to produce a grey-level plot that shows the LD50 at each (x,y) position. I am thinking that I have to do something like fit<-glm(resp ~ x*y + dose, family = binomial) Corrections welcome. But from here I don't know how to get LD50, and certainly

Hi, I want to fit nonlinear dose-response curves, as "fun(X,a,b,c)", for each of our 5 trail locations. Our data basis is something like location plot year dose response For each location there are 4 plots as repetitions (over 3 years). So the interactions "location*year" and "location*plot" should be random effects. There are some examples in "Mixed-Effects

Hi everybody, CentOS will be present for the first time at the Technical Dutch Open Source Event (T-DOSE) in Eindhoven, NL. We have a booth at the entrance as well as a presentation about Virtualization, presented by Daniel de Kok (danieldk). No doubt the presentation will include information about the new CentOS Virtualization SIG ! (Other topics are still accepted for T-DOSE) If you're

Dear R-Helpers Has anyone written a script for the dose proportionality assessement using the power model and the confidence interval criteria as described in - Gough at al. Assessment of dose proportionality: report from the statisticians in the pharmaceutical industry in Drug Information Journal,1995, 29:1039-1048 and/or - Smith et al. Confidence interval criteria for assessment of dose

Dear all, I can use the very nice drc package (multdrc()) to model and plot a dataframe containing dose and response values. I can also use predict.drc() to yield response values given a dose. I need to do the opposite, estimate a dose given the response. The general predict documentation seems to say that this is possible, but it does not appear that predict.drc has that capability.

Dose anybody really can tell me what really need for compile wine for solaris x86? I have tried everything I can think about but ended up with a bunch of errors about need libwine.unicode and somethings Thanks for your help!

Hi all using samba3_alpha20 dose any know what this error in the samba log file is [2002/10/11 13:46:20, 0] profile/profile.c:profile_setup(140) ERROR: we did not create the shmem (owned by another user) [2002/10/11 13:46:20, 0] smbd/server.c:main(813) ERROR: failed to setup profiling thanks for any help Eli =============================== Eli Kleinman B&H Photo - Video Pro Audio 420

-------------- eth0------eth1 eth0------------ |211.241.219.xx | --- | ROUTER | --- |192.168.1.4 | --------------- --------- ------------ when i send traffic from ROUTER to 211.241.219.xx or 192.168.1.4(masquraded), the filter works fine... In ROUTER, tc filter policy is like this: tc filter add dev eth0 parent 1:0 protocol ip u32 match ip dport 80 0xffff

>My CPU is Centaur VIA Nehemiah with 998.715 MHz processor not INTEL CPU. Common Sense dude - The Intel IPPs work only for Intel CPUs. Remove the codec_g729.so file from /usr/lib/asterisk/modules folder and restart asterisk Check if it is working by starting as under: UnixPrompt# asterisk -cvvvvvvvvvvvvvvvvvvf Once this loads correctly use 'Stop now' and restart with command