Nothing
restricted <-
function (B, DD, yy, pp, lambda, smooth, nb, center, constmat,
types)
{
nterms = length(nb)
m = length(yy)
np = length(pp)
lala <- matrix(lambda, nrow = nterms, ncol = 2, dimnames = list(1:nterms,
c("mean", "residual")))
vector.a.ma.schall <- matrix(NA, nrow = sum(nb) + (1 * center),
ncol = np)
if (smooth == "schall") {
sch = schall(yy, B, 0.5, DD, nb, lala[, 1], constmat,
center, types)
lala[, 1] = sch[[2]]
mean.coefficients = sch[[1]]
diag.hat = sch[[3]]
}
else if (smooth == "gcv") {
acv.min = nlminb(start = lala[, 1], objective = acv,
yy = yy, B = B, quantile = 0.5, DD = DD, nb = nb,
constmat = constmat, lower = 0, upper = 10000)
aa <- asyregpen.lsfit(yy, B, 0.5, abs(acv.min$par), DD,
nb, constmat)
mean.coefficients <- aa$a
lala[, 1] <- abs(acv.min$par)
diag.hat = aa$diag.hat.ma
}
else if (smooth == "aic") {
acv.min = nlminb(start = lala[, 1], objective = aicfun,
yy = yy, B = B, quantile = 0.5, DD = DD, nb = nb,
constmat = constmat, lower = 0, upper = 10000)
aa <- asyregpen.lsfit(yy, B, 0.5, abs(acv.min$par), DD,
nb, constmat)
mean.coefficients <- aa$a
lala[, 1] <- abs(acv.min$par)
diag.hat = aa$diag.hat.ma
}
else if (smooth == "bic") {
acv.min = nlminb(start = lala[, 1], objective = bicfun,
yy = yy, B = B, quantile = 0.5, DD = DD, nb = nb,
constmat = constmat, lower = 0, upper = 10000)
aa <- asyregpen.lsfit(yy, B, 0.5, abs(acv.min$par), DD,
nb, constmat)
mean.coefficients <- aa$a
lala[, 1] <- abs(acv.min$par)
diag.hat = aa$diag.hat.ma
}
else if (smooth == "cvgrid") {
lala[, 1] = cvgrid(yy, B, 0.5, DD, nb, constmat, types)
aa <- asyregpen.lsfit(yy, B, 0.5, lala, DD, nb, constmat)
mean.coefficients <- aa$a
diag.hat = aa$diag.hat.ma
}
else if (smooth == "lcurve") {
lala[, 1] = lcurve(yy, B, 0.5, DD, nb, constmat, types)
aa <- asyregpen.lsfit(yy, B, 0.5, lala, DD, nb, constmat)
mean.coefficients <- aa$a
diag.hat = aa$diag.hat.ma
}
else {
aa <- asyregpen.lsfit(yy, B, 0.5, lala[, 1], DD, nb,
constmat)
mean.coefficients <- aa$a
diag.hat = aa$diag.hat.ma
}
residuals = yy - B %*% mean.coefficients
constmat[, ] = 0
gg = asyregpen.lsfit(abs(residuals), B, 0.5, lala[, 1], DD,
nb, constmat)
cc = NULL
for (q in 1:np) {
ca = asyregpen.lsfit(residuals, gg$fitted, pp[q], NULL,
matrix(0, nrow = 1, ncol = 1), 0, matrix(0, nrow = 1,
ncol = 1))
cc[q] = ca$a
vector.a.ma.schall[, q] = mean.coefficients + ca$a *
gg$a
}
diag.hat = matrix(diag.hat, nrow = length(diag.hat), ncol = np)
return(list(vector.a.ma.schall, lala, diag.hat, mean.coefficients,
gg$a, cc))
}
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