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Description

Neo-Normal Distribution.

Provides functions for calculating the density, cumulative distribution, quantile, and random number of neo-normal distribution. It also interfaces with the 'brms' package, allowing the use of the neo-normal distribution as a custom family. This integration enables the application of various 'brms' formulas for neo-normal regression. The package implements the following distributions: Modified to be Stable as Normal from Burr (MSNBurr), Modified to be Stable as Normal from Burr-IIa (MSNBurr-IIa), Generalized of MSNBurr (GMSNBurr), and Jones-Faddy Skew-t. References: Choir, A. S. (2020).Unpublished Dissertation. Iriawan, N. (2000).Unpublished Dissertation. Jones, M. C. and Faddy,M. J. (2003).<doi:10.1111/1467-9868.00378>. Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) <doi:10.1201/9780429298547>.

neodistr package

Neodistr package aims to provide density, distribution function, quantile function and random generation for neo-normal distributions. This package also provides a stan code for the distribution, so that we can estimate the parameter distribution using stan. In this package there is a function that can generate a custom_family for brms so that we can use it to modeling that uses brms with dependent variables having a neo-normal distribution

library(devtools)
install_github("madsyair/neodistr")

References

Choir, A. S. (2020).The New Neo-Normal Distributions and their Properties. Disertation. Institut Teknologi Sepuluh Nopember.

   

Iriawan, N. (2000).Computationally Intensive Approaches to Inference in Neo-Normal Linear Models. Curtin University of Technology.

   

Jones, M.C. and Faddy, M. J. (2003) A skew extension of the t distribution, with applications. Journal of the Royal Statistical Society, Series B, 65, pp 159-174.

   

Rigby, R.A. and Stasinopoulos, M.D. and Heller, G.Z. and De Bastiani, F. (2019) Distributions for Modeling Location, Scale, and Shape: Using GAMLSS in R.CRC Press.

Metadata

Version

0.1.1

License

Unknown

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