library("metrics")
randomize(66666)
n = 200
ss1 = #(1,0.9)~#(0.9,1)
g = #(1)
b = #(-9, 1)
u = gennorm(n, #(0,0), ss1)
ss2 = #(1,0.4)~#(0.4,1)
xz = gennorm(n, #(0,0), ss2)
z = xz[,2]
q = (z*g+u[,1].>=0)
hd = 0.1*(max(z) - min(z))
d = dwade(z,q,hd)*(2*sqrt(3)*pi)
id = z*d
h = (quantile(id, 0.7))|(0.2*(max(id) - min(id)))
x = matrix(n)~xz[,1]
y = x*b+u[,2]
zz = paf(y~x~id, q)
y = zz[,1]
x = zz[,3:(cols(zz)-1)]
id = zz[,cols(zz)]
{a,b} = select(x,y,id,h)
d~a~b ; first-step estimate ~ intercept estimate ~ slope estimate