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#          Series 0.0-6                   #
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                CHANGES in VGAMextra 

                 VERSION 0.0-6 (October 2023)
  o  New dpqr-type functions for the truncated normal and lognormal
     distributions.
  o  New family functions: truncnormalff() and trunclognormalff().
     See manual for details. 


                  VERSION 0.0-5 (May 2021)

  o 'warning' from function gammaRMlink() fixed.

                  VERSION 0.0-4 (March 2021)

  o URL https://www.stat.nus.edu.sq/~staxyc/ (no longer available
    replaced with https://blog.nus.edu.sg/homepage/research/

                  VERSION 0.0-3 (March 2021)
NEW FEATURES 
  
  o New functions:
       * Two-parameter links: weibullQlink() and uninormalQlink()
         for quantile regression.
       * One-parameter links for the mean of several one--parameter 
         distributions.

  o New family functions: uninormalff() and weibullRff(). See manual
    for details.

  o Tested okay on R 4.0.3. This package requires R 3.5.0 or higher.


                   VERSION 0.0-2 (April/May 2020)

NEW FEATURES

 o   Several functions have been adapted to handle the renamed 
     link functions from VGAM-1.1.0, e.g., logit() to logitlink().
 
 o   Tested okay on R 4.0.0. Requires R 3.5.0 or higher. 


                    VERSION 0.0-1 (July 2018)

IMPORTANT FEATURES

  o   Tested okay on R 3.4.3 (This package requires R V-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)-ARMAX, and the order(u, d, v)-ARIMAX 
         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)-ARMA structure
         on the conditional mean equation, and 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, Yule-
         Simon and logarithmic.


  o    Other  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()

