similar to: fitting distribution tails

Hello, I tried to fit a lognormal distribution by using optim. But sadly the output seems to be incorrect. Who can tell me where the "bug" is? test = rlnorm(100,5,3) logL = function(parm, x,...) -sum(log(dlnorm(x,parm,...))) start = list(meanlog=5, sdlog=3) optim(start,logL,x=test)$par Carsten. [[alternative HTML version deleted]]

Hello, maybe that my Question is a "beginner"-Question, but up to now, my research didn't bring any useful result. I'm trying to fit a distribution (e.g. lognormal) to a given set of data (ML-Estimation). I KNOW about my data that there is a truncation for all data below a well known threshold. Is there an R-solution for an ML-estimation for this kind of data-problem? As

Hi A.K Regarding my question on comparing normal/ obese/overweight with blood pressure change, I did finally as per the first suggestion of stacking the data and creating a normal category . This only gives me a obese not obese 14, but when I did with the wide format hoping to get a obese14,normal14,overweight 14 Vs hibp 21, i could not complete any of the models. This time I classified obese=1

Hello, I want to fit a tree parameter distribution to given data. I tried it with sample data using the "fitdistr" function. Here my workflow that didn't had any result: I started with the generalized gamma distr, which is: r*dgamma(x^r,shape,rate) The R-function is: ggamma = function (x,r,shape,rate) r*dgamma(x^r,shape,rate=rate) For the first step I assumed r = 1 and I

Hello, I've written a function that plots a few functions in a diagram. The xlim and or ylim is not always the same, and set automatically by R. A legend is part of this object. Now the problem is: where to put the legend? Me would help a function that returns the limits and scaling of the axis. Thanks for your help. Carsten [[alternative HTML version deleted]]

Hello, just another problem in R, maybe it's simple to solve for you. I didn't find a solution up to now, but I'm convinced that I'm not the only one who has/had a similar problem. Maybe there's a ready-made function in R? The prob: I've imported a CSV-file into R with 1000 dates of an observed event (there's only information of the date. When there happend no

Hi, I've made a function that executes a monte-carlo simulation. It always needs a lot of time until e.g. 1Mio simulation steps are done. So I would like to know, how many percent of the work is already done. In an Excel/VBA Solution I could easily implement a status bar or status window. How could an R-Solution look like? Carsten

Hello, I've the following setting: (1) Data from a source without truncation (x) (2) Data from an other source with left-truncation at threshold u (xu) I have to fit a model on these these two sources, thereby I assume that both are "drawn" from the same distribution (eg lognormal). In a MLE I would sum the densities and maximize. The R-Function could be:

Hello, today I've updated on the newest R-Version. But sadly a function I needed didnt want to work: The input is e.g. days(as.Date("21-07-2005","%d-%m-%y")) the error is: Fehler in Math.Date(dts): floor nicht definiert f??r Date Objekte (Error in Math.Date(dts): floor not defined for date objects) Same for year. Only months gives me the correct output. In Version

Hello, I see that the more I work with R and the more the code gets larger I would like to have some graphic support in my quellcode. Is there a browser that could be easily implemened in R? And how do I call it from R? It would be nice if the browser replaces the "fix()" function. Carsten

Hi, Sorry, but how did you bring it out? Thanks On Fri, Dec 28, 2012 at 8:48 AM, arun kirshna [via R] < ml-node+s789695n4654093h10@n4.nabble.com> wrote: > Hi, > bp.sub<- structure(list(CODEA = c(1L, 3L, 4L, 7L, 8L, 9L, 10L, 11L, 12L, > 13L, 14L, 16L, 17L), C45 = c(NA, 2L, 2L, 2L, 2L, 1L, NA, 1L, > 1L, 2L, 1L, 2L, 1L), ragek = c(3L, 3L, 3L, 4L, 4L, 3L, 3L, 3L, > 3L, 3L,

Hi all, I'm using the function "fitdistr" (library MASS) to fit a distribution to given data. What I have to do further, is getting the log-Likelihood-Value from this estimation. Is there any simple possibility to realize it? Regards, Carsten

Hello, I have to generate a couple of random datasets to validate an actuarial software. Each set has to contain at least two columns: (1) Date of the loss events occurrence; (2) Severity of loss I'm generating the dates on a monthly basis by, for example: ts(matrix(rpois(36,10)), start=c(2003, 1), frequency=12). >From that output I generate dates "by hand", what is REALLY time

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Hello, I want to find the parameters mu and sigma that minimize the following function. It's important, that mu and sigma are strictly positive. ----------------- optimiere = function(fmean,smean,d,x,mu,sigma) { merk = c() for (i in 1:length(d)) merk=c(merk,1/(d[i]^2)*(d[i]-1/(fmean*(1-plnorm(x[i],mu,sigma))))^2) return(sum(merk)) } ----------------- To do that I'm using the nlm

Hola a todos, -Estoy estudiando el efecto de dos genotipos (~tratamientos) en la aparición de síndrome metabólico (MetS) con datos longitudinales recogidos a tiempo 0,7,10,15,20 y 25 años. -He hecho un dataframe con las siguientes variables MetS: Síndrome Metabólico (Si=1,No=0) bmi: Indice de masa corporal (IMC) cuando se produce la conversión a MetS+ . Para los que permancen MetS-, esta variable

Hello, I want to solve some two dimensional equation system with R. Some systems are not solvable analytically. Here is an example: (I) 1/n*sum{from_i=1_to_n}(Xi) = ln lambda + digamma(c) (II) mean(X) = x / lambda I want to find lambda and c, which R-function could do that task? Carsten [[alternative HTML version deleted]]

Hi, my problem is the following: I have a large database of insurance-damage data and want to model the frequency of these events. So to fit a distribution on my frequency-data I want to count the number of events in each month via the date of occurrence. Therefor I use this command which works very well: count_table <- table(months(date_occ),years(date_occ)) But there is another

Hello, for a frequency modelling problem I want to combine expert knowledge with incoming real-life data (which is not available up to now). The frequency has to be modelled with a poisson distribution. The parameter lambda has to be normal distributed (for certain reasons we did not NOT choose gamma althoug it would make everything easier). I've started with the subsequent two functions to

Hi, two questions - I think simple to solve for you ... (1) I've written a function containing some loops. Each loop will generate a few outputs. Finally I have to combine them to get something like a "spreadsheet" that my colleagues can import in EXCEL. Up to now I'm doing it as follows: With each loop-step I assign new values for each "column" of my desired output