        ****************   VGAMextra   *********************
          Additions and extensions of the VGAM package

VGAMextra supplies additional functions and methods to the package VGAM,
addressing three main topics:

  ** Time series modelling. A novel class 
  of VGLMs to model univariate time series, called vector generalized
  linear time series models (VGLTSMs). It is characterized by
  incorporating past information in the VGLM/VGAM loglikelihood.
 
  ** 1--parameter distribution mean modelling.
  Returning full circle by developing new link functions for the mean
  of 1--parameter distributions. VGAMs, VGLMs and GAMLSSs are restricted
  to location, scale and shape. However, the VGLM/VGAM framework has
  infrastructure to accommodate new links as a function of the parameters.
 
  ** Quantile modelling of 1--parameter distributions.
  Similarly, we have implemented link functions to model the quantiles
  of several 1--parameter distributions, to straightforwardly address
  quantile regression.


Note, VGAMextra is still under development.
The package is revised, altered, and/or upgraded on a regular basis.
It is central to regularly improve and develop the functionalities 
conferred. Hence, be aware that any feature, e.g., function names,
arguments, or methods, may be modified without prior notice.
Check the NEWS for the latest changes and additions across the
different versions.

For more on VGAM visit
       https://CRAN.R-project.org/package=VGAM

Last update: January 2021
All functions and methods at 'VGAMextra' are
Copyright (C) 2014 - 2021, Victor Miranda 
Auckland University of Technology
For bugs/fixes/comments, please email me at victor.miranda@aut.ac.nz




     CHANGES in VGAMextra VERSION 0.0-1

NEW FEATURES


                    VERSION 0.0-1

IMPORTANT FEATURES

  o   Tested okay on R 4.0.4 (This package requires R 3.4.0 or higher)
  
  o   VGAM/VGLM time series family functions for each sub-class
      of vector generalized linear time series models (VGLTSMs).
      *  Order(u, d, v) VGLM-ARIMA:
         Family functions ARXff(), MAXff(), ARMAXff(), ARIMAXff(),
         to estimate the order-u autoregressive (AR(u)),
         the order-v moving average (MA(v)),
         the order(u, v)-ARMA, and the order(u, d, v)-ARIMA structure
         with covariates.
         Here, 'd' is the order of differencing. Normal errors
         handled at present.
         
      *  Order(u, v, r, s) VGLM-ARMAX-GARCH:
         Family function ARMAX.GARCHff(),
         which allows an order(u, v)-ARMAX structure (with covariates)
         on the conditional mean equation, plus an order(r, s)-GARCH
         model on the conditional variance. Normal errors
         handled at present.
        
      *  Order(u, v) VGLM-INGARCH (for time series of counts):
         Family function VGLM.INGARCH(), to fit an INGARCH model
         with interventions including interaction between "events",
         Distributions handled: Poisson, negative binomial, logarithmic,
         and Yule-Simon.


  o    Additional VGAM/VGLM family functions (not included in VGAM)
      *  trinormal(), to estimate the 3-dimensional Normal distribution,
         aka Trinormal.
      *  invweibull2mr(), invgamma2mr(), to estimate the 
         2-parameter Inverse Weibull and 2-parameter Inverse 
         Gamma distributions.
      * inv.chisqff.R(), to estimate the inverse chi-square
        distribution.
      *  gen.betaIImr(), to estimate the 4-paramater Generalized
         Beta distribution of the Second Kind.
 
 
  o    All family functions, except by VGLM.INGARCHff(), handle multiple
       responses.
       
       
  o    New link functions for the mean-function of 1-parameter 
       distributions.
       * Continous: expMeanlink(), inv.chisqMeanlink(),
         maxwellMeanlink(), rayleighMeanlink(), toppleMeanlink().
       
       * Discrete: Borel.tannerMeanlink(), geometricffMeanlink(),
         logffMeanlink(), posPoiMeanlink(), yulesimonMeanlink(),
         zetaffMeanlink().
 
 
  o    New link functions for the quantile-function of 1-parameter 
       continous distributions: benini1Qlink(), rayleighQlink(),
       toppleQlink(), gamma1Qlink(), maxwellQlink(), expQlink(),
       normal1sdQlink().

  
  o   Other important functions: 

    * 'summaryS4VGAMextra'. S4 dispatching methods of
      'summary' for VGLM--time series family functions.
      Here, standard errors and extra information are 
      now incorporated to the default output displayed 
      by show-methods in VGAM.
    * AR1EIM.G2(), ARpEIM.G2(), MAqEIM.G2(), and ARMA.EIM.G2();
      to compute the exact expected information matrices of
      Gaussian time series conforming with the AR(1), AR(p),
      MA(q) and ARMA(p, q) processes, respectively.
    * pre2.wz(); to compute the approximate information
      matrix of any AR, MA or ARMA time series data.
    * dARp(), dMAq(), dARMA(); the density of the AR(p),
      MA(q) and ARMA(p, q) processes.
    * dpqr.invgamma(), the Inverse Gamma Distribution.
    * dpqr.invweibull(), the Inverse Weibull Distribution.
    * dpqr.genbetaII(), the Generalized Beta Distribution
      of the Second King (4-parameter).	


BUG FIXES and CHANGES

   o   Switched the default values of arguments 'scale' and 'rate'
       (now, 'scale = 1/rate' and 'rate = 1') for dpqr.invgamma()
       and dpqr.invweibull()





