A Modern and Flexible 'Neo4J' Driver, allowing you to query 
    data on a 'Neo4J' server and handle the results in R. It's modern in 
    the sense it provides a driver 
    that can be easily integrated in a data analysis workflow, especially by 
    providing an API working smoothly with other data analysis and graph 
    packages. It's flexible in the  way it returns the results, by 
    trying to stay as close as 
    possible to the way 'Neo4J' returns data. That way, you have the control 
    over the way you will compute the results. At the same time, the result 
    is not too complex, so that the "heavy lifting" of data wrangling is not 
    left to the user.

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.  Modified to be Stable as Normal from Burr (MSNBurr), 
    Modified to be Stable as Normal from Burr-IIa (MSNBurr-IIa), Generalized of MSNBurr (GMSNBurr), 
    Jones-Faddy Skew-t, Fernandez-Osiewalski-Steel Skew Exponential Power,  
    and Jones Skew Exponential Power distributions are supported.
    References: Choir, A. S. (2020).Unpublished Dissertation, Iriawan, N. (2000).Unpublished Dissertation,
    Rigby, R. A., Stasinopoulos, M. D., Heller, G. Z., & Bastiani, F. D. (2019) <doi:10.1201/9780429298547>.

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Unpublished Dissertation.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Unpublished Dissertation.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>.