This file documents software changes since the previous edition.



# npregfast 1.0.1 (2015-11-16)

  * the srand function of the fortran code has been deleted. Now it call the R one.


# npregfast 1.2.0 (2016-02-10)

   * the random numbers generation (for the bootstrap) has been changed reducing the computational time.
  * the plots are now obtained by means of the ggplot2.
  
# npregfast 1.2.1 (2016-02-16)

   * corrected bug at globaltest function (random numbers problem)
   
   
# npregfast 1.3.0 (2016-04-29)

   * the argument smooth has been incorporated to the functions. Users can select now the type of smoother: kernel (by default) or splines.
   
   
   # npregfast 1.4.0 (2016-11-18)

   * the plotting functions have been changed. Users can choose between the plot.frfast function, used for base graphics, and the autoplot.frfast function, which is appropriate for ggplot2-type plot and returns objects of the ggplot class. 
   * we have merged the plottdiff function of the previous version of the package with plot.frfast and with  autoplot.frfast by means of the new argument diffwith. This new argument lets users visualize the differences between two factor’s levels.
 
 
 
  # npregfast 1.5.0 (2017-10-30)

  * new implementation in R of the allotest. Now it is possible
  to choose between two statistic test: "res" (based on residuals on the 
  null model) or "lrt" (based on the likelihood ratio test using rss0 and rss1).
  * the localtest function has a new argument: ci.level.
  * fixed some bugs in the formula argument of frfast, globaltest, localtest and allotest functions.
  
  
  # npregfast 1.5.1 (2017-11-30)
  

  * the DOI in the CITATION is for a new JSS publication that will be registered after publication on CRAN.
 
 
   # npregfast 1.5.2 (2022-09-02)
  

  * new version that solves math rendering problems.
  
  
     # npregfast 1.6.0 (2025-10-10)
  

  * added a standard bias-correction in the allometric models for the 
  back-transformed slope to prevent systematic errors in the mean regression results, 
  following Hayes et al.(1995) Efficiency and bias of estimators and sampling designs 
  for determining length-weight relationships of fish. Can J. Fish. Aquat. Sci. 
  52: 84-92
  
  
  