Nothing
sumry <-
function(Vec,type_bw,ker="bino",h=NULL,a=1,c=2){
###########################################################################################################
# INPUTS:
# "Vec" : Sample of data
# "h" : Bandwidth.
# "ker" : The kernel function: "dirDU" DiracDU,"bino" Binomial,"triang" discrete Triangular.
# "a" : The arm is used only for the Discrete Triangular kernel. The default value is 1.
# "c" : The number of categories in the Aitchison and Aitken kernel is used only for DiracaDU.The default value is 2.
# OUTPUT:Returns a list containing:
# "n" : The number of observations.
# "support_of_f_n" : The support of f_n.
# "C_n" : The normalizant constant.
# "ISE_0" : The integrated squared error when using the naive distribution instead of f_n.
# "f_0" : The couples (x,f_0(x)).
# "f_n" : The couples (x,f_n(x)).
# "h" : The bandwidth used to estimate the p.m.f.
###########################################################################################################
if(missing(h)){
if((ker=="dirDU")&(type_bw=="CV")){
h1=CVbw(Vec,NULL,ker,a,c)
h=h1$hcv
}
else if((ker=="triang")& (type_bw=="CV")){
h1=CVbw(Vec,NULL,ker,a)
h=h1$hcv
}
else if((ker=="bino")&(type_bw=="CV")){
h1=CVbw(Vec,NULL,ker)
h=h1$hcv
}
else if((ker=="bino")&(type_bw=="Bays")){
h=Baysbw(Vec)
}
bilan=kpmfe(Vec,h,ker,a,c)
message('The estimated p.m.f. f_n is the smoothing of the empirical p.m.f. f_0')
if ((type_bw=="CV")&(ker=="bino")){
message('using Binomial kernel and h_n by cross validation technique.')
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, hn_cv=h))
}
else if ((type_bw=="CV")&(ker=="triang")) {
message(paste('using Discrete Triangular kernel with a=', a ,'and h_n by cross validation technique. ', sep=" "))
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, hn_cv=h))
}
else if((ker=="bino")&(type_bw=="Bays")){
message('using Binomial kernel and h_n by local Bayesian procedure.')
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, hn_Bays=h))
}
else if ((type_bw=="CV")&(ker=="dirDU")) {
message(paste('using Dirac Discrete Uniform kernel with c=', c ,' and h_n by cross validation technique.'))
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, hn_cv=h))
}
}
else
{
bilan=kpmfe(Vec,h,ker,a,c)
message('The estimated p.m.f. f_n is the smoothing of the empirical p.m.f. f_0')
if (ker=="bino"){
message('with a Binomial kernel and a given bandwidth h=',h)
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, h=h))
}
else if (ker=="triang"){
message('with a Discrete Triangular kernel with a= ' , a , ' and a given bandwidth h=',h)
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, h=h))
}
else if (ker=="dirDU"){
message('with a Dirac Discrete Uniform kernel with c=', c ,' and a given bandwidth h=',h)
return(list(n=bilan$n,support_of_f_n=bilan$support,f_0=bilan$f_0,f_n=bilan$f_n,ISE_0=bilan$ISE_0,C_n=bilan$C_n, h=h))
}
}
}
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