search for: weib

I am trying to extract the shape and scale parameters of a wind speed distribution for different sites. I can do this in a clunky way, but I was hoping to find a way using data.table or plyr. However, when I try I am met with the following: set.seed(144) weib.dist<-rweibull(10000,shape=3,scale=8) weib.test<-data.table(cbind(1:10,weib.dist)) names(weib.test)<-c('site','wind_speed') fitted<-weib.test[,fitdistr(wind_speed,'weibull'),by=site] Error in class(ans[[length(byval) + jj]]) = class(testj[[jj]]) : invalid to...

Dear R-users, I am trying to create a model using the NLS function, such that: Y = f(X) + q + e Where f is a nonlinear (Weibull: a*(1-exp(-b*X^c)) function of X and q is a covariate (continous variable) and e is an error term. I know that you can create multiple nonlinear regressions where x is polynomial for example, but is it possible to do this kind of thing when x is a function with unknown coefficients (a,b,c)? Ulti...

I was wondering if someone familiar with survival analysis can help me with the following. I would like to fit a Weibull curve, that may be dependent on a covariate, my dataframe "labdata" that has the fields "cov", "time", and "censor". Do I do the following? wieb<-survreg(Surv(labdata$time, labadata$censor)~labdata$cov, dist="weibull") This returns: &g...

...his distribution. I have been googling around for some help, and have found some threads to a similar question posted to the R-Help list in October last year. Because I am a bit of a survival analysis and R newbie, I didn't really understand the discussion thread. I've been working with a Weibull distribution, thus: >leafsurv.weibull<-survreg(Surv(minage, maxage, censorcode, type = >"interval")~1, dist = "weib") And I guess I'd like to be able to do something that's the equivalent of >leafsurv.gamma<-survreg(Surv(minage, maxage, censorcode, t...

...his distribution. I have been googling around for some help, and have found some threads to a similar question posted to the R-Help list in October last year. Because I am a bit of a survival analysis and R newbie, I didn't really understand the discussion thread. I've been working with a Weibull distribution, thus: >leafsurv.weibull<-survreg(Surv(minage, maxage, censorcode, type = "interval")~1, dist = "weib") And I guess I'd like to be able to do something that's the equivalent of >leafsurv.gamma<-survreg(Surv(minage, maxage, censorcode, type...