neojags - Neo-Normal Distributions Family for Markov Chain Monte Carlo (MCMC) Models in 'JAGS'

A 'JAGS' extension module provides neo-normal distributions family including MSNBurr, MSNBurr-IIa, GMSNBurr, Lunetta Exponential Power, Fernandez-Steel Skew t, Fernandez-Steel Skew Normal, Fernandez-Osiewalski-Steel Skew Exponential Power, Jones Skew Exponential Power. References: Choir, A. S. (2020). "The New Neo-Normal Distributions and Their Properties".Unpublished Dissertation. Denwood, M.J. (2016) <doi:10.18637/jss.v071.i09>. Fernandez, C., Osiewalski, J., & Steel, M. F. (1995) <doi:10.1080/01621459.1995.10476637>. Fernandez, C., & Steel, M. F. (1998) <doi:10.1080/01621459.1998.10474117>. Iriawan, N. (2000). "Computationally Intensive Approaches to Inference in NeoNormal Linear Models".Unpublished Dissertation. Mineo, A., & Ruggieri, M. (2005) <doi:10.18637/jss.v012.i04>. Rigby, R. A., & Stasinopoulos, D. M. (2005) <doi:10.1111/j.1467-9876.2005.00510.x>. Lunetta, G. (1963). "Di una Generalizzazione dello Schema della Curva Normale". Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) <doi:10.1201/9780429298547>.

Last updated 4 months ago

jagscpp

4.30 score 2 scripts 266 downloads

neodistr - 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Unpublished Dissertation.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Unpublished Dissertation.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>.

Last updated 7 months ago

probability-distribution

3.48 score 15 scripts 200 downloads