Functions to have nice 'rmarkdown' outputs of the 
  seasonal and trading day adjustment models made with 'RJDemetra'.

Add-in to the 'RJDemetra' package on seasonal adjustments.
    It allows to produce dashboards to summarise models and quickly check the quality of the seasonal adjustment.

Set of tools to manipulate the 'JDemetra+' workspaces.  Based
    on the 'RJDemetra' package (which interfaces with version 2 of the
    'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal
    adjustment software officially recommended to the members of the
    European Statistical System (ESS) and the European System of Central
    Banks).  This package provides access to additional workspace
    manipulation functions such as metadata manipulation, raw paths and
    wrangling of several workspaces simultaneously.  These additional
    functionalities are useful as part of a CVS data production chain.

A series of functions in some way considered useful to the author.  These 
    include methods for subsetting tables and generating indices for arrays, 
    conditioning and intervening in probability distributions, generating 
    combinations, fast transformations, and more...

Implementation of the Johnson Quantile-Parameterised Distribution in R. 
  The Johnson Quantile-Parameterised Distribution (J-QPD) is a flexible distribution
  system that is parameterised by a symmetric percentile triplet of quantile values
  (typically the 10th-50th-90th) along with known support bounds for the distribution.
  The J-QPD system was developed by Hadlock and Bickel (2017) <doi:10.1287/deca.2016.0343>.
  This package implements the density, quantile, CDF and random number generator functions.

Provides functions to retrieve data and metadata from providers 
			 that disseminate data by means of SDMX web services. 
			 SDMX (Statistical Data and Metadata eXchange) is a standard that 
			 has been developed with the aim of simplifying the exchange of 
			 statistical information. 
			 More about the SDMX standard and the SDMX Web Services 
			 can be found at: <https://sdmx.org>.