similar to: qq.loglogistic

I am trying to use R to do loglogistic hazard estimation. My plan is to generate a loglogistic hazard sample data and then use survreg to estimate it. If everything is correct, survreg should return the parameters I have used to generate the sample data. I have written the following code to do a time invariant hazard estimation. The output of summary(modloglog) shows the factor loading of

Hi Dear, Can someone please inform me on genreating random variables of Loglogistic, and PERT beta distributions? Thanks for your time and help, in advance. Regards, Murthy.

Hi, I'm estimating a loglogistic aft (accelerated failure time) model, just a simple plain vanilla one (without time dependent covariates), I'm comparing the results that I obtain between aftreg (eha package) and survreg(surv package). If I don't use any covariate the results are identical , if I add covariates all the coefficients are the same until a precision of 10^4 or 10^-5 except

Dear all, What is the cumulative distribution (with parameterization) used within survreg with respect to the log-logistic distribution? That is, how are the parameters linked to the survivor function? Best regards, Mario [[alternative HTML version deleted]]

Hola a tod@s, Hace poco en la lista se discutieron algunas aproximaciones para determinar la distribución de probabilidad que potencialmente podrían haber generado los datos (ver [1]) y una de ellas fué el AIC. Haciendo uso del programa enviado por Pablo Verde (ver [1]), estos son los resultados para mis datos: weibull , AIC = 69839.44 exponential , AIC = 79488.77 gaussian , AIC = 69413.03

I a trying to use survreg to fit a Weibull distribution. From the last few messages I understand how to interpret the parameters. However, how do I get the covariance of lambda and alpha? Is there a predict command for that? Thanks -- View this message in context: http://n4.nabble.com/Survreg-function-for-loglogistic-hazard-estimation-tp893503p1604918.html Sent from the R help mailing list

Hi list! I'm getting an error message when trying to fit an accelerated failure time parametric model using the aftreg() function from package eha: > Error in optim(beta, Fmin, method = "BFGS", control = list(trace = > as.integer(printlevel)), : > non-finite finite-difference value [2] This only happens when adding four specific covariates at the same time in the

I have constructed the function mml2 (below) based on the likelihood function described in the minimal latex I have pasted below for anyone who wants to look at it. This function finds parameter estimates for a basic Rasch (IRT) model. Using the function without the gradient, using either nlminb or optim returns the correct parameter estimates and, in the case of optim, the correct standard

Hello, I am having two data set original and predicted. I want to dind QQ-plot fot it. I tried in following manner : >qq(original~predicted) and error was : Error in qq.formula(o ~ p) : y must have exactly 2 levels There is an option "qtype" which dosent make any difference. What is the correct way for plotting QQ-plot or am I missing something. -- Amar Kumar Nandan

I have 20 variables: 5,9,6,1,5,9,7,4,5,6,3,2,4,8,9,6,1,8,4,8 How do I calculate the corresponding quantiles from a normal distribution with the same mean and variance as the sample? Also, how do I draw a QQ plot of the data? Thanks for any help! -- View this message in context: http://www.nabble.com/Quantiles-and-QQ-plots-tf4925742.html#a14097909 Sent from the R help mailing list archive at

Hi, i am working on a data set with EDA. That includes QQ-Plots of residuals vs expected normal distribution. What puzzles me is that the range of ordinate and abscissae is so different: while the theoretical quantiles range from [-2, 2] the sample quantiles on the ordinate do extent from [-20, 50]. Quite obviously some kind of transformation is done. Although i intensively RTFM i could not

As I mentioned in the subject, I have installed the latest version of QQ International (beta 3), under wine in ubuntu lucid. It installs without much trouble, however when I run the application, nothing happens. How do I begin troubleshooting this application to see if I can make it work? Or if anyone happens to know of an x64 linux qq client that actually works that would be great too :D

I got QQ International (version 1.0) to work via WINE under Mepis 8.5. Using winetricks, I installed all of the missing DLL's, and QQ now starts up and runs fine. ... except for the fact that it always shows me as being "Away". Even if I manually set my status to "Online", it changes me back to "Away" after a second or two. This only happens under WINE. I log in

Hi everyone, I'm a newbie to wine, and am working on QQ or any other messengers in wine. My environment is : ubuntu 10.04, installed wine 1.1.42, QQ2009. And during my debugging, I also check some source code from latest wine 1.2-rc4. Although QQ's level is "garbage", but fortunately it works almost fine under wine, including login, text chat, ..... But the video call can only

Dear all, I am trying to find a suitable R-function for parametric proportional hazard regressions. The package survival contains the coxph() function which performs a Cox regression which leaves the base hazard unspecified, i.e. it is a semi-parametric method. The package Design contains the function pphsm() which is good for parametric proportional hazard regressions when the underlying base

Hi all, I am trying to test wheater the distribution of my samples is normal with QQ plot. I have a values of water content in clays in around few hundred samples. Is the code : qqnorm(w) #w being water content qqline(w) sufficient? How do I know when I get the plots which distribution is normal and which is not? Thanks, m [[alternative HTML version

Hi, I am trying to figure out how to get the correlation coefficient for a QQ plot (residual plot). So to be more precise, I am creating the plot like this: qq.plot(rstudent(regrname), main = rformula, col=1) But want to also access (or compute) the correlation coefficient for that plot. Thanks, Tom [[alternative HTML version deleted]]

Full_Name: Jarno Tuimala Version: 1.5.0 OS: Windows Nt Submission from: (NULL) (193.166.1.21) Running the following analysis gives as a result kukot vs. kisut. aikaero <- -27.5+5*(0:10) frekvenssi.m <- c(0,1,15,37,53,45,23,18,4,1,1) frekvenssi.n <- c(2,8,12,19,33,47,42,15,2,1,0) win.graph() aikaero <- rep(c(aikaero,aikaero), c(frekvenssi.m,frekvenssi.n)) a.ero <-

I'm new to R (and to S) and am wondering about code from pages 72 and 83 of MASS (Venables+Ripley, 3rd edition), to draw an envelope on a QQ plot. Copying from the book, I've got: #... code whose gist is "a.fit <- nls(..." num.points <- length(resid(a.fit)) qqnorm(residuals(a.fit)) # illustrate data-model residuals qqline(residuals(a.fit)) samp <-

I am attempting to use the R Commander Graphs Quantile-Comparison functionality on a dataset, to compare with a triangular distribution. I have the package triangle. My question is on the syntax of how to specify the parameters of the theoretical distribution in the Parameters field of the dialog box. For example, the theoretical distribution has min of 3000, max of 5000, mode of 4000. When