Calculates a cumulative summation nonparametric extended 
    median test based on the work of Brown & Schaffer (2020) <DOI:10.1080/03610926.2020.1738492>. 
    It then generates a control chart to assess processes and determine if any streams are out of control.

The aim of neo2R is to provide simple and low level connectors
   for querying neo4j graph databases (<https://neo4j.com/>).
   The objects returned by the query functions are either lists or data.frames
   with very few post-processing.
   It allows fast processing of queries returning many records.
   And it let the user handle post-processing according to the data model
   and his needs.

Sends queries to a specified 'Neo4J' graph database, capturing results in a dataframe where appropriate.  
    Other useful functions for the importing and management of data on the 'Neo4J' server and basic local server admin.

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.

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Unpublished Dissertation.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Unpublished Dissertation.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>.