MLE Estimation of Gamma Distribution Parameters for data with 'zeros'
Another situation for the presence of 0 is about dosage when concentration is below the detection limit. It is not necessary to discretize the data. We propose a method here: Salvat-Leal I, Cort?s-G?mez AA, Romero D, Girondot M (2022) New method for imputation of unquanti?able values using Bayesian statistics for a mixture of censored or truncated distributions: Application to trace elements measured in blood of olive ridley sea turtles from mexico. Animals 2022: 2919 doi 10.3390/ani12212919 with R code. If the data has "true" 0, the gamma distribution is not the best choice as 0 is impossible with gamma distribution. Marc Le 19/01/2023 ? 12:49, peter dalgaard a ?crit?:
Not necessarily homework, Bert. There's a generic issue with MLE and rounded data, in that gamma densities may be 0 at the boundary but small numbers are represented as 0, making the log-likelihood -Inf. The cleanest way out is to switch to a discretized distribution in the likelihood, so that instead of log(dgamma(0,...)) you use log(pgamma(.005,..) - pgamma(0,...)) == pgamma(.005,..., log=TRUE). (For data rounded to nearest .01, that is). Cruder techniques would be to just add, like, .0025 to all the zeros. -pd
On 10 Jan 2023, at 18:42 , Bert Gunter <bgunter.4567 at gmail.com> wrote: Is this homework? This list has a no-homework policy. -- Bert On Tue, Jan 10, 2023 at 8:13 AM Nyasha <kahuninyasha13296 at gmail.com> wrote:
Please how can one go about this one? I don't know how to go about it.
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______________________________________________ R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.