search for: lrc

...ypes (84 observations in total), but den df for each parameter of the model is 64. Isn’t it too high? Your help is greatly appreciated, Julia Summary of the CO2 example: > summary(fm4CO2.nlme) Nonlinear mixed-effects model fit by maximum likelihood Model: uptake ~ SSasympOff(conc, Asym, lrc, c0) Data: CO2 AIC BIC logLik 388.4185 420.0191 -181.2092 Random effects: Formula: list(Asym ~ 1, lrc ~ 1) Level: Plant Structure: General positive-definite, Log-Cholesky parametrization StdDev Corr Asym.(Intercept) 2.349640 As.(I) lrc.(Intercept) 0.07...

RedHat AS 2.1 kernel 2.4.9-e.16 with kbr5-1.2.7 I've been playing with ADS features of samba-3.0alpha21 and am having problems getting winbind to work. I can join the domain: [root@asecl etc]# net ads join Joined 'ASECL' to realm 'ASE-LRC-AD.AE.UTEXAS.EDU' After joining the domain, I can use the other 'net ads' options of user, group, status and info. Can also use the smbclient with the -k option to browse shares on the AD server. When starting winbind, I get the following error which just keeps repeating ever...

Hi List, I have to compare a relationship between y and x for two locations. I found logistic regression fits both datasets well, but I am not sure how to test if relationships for both sites are significantly different. I searched the r site, however no answers exactly match the question. I used Tukey's HSD to compare two means, but the relationship in my study was not simply linear. So I

...function SSweibull(). However, I often got two error messages: 1) # Example days <- c(163,168,170,175,177,182,185,189,196,203,211,217,224) height <- c(153,161,171,173,176,173,185,192,195,187,195,203,201) dat <- as.data.frame(cbind(days,height)) fit <- nls(y ~ SSweibull(x, Asym, Drop, lrc, pwr), data = dat, trace=T, control=nls.control(minFactor=1/100000)) Error in nls(y ~cbind(1, -exp(-exp(lrc)* x^pwr)), data = xy, algorithm = “plinear”, :                           step factor 0.000488281 reduced below `minFactor` of 0.000976562 I tried to avoid this error by reducing the step f...

Dear all I encountered strange behaviour of augPred with virtually the same data First I made groupedData object. > mar.g<-groupedData(rutilizace~doba|int, data=mar) When I perform nlme on complete dataset I get an error with augPred > fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g) Warning message: c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x), exp(-exp(lrc) * x)), data = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = \"plinear\"): singular gradient") > fit1<-nlme(fit) > pl...

...range behaviour of augPred with virtually the same data > > First I made groupedData object. >> mar.g<-groupedData(rutilizace~doba|int, data=mar) > > When I perform nlme on complete dataset I get an error with augPred >> fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g) > Warning message: > c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x), exp(-exp(lrc) * x)), data = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = \"plinear\"): singular gradient") >> fit1<-nlm...

...y the same > > data > > > > First I made groupedData object. > >> mar.g<-groupedData(rutilizace~doba|int, data=mar) > > > > When I perform nlme on complete dataset I get an error with augPred > >> fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g) > > Warning message: > > c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x), exp(-exp(lrc) * x)), data > = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = > \"plinear\"): singular gradient") &...

I ran into a problem trying to make a plot from a file that's read using source. Basically, I have the following code in a file "plot.R" : library(nlme) data(Loblolly) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) windows(6,6) plot(fm1) This code is taken from the help page for 'nlme'. If I cut an paste this code into the console, everythin...

...ng the CO2 data in nlme (based off of the Ch08.R script). This works (when 'conc' is the same for each 'Plant': (fm1CO2.lis <- nlsList(SSasympOff, CO2)) (fm1CO2.nlme <- nlme(fm1CO2.lis, control = list(tolerance = 1e-2))) (fm2CO2.nlme <- update(fm1CO2.nlme, random = Asym + lrc ~ 1)) CO2.nlme.var <- update(fm2CO2.nlme, fixed = list(Asym ~ Type * Treatment, lrc + c0 ~ 1), start = c(32.412, 0, 0, 0, -4.5603, 49.344), weights=varConstPower(fixed=list(const=0.1, power=1)), verbose=T) CO2.nlme.CAR<-update(CO2.nlme.var, corr=corCAR1()) CO2.nlme.gauss<-update(CO2....

...data >>> >>> First I made groupedData object. >>>> mar.g<-groupedData(rutilizace~doba|int, data=mar) >>> >>> When I perform nlme on complete dataset I get an error with augPred >>>> fit<-nlsList(rutilizace~SSasymp(doba, Asym, R0, lrc), data=mar.g) >>> Warning message: >>> c("1 error caught in nls(y ~ cbind(1 - exp(-exp(lrc) * x), exp(-exp(lrc) * x)), data >> = xy, : singular gradient", "1 error caught in start = list(lrc = lrc), algorithm = >> \"plinear\"): singular gra...

...dos Les consulto por un problema con xtable y nlme, tomando un ejemplo del manual de nlme para obtener los resultados en latex utilizando xtable, se puede utilizar el siguiente código, pero hay un problema y causa error. library(nlme) library(xtable) fm1 <- nlme(height ~ SSasymp(age, Asym, R0, lrc), data = Loblolly, fixed = Asym + R0 + lrc ~ 1, random = Asym ~ 1, start = c(Asym = 103, R0 = -8.5, lrc = -3.3)) summary(fm1) xtable(summary(fm1)) Por si prefieren no ejecutar el código, el mensaje de error es: Error en UseMethod("xtable")...

Dear list members, I am working with a multilevel growth curve, that in its simplest form goes like follows: Yit = Ai + Bi t + eit (the error term is assumed to follow an AR(1) autorregressive process) One major topic in my research is the convergence in the values of Y over time. Thus, I am interested in the relationship between the random effects for the intercept and the slope, and I

...LOAD_WITH_ALTERED_SEARCH_PATH); SC_PROXY_GET_OBJECT lFunc; lFunc = (SC_PROXY_GET_OBJECT) GetProcAddress (m_ProxyModule, SC_PROXY_GET_OBJECT_FUN); if (lFunc == 0) { return -1; } // get proxy object ULONG lRc = lFunc (&m_ProxyObject,SC_PROXY_INTERFACE_VERSION); if ((lRc != SC_PROXY_OK) || (m_ProxyObject == 0)) { FreeLibrary (m_ProxyModule); m_ProxyModule = 0; return -2; } char* lParams = 0; lParams = strdup (""); Ou...

...by song_title.I have many song titles to create many files.but unfortunately,some of song titles contain special characters,such as [ ,which leads the following error: ##### Errno::EINVAL in Lyric spiderController#scrap_one_category Invalid argument - e:/rails/lyric/public/song/e/Energy/ [ar:Energy.lrc ##### I use the following codes to create and write to files: ##### File.open(singer_dir+"/"+UTF8_TO_GBK.iconv(song_title)+".lrc",''w'')do |f| f.write(lyric_initial_data) end ##### It is impossible to drop those special characters individually,and they ar...

...stderr()); flush(stdout()) > > ### Name: BOD > ### Title: Biochemical Oxygen Demand > ### Aliases: BOD > ### Keywords: datasets > > ### ** Examples > > data(BOD) > # simplest form of fitting a first-order model to these data > fm1 <- nls(demand ~ A*(1-exp(-exp(lrc)*Time)), data = BOD, + start = c(A = 20, lrc = log(.35))) > coef(fm1) A lrc 19.1425768 -0.6328215 > print(fm1) Nonlinear regression model model: demand ~ A * (1 - exp(-exp(lrc) * Time)) data: BOD A lrc 19.1425768 -0.6328215 residual sum-of-squa...

...t;incorrect number of names") for(i in 1:length(names.arg)) axis(1, at=1:length(names.arg), labels=names.arg, lty=0) } } else { ##---- height is vector --------- space <- space * mean(width) width <- rep(width, length = length(height)) delta <- width / 2 LRC <- cumsum(space + width) MID <- LRC - delta LLC <- MID - delta if (missing(xlim)) xlim <- c(0, max(LRC)) if (missing(ylim)) ylim <- range(-0.01, height) plot.new() if (horiz) { plot.window(ylim, xlim, log = "") rect(0, LLC, height, LRC, c...

...am trying to run some R example to get learn of them, but, I have a problem when running the example below: http://stat.ethz.ch/R-manual/R-patched/library/datasets/html/zCO2.html CO2.Qn1 <- CO2[CO2$Plant == "Qn1", ] SSasympOff(CO2.Qn1$conc, 32, -4, 43) # response only Asym <- 32; lrc <- -4; c0 <- 43 SSasympOff(CO2.Qn1$conc, Asym, lrc, c0) # response and gradient getInitial(uptake ~ SSasympOff(conc, Asym, lrc, c0), data = CO2.Qn1) ## Initial values are in fact the converged values fm1 <- nls(uptake ~ SSasympOff(conc, Asym, lrc, c0), data = CO2.Qn1) summary(fm1) I am fac...

Hello, How do I specify the formula and random effects without a startup object ? I thought it would be a mixture of nls and lme. after trying very hard, I ask for help on using nlme. Can someone hint me to some examples? I constructed a try using the example from nls: #variables are density, conc and Run #all works fine with nls DNase1 <- subset(DNase, Run == 1 ) fm2DNase1 <- nls(

...\" but class \"%s\" was supplied", : missing value where TRUE/FALSE needed What causes the trouble is the call to .checkMFClasses(cl, newdata) in predict.nls. Incidently, on the predict.nls page the example works: > fm <- nls(demand ~ SSasympOrig(Time, A, lrc), data = BOD) > predict(fm) [1] 7.887449 12.524977 15.251673 16.854870 17.797490 18.677580 > predict(fm,newdata=BOD) [1] 7.887449 12.524977 15.251673 16.854870 17.797490 18.677580 attr(,"gradient") A lrc [1,] 0.4120369 5.977499 [2,] 0....

Hi, I've heard somewhere that it is possible to store inside .ogg files text streams and thus it should be possible to store lyrics for the sond directly in the file. Is it true? Could anybody point me towards some code how to do it (Python preferable, but not required)? Is there any documentation for text streams in .ogg files? Thanks for any reply, Mat?j -- GPG Finger: 89EF 4BC6 288A