y<-c(2.8,3.0,3.1,3.2,3.4,3.4,3.5,3.1,3.8,4.0,4.1,4.3,4.4,4.9)
x<-c(0,3,6,8,10,13,16,20,24,27,30,34,37,41)
rr  <- rrega(x,y,method=function(u) wt.huber(u,c=1.5),acc = 10.0*
	.Machine$single.eps^0.5)
sig <- 1.483*median(abs(rr$residuals))
rra <- rrega(rep(0,length(y)),
        y, method=function(u) wt.huber(u,c=1.5),fix.scale=sig,acc = 10.0*
	.Machine$single.eps^0.5)
FMapp (rr$residuals,rra$residuals,1,0)


xy<-matrix(c(37 ,   4,   22,
 40 ,   6,   24,
 48  ,  6  , 18,
 44 ,   9 ,  20,
 50 ,  11 ,  15,
 51  , 12 ,   9), byrow=T,nrow=6)
x<-xy[,2:3]
y<-xy[,1]

rr  <- rrega(x,y,method=function(u) wt.huber(u,c=1.5))
sig <- 1.483*median(abs(rr$residuals))
rra <- rrega(x[,1],y, method=function(u) wt.huber(u,c=1.5),fix.scale=sig)
FMapp (rr$residuals,rra$residuals,2,1)

rr  <- rrega(x[,1],y,method=function(u) wt.huber(u,c=1.5))
sig <- 1.483*median(abs(rr$residuals))
rra <- rrega(rep(0,6),y, method=function(u) wt.huber(u,c=1.5),fix.scale=sig)
FMapp (rr$residuals,rra$residuals,1,0)

n<-10
m<-100
fm<-rep(0,m)
b1<-0
x<-c(1:n)
for (i in 1:m){
y<- b1*x+rt(n,5)
rr  <- rrega(x,y,method=function(u) wt.huber(u,c=1.5))
sig <- 1.483*median(abs(rr$residuals))
rra <- rrega(rep(0,n),y, method=function(u) wt.huber(u,c=1.5),fix.scale=sig)
fff<-FMapp (rr$residuals,rra$residuals,1,0)
fm[i]<-fff$FM
}

qfs<-qf((1:m)/(m+1),1,n-2)
plot(qfs,sort(fm))
lines(c(0,min(max(qfs),max(fm))),c(0,min(max(qfs),max(fm))))

qff<-qf(0.95,1,n-2)
sort(fm)[60:100]
fmadj<-fm/l1fit(qfs,sort(fm))$coef[2]