Download the new release 20.90

Release 20.90
  Two new auxiliary R-functions:   Hotelling and HotellingEllipse


 Allows to detect Tē ouliers using the PCA or the PLS components and display Tē Hotelling ellipses on the same (ti, tj) scatterplot.
to detect outlying observations on the component variables ii and jj (default to 1 and 2) at the Fisher-Snedecor level (FSthreshold defaults to 0.95).
                       Hotelling displays the corresponding Tē ellipse only if FStrhesold=0.95 thus giving the initial plot.
 HotellingEllipse: When FSthreshold is different from 0.95 one have to use Hotelling and then HotellingEllipse to see the ellipse and the coloured outliers.

Example ;   PCA on 'cornell' data  (see Tenenhaus's book on pages 86-87   or  the lecture notes, page 199)

Hotelling(cornellPCA$C, axislabel=list("Dim  1  (61.81%)","Dim  2  (23.97%)") )
                              HOTcornell85 = Hotelling(cornellPCA$C, FSthreshold=0.85)
                              HotellingEllipse(HOTcornell85, colpar="black")

                         HOTcornell75 = Hotelling(cornellPCA$C, FSthreshold=0.75)
                         [1] "Outliers with components 1 and 2 ,Tē=75% :"
                              [1] "6"

                          HotellingEllipse(HOTcornell75, colpar="red")


Release 20.80
1) Numerical outputs in the PLS iterations are differently displayed in the one response case. The adjusted Rē  is now computed.

   > PLSL(cornell[,1:7],cornell[,8,drop=F], cexpar=0.8,bgpar="white")
            - Linear PLS -
   Total Variance of X = 7
   Variance of y = 1 , y0 = y

   Dimension 1

    cov(t1,y0)= 1.916  r(t1,y0)= 0.961 stdev(t1)= 1.994  stdev(y0)= 1

                    y      % of VAR
   R2 part. 0.924    92.359
   adjusted R2 for y with dim. 1 and 7 predictors : R2_adjust= 0.791
.  .................
   % of VAR X accounted for by the current comp. = 57.361

2) PRESS plots can eventually show the threshold of acceptability for the dimension of the model.

    The rule for the dimension k, being (in the 1 response case):

                                  PRESS(k) > 1   ==>  model not better than  yhat(k) = Const = mean y 

 PRess plot  

Release 20.69
1) A new MVcut R-function to code continuous vaviables into categorical by choosing graphically the breaks points that default to quantiles.

     Heavy  :
     nunber of levels :  3

     Change or not that number ? (y/n)1:


2) The item "Remove/Add variables" no more available in the MAPLSS menu.