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study13_narrow_dt.R
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# Function containing the framework setup in the intial study design
# -----------------------------------------------------------------------------
# Set up directories
if (!exists("git.dir")) {
rm(list = ls(all = T))
wd <- c("C:/Users/Jim Hughes/Documents", "C:/Users/hugjh001/Documents",
"C:/Users/hugjh001/Desktop", "C:/windows/system32")
graphics.off()
if (getwd() == wd[1]) {
gir.dir <- paste0(getwd(), "/GitRepos")
reponame <- "optinterval"
} else if (getwd() == wd[2]) {
git.dir <- getwd()
reponame <- "optinterval"
} else if (getwd() == wd[3] | getwd() == wd[4]) {
git.dir <- "E:/Hughes/Git"
reponame <- "splines"
}
rm("wd")
}
# Load packages
library(GA)
#library(ggplot2)
#theme_bw2 <- theme_set(theme_bw(base_size = 14))
#theme_update(plot.title = element_text(hjust = 0.5))
# Source scripts to set up environment
source(paste(git.dir, reponame, "study_functions.R", sep = "/"))
# -----------------------------------------------------------------------------
# Set basic parameters
set.seed(256256)
t1 <- c(0, 0.5, 1, 1.5, 2, 3, 4, 6, 8, 12, 16, 24)
niter <- 1000
time.samp <- seq(0, 24, by = 0.05)
sdev <- 0.15
tlast <- max(t1)
nobs <- 7
t0 <- c(t1[1:(nobs+1)], tlast)
pred.d1a <- function(x, p) {
exp(p[1]*x + p[3]) - exp(p[2]*x + p[3])
}
d1a.p <- c(-0.2, -0.4, 4)
d1a <- pred.d1a(time.samp, d1a.p)
times <- seq(0, tlast, length.out = nobs)
err <- matrix(
1 + rnorm(n = length(times)*niter, mean = 0, sd = sdev),
nrow = length(times), ncol = niter
)
subd <- d1a[which(time.samp %in% times)]*err
fit.par <- apply(subd, 2, function(x) {
chisq.sumexp(optim.sumexp.hes(
data.frame(time = times, conc = x), oral = T
))$par
})
t2 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0)$times, 1), tlast)
)
t3 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0, tmax = T)$times, 1), tlast)
)
auc <- data.frame(
true = integrate(pred.d1a, 0, tlast, p = d1a.p)$value,
user = auc.interv(t1, d1a.p, pred.d1a),
optint = apply(t2, 2, function(x) auc.interv(x, d1a.p, pred.d1a)),
optintwCmax = apply(t3, 2, function(x) auc.interv(x, d1a.p, pred.d1a))
)
cmax <- data.frame(
true = pred.sumexp(d1a.p, tmax.sumexp(d1a.p)),
user = max(pred.sumexp(d1a.p, t1)),
optint = apply(t2, 2, function(x) max(pred.sumexp(d1a.p, x))),
optintwCmax = apply(t3, 2, function(x) max(pred.sumexp(d1a.p, x)))
)
tmax <- data.frame(
true = tmax.sumexp(d1a.p),
user = t1[which(pred.sumexp(d1a.p, t1) == cmax$user[1])],
optint = mapply(cmax$optint, data.frame(t2),
FUN = function(y, z) z[which(pred.sumexp(d1a.p, z) == y)][1]
),
optintwCmax = mapply(cmax$optintwCmax, data.frame(t3),
FUN = function(y, z) z[which(pred.sumexp(d1a.p, z) == y)][1]
)
)
d1a.out <- list(
par = d1a.p, fit.par = fit.par, t2 = t2, t3 = t3,
auc = auc, cmax = cmax, tmax = tmax
)
setwd("E:/Hughes/Git/splines/fn_diag")
saveRDS(d1a.out, "d1a-narrow-dt15.rds")
# -----------------------------------------------------------------------------
pred.d2a <- function(x, p) {
exp(p[1]*x + p[4]) + exp(p[2]*x + p[5]) - exp(p[3]*x + log(sum(exp(p[4]), exp(p[5]))))
}
d2a.p <- c(-0.06, -0.4, -0.6, log(exp(4)*0.15), log(exp(4)*0.85))
d2a <- pred.d2a(time.samp, d2a.p)
times <- seq(0, tlast, length.out = nobs)
err <- matrix(
1 + rnorm(n = length(times)*niter, mean = 0, sd = sdev),
nrow = length(times), ncol = niter
)
subd <- d2a[which(time.samp %in% times)]*err
fit.par <- apply(subd, 2, function(x) {
chisq.sumexp(optim.sumexp.hes(
data.frame(time = times, conc = x), oral = T
))$par
})
t2 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0)$times, 1), tlast)
)
t3 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0, tmax = T)$times, 1), tlast)
)
auc <- data.frame(
true = integrate(pred.d2a, 0, tlast, p = d2a.p)$value,
user = auc.interv(t1, d2a.p, pred.d2a),
optint = apply(t2, 2, function(x) auc.interv(x, d2a.p, pred.d2a)),
optintwCmax = apply(t3, 2, function(x) auc.interv(x, d2a.p, pred.d2a))
)
cmax <- data.frame(
true = pred.sumexp(d2a.p, tmax.sumexp(d2a.p)),
user = max(pred.sumexp(d2a.p, t1)),
optint = apply(t2, 2, function(x) max(pred.sumexp(d2a.p, x))),
optintwCmax = apply(t3, 2, function(x) max(pred.sumexp(d2a.p, x)))
)
tmax <- data.frame(
true = tmax.sumexp(d2a.p),
user = t1[which(pred.sumexp(d2a.p, t1) == cmax$user[1])],
optint = mapply(cmax$optint, data.frame(t2),
FUN = function(y, z) z[which(pred.sumexp(d2a.p, z) == y)][1]
),
optintwCmax = mapply(cmax$optintwCmax, data.frame(t3),
FUN = function(y, z) z[which(pred.sumexp(d2a.p, z) == y)][1]
)
)
d2a.out <- list(
par = d2a.p, fit.par = fit.par, t2 = t2, t3 = t3,
auc = auc, cmax = cmax, tmax = tmax
)
setwd("E:/Hughes/Git/splines/fn_diag")
saveRDS(d2a.out, "d2a-narrow-dt15.rds")
# -----------------------------------------------------------------------------
pred.d3a <- function(x, p) {
exp(p[1]*x + p[5]) + exp(p[2]*x + p[6]) + exp(p[3]*x + p[7]) - exp(p[4]*x + log(sum(exp(p[5]), exp(p[6]), exp(p[7]))))
}
d3a.p <- c(-0.05, -0.25, -0.6, -1, log(exp(4)*0.10), log(exp(4)*0.35), log(exp(4)*0.55))
d3a <- pred.d3a(time.samp, d3a.p)
times <- seq(0, tlast, length.out = nobs)
err <- matrix(
1 + rnorm(n = length(times)*niter, mean = 0, sd = sdev),
nrow = length(times), ncol = niter
)
subd <- d3a[which(time.samp %in% times)]*err
fit.par <- apply(subd, 2, function(x) {
chisq.sumexp(optim.sumexp.hes(
data.frame(time = times, conc = x), oral = T
))$par
})
t2 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0)$times, 1), tlast)
)
t3 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0, tmax = T)$times, 1), tlast)
)
auc <- data.frame(
true = integrate(pred.d3a, 0, tlast, p = d3a.p)$value,
user = auc.interv(t1, d3a.p, pred.d3a),
optint = apply(t2, 2, function(x) auc.interv(x, d3a.p, pred.d3a)),
optintwCmax = apply(t3, 2, function(x) auc.interv(x, d3a.p, pred.d3a))
)
cmax <- data.frame(
true = pred.sumexp(d3a.p, tmax.sumexp(d3a.p)),
user = max(pred.sumexp(d3a.p, t1)),
optint = apply(t2, 2, function(x) max(pred.sumexp(d3a.p, x))),
optintwCmax = apply(t3, 2, function(x) max(pred.sumexp(d3a.p, x)))
)
tmax <- data.frame(
true = tmax.sumexp(d3a.p),
user = t1[which(pred.sumexp(d3a.p, t1) == cmax$user[1])],
optint = mapply(cmax$optint, data.frame(t2),
FUN = function(y, z) z[which(pred.sumexp(d3a.p, z) == y)][1]
),
optintwCmax = mapply(cmax$optintwCmax, data.frame(t3),
FUN = function(y, z) z[which(pred.sumexp(d3a.p, z) == y)][1]
)
)
d3a.out <- list(
par = d3a.p, fit.par = fit.par, t2 = t2, t3 = t3,
auc = auc, cmax = cmax, tmax = tmax
)
setwd("E:/Hughes/Git/splines/fn_diag")
saveRDS(d3a.out, "d3a-narrow-dt15.rds")
# -----------------------------------------------------------------------------
pred.d2b <- function(x, p) {
exp(p[1]*x + p[3]) + exp(p[2]*x + p[4])
}
d2b.p <- c(-0.06, -0.5, 5, 6)
d2b <- pred.d2b(time.samp, d2b.p)
times <- seq(0, tlast, length.out = nobs)
err <- matrix(
1 + rnorm(n = length(times)*niter, mean = 0, sd = sdev),
nrow = length(times), ncol = niter
)
subd <- d2b[which(time.samp %in% times)]*err
fit.par <- apply(subd, 2, function(x) {
chisq.sumexp(optim.sumexp.hes(
data.frame(time = times, conc = x), oral = T
))$par
})
t2 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0)$times, 1), tlast)
)
t3 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0, tmax = T)$times, 1), tlast)
)
auc <- data.frame(
true = integrate(pred.d2b, 0, tlast, p = d2b.p)$value,
user = auc.interv(t1, d2b.p, pred.d2b),
optint = apply(t2, 2, function(x) auc.interv(x, d2b.p, pred.d2b)),
optintwCmax = apply(t3, 2, function(x) auc.interv(x, d2b.p, pred.d2b))
)
cmax <- data.frame(
true = pred.sumexp(d2b.p, tmax.sumexp(d2b.p)),
user = max(pred.sumexp(d2b.p, t1)),
optint = apply(t2, 2, function(x) max(pred.sumexp(d2b.p, x))),
optintwCmax = apply(t3, 2, function(x) max(pred.sumexp(d2b.p, x)))
)
tmax <- data.frame(
true = tmax.sumexp(d2b.p),
user = t1[which(pred.sumexp(d2b.p, t1) == cmax$user[1])],
optint = mapply(cmax$optint, data.frame(t2),
FUN = function(y, z) z[which(pred.sumexp(d2b.p, z) == y)][1]
),
optintwCmax = mapply(cmax$optintwCmax, data.frame(t3),
FUN = function(y, z) z[which(pred.sumexp(d2b.p, z) == y)][1]
)
)
d2b.out <- list(
par = d2b.p, fit.par = fit.par, t2 = t2, t3 = t3,
auc = auc, cmax = cmax, tmax = tmax
)
setwd("E:/Hughes/Git/splines/fn_diag")
saveRDS(d2b.out, "d2b-narrow-dt15.rds")
# -----------------------------------------------------------------------------
pred.d3b <- function(x, p) {
exp(p[1]*x + p[4]) + exp(p[2]*x + p[5]) + exp(p[3]*x + p[6])
}
d3b.p <- c(-0.03, -0.15, -0.5, 3.8, 4.7, 6)
d3b <- pred.d3b(time.samp, d3b.p)
times <- seq(0, tlast, length.out = nobs)
err <- matrix(
1 + rnorm(n = length(times)*niter, mean = 0, sd = sdev),
nrow = length(times), ncol = niter
)
subd <- d3b[which(time.samp %in% times)]*err
fit.par <- apply(subd, 2, function(x) {
chisq.sumexp(optim.sumexp.hes(
data.frame(time = times, conc = x), oral = T
))$par
})
t2 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0)$times, 1), tlast)
)
t3 <- sapply(fit.par, simplify = "array",
FUN = function(x) c(0, round(optim.interv.dtmax(x, t0, tmax = T)$times, 1), tlast)
)
auc <- data.frame(
true = integrate(pred.d3b, 0, tlast, p = d3b.p)$value,
user = auc.interv(t1, d3b.p, pred.d3b),
optint = apply(t2, 2, function(x) auc.interv(x, d3b.p, pred.d3b)),
optintwCmax = apply(t3, 2, function(x) auc.interv(x, d3b.p, pred.d3b))
)
cmax <- data.frame(
true = pred.sumexp(d3b.p, tmax.sumexp(d3b.p)),
user = max(pred.sumexp(d3b.p, t1)),
optint = apply(t2, 2, function(x) max(pred.sumexp(d3b.p, x))),
optintwCmax = apply(t3, 2, function(x) max(pred.sumexp(d3b.p, x)))
)
tmax <- data.frame(
true = tmax.sumexp(d3b.p),
user = t1[which(pred.sumexp(d3b.p, t1) == cmax$user[1])],
optint = mapply(cmax$optint, data.frame(t2),
FUN = function(y, z) z[which(pred.sumexp(d3b.p, z) == y)][1]
),
optintwCmax = mapply(cmax$optintwCmax, data.frame(t3),
FUN = function(y, z) z[which(pred.sumexp(d3b.p, z) == y)][1]
)
)
d3b.out <- list(
par = d3b.p, fit.par = fit.par, t2 = t2, t3 = t3,
auc = auc, cmax = cmax, tmax = tmax
)
setwd("E:/Hughes/Git/splines/fn_diag")
saveRDS(d3b.out, "d3b-narrow-dt15.rds")