Nothing
##
## We need the splines library, so we load it.
##
#.onLoad <- function(lib, pkg) require(splines)
locmle <-
function(z, xlim , Jmle = 35, d = 0, s = 1, ep = 1/100000, sw = 0, Cov.in)
{
## uses z-values in [-xlim,xlim] to find mles for p0,del0,sig0
## Jmle number of iterations, beginning at (del0,sig0)=(d,s)
## sw=1 returns correlation matrix
N = length(z)
if (missing(xlim)) {
if (N>500000) b = 1
else b=4.3 * exp(-0.26*log(N,10))
xlim=c(median(z),b*diff(quantile(z)[c(2,4)])/(2*qnorm(.75)))
}
aorig=xlim[1]-xlim[2]
borig=xlim[1]+xlim[2]
z0=z[which(z>=aorig & z<=borig)]
N0 = length(z0)
Y = c(mean(z0), mean(z0^2))
that = N0/N
######## find mle estimates ###########################
for(j in 1:Jmle) {
bet = c(d/s^2, -1/(2 * s^2))
aa = (aorig - d)/s
bb = (borig - d)/s
H0 = pnorm(bb) - pnorm(aa)
fa = dnorm(aa)
fb = dnorm(bb)
H1 = fa - fb
H2 = H0 + aa * fa - bb * fb
H3 = (2 + aa^2) * fa - (2 + bb^2) * fb
H4 = 3 * H0 + (3 * aa + aa^3) * fa - (3 * bb + bb^3) * fb
H = c(H0, H1, H2, H3, H4)
r = d/s
I = matrix(rep(0, 25), 5)
for(i in 0:4)
I[i + 1, 0:(i + 1)] = choose(i, 0:i)
u1 = s^(0:4)
II = pmax(row(I) - col(I), 0)
II = r^II
I = u1 * (I * II)
E = as.vector(I %*% H)/H0
E1 = E[2]
E2 = E[3]
E3 = E[4]
E4 = E[5]
mu = c(E1, E2)
V = matrix(c(E2 - E1^2, E3 - E1 * E2, E3 - E1 * E2, E4 -
E2^2), 2)
bett = bet + solve(V, Y - mu)/(1 + 1/j^2)
if(bett[2]>0)bett=bet+.1*solve(V, Y - mu)/(1 + 1/j^2)
if (is.na(bett[2])) break
else if (bett[2]>=0) break
d = - bett[1]/(2 * bett[2])
s = 1/sqrt(-2 * bett[2])
if(sum((bett - bet)^2)^0.5 < ep)
break
}
if (is.na(bett[2])) {
mle = rep(NA, 6)
Cov.lfdr = NA
Cor = matrix(NA, 3, 3)
}
else if (bett[2] >=0) {
mle = rep(NA, 6)
Cov.lfdr = Cov.out = NA
Cor = matrix(NA, 3, 3)
}
else {
aa = (aorig - d)/s
bb = (borig - d)/s
H0 = pnorm(bb) - pnorm(aa)
p0 = that/H0
############ sd calcs ###########################
J = s^2 * matrix(c(1, 0, 2 * d, s), 2)
JV = J %*% solve(V)
JVJ = JV %*% t(J)
mat2 = cbind(0, JVJ/N0)
mat1 = c((p0 * H0 * (1 - p0 * H0))/N, 0, 0)
mat = rbind(mat1, mat2)
h = c(H1/H0, (H2 - H0)/H0)
matt = c(1/H0, - (p0/s) * t(h))
matt = rbind(matt, cbind(0, diag(2)))
C = matt %*% (mat %*% t(matt))
mle = c(p0, d, s, diag(C)^0.5)
if(sw == 1) {
sd = mle[4:6]
Co = C/outer(sd, sd)
dimnames(Co) = list(c("p0", "d", "s"), c("p0", "d", "s"))
Cor = Co[c(2, 3, 1), c(2, 3, 1)]
}
if (!missing(Cov.in)) {
i0 = which(Cov.in$x > aa & Cov.in$x < bb)
Cov.out = loccov(N, N0, p0, d, s, Cov.in$x, Cov.in$X, Cov.in$f,
JV, Y, i0, H, h, Cov.in$sw)
}
}
names(mle) = c("p0", "del0", "sig0", "sd.p0", "sd.del0", "sd.sig0")
mle = mle[c(2, 3, 1, 5, 6, 4)]
out = list(mle=mle)
if (sw==1) {
Cor = list(Cor = Cor)
out = c(out, Cor)
}
if (!missing(Cov.in)) {
if (Cov.in$sw == 2) {
pds. = list(pds.=Cov.out)
out = c(out, pds.)
}
else if (Cov.in$sw == 3) {
Ilfdr = list(Ilfdr=Cov.out)
out = c(out, Ilfdr)
}
else {
Cov.lfdr = list(Cov.lfdr=Cov.out)
out = c(out, Cov.lfdr)
}
}
if ((sw==1) | !missing(Cov.in)) return(out)
else return(mle)
}
loccov = function(N, N0, p0, d, s, x, X, f, JV, Y, i0, H, h, sw) {
M = rbind(1, x - Y[1], x^2 - Y[2])
if (sw==2) {
K = length(x)
K0 = length(i0)
toprow = c(1 - N0/N, -t(h) %*% JV / s)
botrow = cbind(0, JV / p0)
mat = rbind(toprow, botrow)
M0 = M[,i0]
dpds.dy0 = mat %*% M0 / N / H[1]
dy0.dy = matrix(0, K0, K)
dy0.dy[,i0] = diag(1, K0)
dpds.dy = dpds.dy0 %*% dy0.dy
rownames(dpds.dy) = c("p", "d", "s")
return(dpds.dy)
}
else {
xstd = (x - d)/s
U = cbind(xstd - H[2]/H[1], xstd^2 - H[3]/H[1])
M[,-i0] = 0
dl0plus.dy = cbind(1 - N0/N, U %*% JV / s) %*% M /N/H[1]/p0
G <- t(X) %*% (f * X)
dl.dy = X %*% solve(G) %*% t(X)
dlfdr.dy = dl0plus.dy - dl.dy
if (sw==3) return(dlfdr.dy)
else {
Cov.lfdr = dlfdr.dy %*% (f * t(dlfdr.dy))
return(Cov.lfdr)
}
}
}
loccov2 = function(X, X0, i0, f, ests, N) {
d = ests[1]
s = ests[2]
p0 = ests[3]
theo = I(ncol(X0)==1)
Xtil <- X[i0,]
X0til <- X0[i0,]
G <- t(X) %*% (f * X)
G0 <- t(X0til) %*% X0til
B0 <- X0 %*% (solve(G0) %*% t(X0til)) %*% Xtil
C <- B0 - X
Ilfdr = C %*% solve(G, t(X))
Cov <- C %*% solve(G) %*% t(C)
if (theo)
D = matrix(1,1,1)
else
D = matrix(c(1, 0, 0, d, s^2, 0, s^2 + d^2, 2 * d * s^2, s^3), 3)
gam. = solve(G0, t(X0til)) %*% (Xtil %*% solve(G, t(X)))
pds. = D %*% gam.
if (theo) pds. = rbind(pds., matrix(0, 2, nrow(X)))
pds.[1,] = pds.[1,] - 1/N
m1 = pds. %*% f
m2 = pds.^2 %*% f
stdev = as.vector(sqrt(m2 - m1^2/N))
stdev[1] = p0 * stdev[1]
pds.[1,] = p0 * pds.[1,]
rownames(pds.) = c("p", "d", "s")
list(Ilfdr = Ilfdr, pds.=pds., stdev=stdev, Cov=Cov)
}
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