[R] Defining a pmf which has sum( from zero to infinity)

Hi everyone!! I have new probability mass function which has the following form( kindly see the image please) http://r.789695.n4.nabble.com/file/n4635047/abc.jpg Here alpha and beta are two parameters and I need to estimate those parameters using Maximum Likelihood Estimation Method( mle2 avai

[R] Maximum Likelihood Estimation Poisson distribution mle {stats4}

Hi everyone! I am using the mle {stats4} to estimate the parameters of distributions by MLE method. I have a problem with the examples they provided with the mle{stats4} html files. Please check the example and my question below! *Here is the mle html help file * http://stat.ethz.ch/R-manual/R-dev

Re: [R] Maximum Likelihood Estimation Poisson distribution mle {stats4}

Thank you S Ellison-2 for your reply. I will understand it with Prof.Peter Dalgaard's answer.. -- View this message in context: http://r.789695.n4.nabble.com/Maximum-Likelihood-Estimation-Poisson-distribution-mle-stats4-tp4635464p4635484.html Sent from the R help mailing list archive at Nabble.c

Re: [R] Maximum Likelihood Estimation Poisson distribution mle {stats4}

Thank you very much Professor .Peter Dalgaard for your kind explanations.. This made my work easy.. I am struggling with this for more than 2 days and now I got the correct reply. Thank again. -- View this message in context: http://r.789695.n4.nabble.com/Maximum-Likelihood-Estimation-Poisson-d

[R] Which is Best function to find Maximum Likelihood Estimates in R?

I read there are several R functions to get the Maximum Likelihood Estimates of a probability distribution with the available data in R. For Example... http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html mle {stats4} http://stat.ethz.ch/R-manual/R-devel/library/stats/html/optim.html

[R] Declaring a density function with for loop

I have an extended binomial distribution which has the following form: http://r.789695.n4.nabble.com/file/n4635699/kb.png Here alpha and beta are two parameters and x=0,1,2,3,...n (alike the binomial distribution) I am writing a function to find out the densities (probabilities) of this distri

Re: [R] Declaring a density function with for loop

Thank you very much for you kind explanation Berend Hasselman!! Is it possible to declare this probability density function without looping? -- View this message in context: http://r.789695.n4.nabble.com/Declaring-a-density-function-with-for-loop-tp4635699p4635720.html Sent from the R help maili

Re: [R] Declaring a density function with for loop

Thank you very much Professor. David L Carlson .. This method saves my time!! -- View this message in context: http://r.789695.n4.nabble.com/Declaring-a-density-function-with-for-loop-tp4635699p4635795.html Sent from the R help mailing list archive at Nabble.com. ___

[R] declaring negative log likelihood of a distribution

Hi everyone! I already posted http://r.789695.n4.nabble.com/Declaring-a-density-function-with-for-loop-td4635699.html a question on finding density values of a new Binomial like distribution which has the following pmf: http://r.789695.n4.nabble.com/file/n4636134/kb.png Thank fully http://r.789

Re: [R] MODE , VARIANCE , NTH PERCENTAILE

Din't you try sapply function? I tried it for you. Just convert your matrix into a data frame using as.data.frame and then *> rantony* ABC PQR XYZ MNO [1,] 3 6 7 15 [2,] 2 12 24 15 [3,] 20 5 1 2 [4,] 25 50 15 35 *> rantony=as.data.frame(rantony)* *> sapply(rantony,va

[R] Maximum Likelihood estimation of KB distribution

Hi, The following distribution is known as Kumaraswamy binomial Distribution. http://r.789695.n4.nabble.com/file/n4636782/kb.png For a given data I need to estimate the paramters (alpha and beta) of this distribution(Known as Kumaraswamy binomial Distribution, A Binomial Like Distribution). For t

[R] Help on VGAM package(missing value where TRUE/FALSE needed )

I am using VGAM R package for my research works. In my study, I am trying to simulate 1000 datasets from Beta binomial distribution for a given set of (n,prob,size,rho) and then I need to estimate the parameters prob and rho of the simulated 1000 datasets and need to store the fitted coefficients