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hurdlr
View on CRAN: Click
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Download and install hurdlr package within the R console
Install from CRAN:
install.packages("hurdlr")
Install from Github:
library("remotes")
install_github("cran/hurdlr")
Install by package version:
library("remotes")
install_version("hurdlr", "0.1")
Attach the package and use:
library("hurdlr")
Maintained by
Earvin Balderama
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-07-02
Latest Update: 2017-07-02
Description:
When considering count data, it is often the case that many more zero counts than would be expected of some given distribution are observed. It is well established that data such as this can be reliably modelled using zero-inflated or hurdle distributions, both of which may be applied using the functions in this package. Bayesian analysis methods are used to best model problematic count data that cannot be fit to any typical distribution. The package functions are flexible and versatile, and can be applied to varying count distributions, parameter estimation with or without explanatory variable information, and are able to allow for multiple hurdles as it is also not uncommon that count data have an abundance of large-number observations which would be considered outliers of the typical distribution. In lieu of throwing out data or misspecifying the typical distribution, these extreme observations can be applied to a second, extreme distribution. With the given functions of this package, such a two-hurdle model may be easily specified in order to best manage data that is both zero-inflated and over-dispersed.
How to cite:
Earvin Balderama (2017). hurdlr: Zero-Inflated and Hurdle Modelling Using Bayesian Inference. R package version 0.1, https://cran.r-project.org/web/packages/hurdlr. Accessed 22 Dec. 2024.
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Complete documentation for hurdlr
Functions, R codes and Examples using
the hurdlr R package
Some associated functions: GenPareto . PE . PT . PZ . dist_ll . hurdle . hurdle_control . loglik_zinb . loglik_zip . mlnorm . update_beta . update_pars . update_probs . zero_nb . zero_poisson .
Some associated R codes: GenPareto.R . PE.R . PT.R . PZ.R . dist_ll.R . hurdle.R . hurdle_control.R . loglik_zinb.R . loglik_zip.R . mlnorm.R . update_beta.R . update_pars.R . update_probs.R . zero_nb.R . zero_poisson.R . Full hurdlr package functions and examples
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