search for: loglogist

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....

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 c...

Hi, is there any similar function in R to S function qq.loglogistic, which produces a Q-Q plot? Thanks a lot Pete

...er 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 logistic , AIC = 68816.95 lognormal , AIC = 68001.32 loglogistic , AIC = 67987.08 De acuerdo con lo anterior, la distribución que _potencialmente los genera_ es la log-logistica. Haciendo una revisión de los datos y las aplicaciones de esta distribución, encuentro que sería apropiado utilizarla como modelo. En R es posible generar observaciones, densidades,...

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]]

...g 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 archive at Nabble.com.

...underlying base distribution is "weibull" or "exponential". But what if I need a parametric proportional hazard model with the other "usual" distributions like '"gaussian"', '"logistic"', '"lognormal"'and '"loglogistic"? Thanks a lot for your support! Valentin Dimitrov Statistics and Econometrics University of Saarland

...el free to ask for more testing. I'm using R 2.13.1 (x86_64-redhat-linux-gnu), eha 2.0-5 and survival 2.36-9. Thanks for your help! > m <-aftreg(Surv(start, end, event) ~ homo1 + sexego + dipref1 + + t.since.school.q, + data=ms, dist="loglogistic", id=ident) Error in optim(beta, Fmin, method = "BFGS", control = list(trace = as.integer(printlevel)), : non-finite finite-difference value [2] Calls: aftreg -> aftreg.fit -> aftp0 -> optim > traceback() 4: optim(beta, Fmin, method = "BFGS", control = li...

Dear all, I am looking for routines which allow multi-variate sampling from non-normal distributions (loglogistic) given correlations among the variables. Unfortunately, I could not find a suitable package for R. Does anybody know one? Many thanks and best regards, Stefan Albrecht [[alternative HTML version deleted]]

...thods are ready to be put to use on a wide variety of "triangles". To see a demonstration of the example in Clark's paper (ChainLadder's "GenIns" is the same dataset), run > library(ChainLadder) > demo(clarkDemo) This will run the "LDF Method" with the loglogistic growth function limited to 20 years of development, per Clark's example. It will also run the "CapeCod Method" with the weibull growth function. In both cases, per Clark's recommendation, the option is selected to fit the growth function to the average date of loss of each accid...

On Wed, Aug 1, 2012 at 3:08 PM, <fra.meucci@hotmail.it> wrote: > Dear Göran Broström, > I am trying to use AFTREG function for R to estimate a loglogistic > survival function, including time dependent covariates. > Actually, my Subset includes some partial events; the idea is to model > this kind of events using something similar to “weights” in the SURVREG > function. > In particular I would like to manage this kind of Dataset: &...

Hi I'm trying to predict the values for a survreg object called loglogistic_na. Here is the definition of loglogistic_na and following that the syntax used for the predict function. But upon execution I don't get any output. Not sure what I'm doing wrong: loglogistic_na <- survreg(Surv(time_na,event_na) ~ t_na, dist="loglogistic") summary(loglogisti...

...2.13.1 (x86_64-redhat-linux-gnu), eha 2.0-5 > and survival 2.36-9. > > > Thanks for your help! > > >> > m <-aftreg(Surv(start, end, event) ~ homo1 + sexego + dipref1 > + + t.since.school.q, > + data=ms, dist="loglogistic", id=ident) > Error in optim(beta, Fmin, method = "BFGS", control = list(trace = > as.integer(printlevel)), : > non-finite finite-difference value [2] > Calls: aftreg -> aftreg.fit -> aftp0 -> optim > >> > traceback() > 4: optim(beta, Fmin,...

...n <- length(x) if (is.character(distfun)) { distname <- tolower(distfun) densfun <- switch(distname, exp = dexp, exponential = dexp, gamma = dgamma, `log-normal` = dlnorm, lnorm = dlnorm, lognormal = dlnorm, weibull = dweibull, pareto = dpareto, loglogistic = dllogis, transbeta = dtrbeta, `transformed beta` = dtrbera, burr = dburr, paralogistic = dparalogis, genpareto = dgenpareto, generalizedpareto = dgenpareto, `generalized pareto` = dgenpareto, invburr = dinvburr, `inverse burr` = dinvburr, invpare...

Hola, ¿qué tal? Tengo una pregunta de esta

Dear All, I am doing a parametric survival analysis with: fit <- survreg(Surv(xyz$start, xyz$stop, xyz$event, type="interval") ~ 1, dist='loglogistic') At this point I do not want to look into covariates, hence the '~1' as model formulation. As event types I have exact, interval, and right censored lifetime data. Everything works fine. For reasons that are not important here now, I wanted to look for the effects of 'ran...

...ropped? Example I want to compare the likelihoods in Fit1 and Fit2. Is it straightforward, or should I e.g. add a syntax asking for the full likelihood? Fit1<-survreg(Surv(Time, Event) ~ x, data, dist=''weibull'') Fit2<-survreg(Surv(Time, Event) ~ x, data, dist=''loglogistic'') Ullrika [[alternative HTML version deleted]]

...-help, I am using R 2.14.1 on Windows 7 with the 'gfcure' package (cure rate model). I have included the treatment variable in the cure part of the model as shown below: Ø ref_treat <- gfcure(Surv(rem.Remtime,rem.Rcens)~1,~1+strata(drpa)+factor(treat(delcure)),data=delcure,dist="loglogistic") >From that I can obtain the coefficients, standard errors etc as per alternative models (with covariates only fitted to the survival part of the model say). > summary(ref_treat) However, only one standard error is output: Log-logistic mixture model The maximum loglikelihood is -...

...ot;X2"), row.names = c(NA, 20L), class = "data.frame") The quote(s) from the paper is as follows: "Maximum likelihood was applied to probit models (normal, lognormal, weibull, logistic, and log-logistic) and the data to determine the incidence relationships. The lognormal and loglogistic models best represent the data." and later: "Binary data are utilized for the maximum likelihood dose response calculations" I tried using a simple glm() with a probit linker, but that produced border-line nonsense results. This made sense when I thought about it more, as R was...