Code for  Decision Theory for Statistical Problems
                (N.T. Longford)  SpringerBrief 2012


CHAPTER 6

Chap6.an1  -- Optimal thresholds in classifications will all three kernel losses
Function  Ch6cla; results matrix Ch6claR 

Chap6.an2  --  Application of the function  Ch6cla en masse
Results list  Ch6claS  (setting vectors,  si2s and mus;  rho=2.0)

Chap6.an3  --   Application of the function  Ch6cla en masse
Near-replica of Chap6.an2  (different value of  rho, 0.5)
Results list  Ch6claT  (setting vectors,  si2s and mus)

Chap6.an4  --  Graphics for the results from  Chap6.an2 and Chap6.an3
##  Figure 6.1, page 79
Function  Ch6claG; results list Ch6claGr

Chap6.an6  --  Example of a mixture of normals for the exceptions
##  Figure 6.2, page 84;  DATASET  Chap6xc.dat
Function  Ch6Exc; results list Ch6ExcR

Chap6.an7  --  Newton-Raphson algorithm for setting the thresholds $c_L$ and $c_H$
Ordinary and exceptional units
SUPERSEDED  BY  .an8  and  .an9
Function  Ch6excT;  results matrix/vector Ch6excT  --  deleted

Chap6.an8  --  Newton algorithm for setting the thresholds $c_L$ and $c_H$
Ordinary and exceptional units
Function  Ch6excNT; results list  Ch6excNTr

Chap6.an9  --  Newton-Raphson algorithm for setting the thresholds $c_L$ and $c_H$
Ordinary and exceptional units
Function  Ch6excNR; results list Ch6excNRr 
Note:  the highest value for which there is convergence:  R=349.117
(cL and cH  both close to  0.200)

Chap6A.an1 --  Classification with a range of values of  R
Results matrix  Ch6excNRs  (settings vector Rs)

Chap6.an2  --  Graphics for Ch6excNRr, the results  from  Chap6A.an1
##  Figure 6.3, page 86

