In Twitter I recently observed people tweeting two photos,where under one the caption is “How it started” and the other “How it ended”. I figured why not change this humorous trend to journal articles as well.
We start with an initial submission but after rejections and comments the article might get severely scrutinized. Not always but sometimes this leads to somewhat of a stunning transformation of the research idea. Hence, below I have provided how my initial article for the “fitODBOD” R package has evolved.
Presidential Election Data of Sri Lanka has been in PDF files until this project was finished. While a Presidential Election is close by it would be useful to have all the data regarding Presidential Elections from the beginning(1982). Over the seven …
The R package fitODBOD can be used to identify the best-fitting model for Over-dispersed Binomial Outcome Data(BOD).The Triangular Binomial(TriBin),Beta-Binomial(BetaBin), Kumaraswamy Binomial (KumBin), Gaussian Hypergeometric Generalized …
Binomial Outcome Data has vast amount use in the field of biology, medicine and epidemiology. Modelling such data relative to Binomial Mixture Distributions were discussed because Binomial distribution fails to model the data. The reason is actual …
GitHub version is there for version 1.2.0 with is maintained by me if issues are raised regarding the package. While building under CRAN restrictions some examples and vignettes were not included to submission but there are in R-fitODBOD repository. …
Using [pkgdown](https://pkgdown.r-lib.org/) a genuine website for fitODBOD was generated. There is no extra work to be done here, because pkgdown uses our existing man files and vignettes to create this website. It is quite easy and convenient for a …
Meta analysis was conducted by me for the provided data using the packages meta and metafor from R statistical programming software. In the full article the package versions are clearly mentioned. Data was used to generate forest plots, funnel plots …