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authorJohannes Ranke <jranke@uni-bremen.de>2017-03-24 15:28:44 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2017-03-24 15:28:44 +0100
commitbaf8e4341b58c09532b4ca37ebf80c9068934db4 (patch)
treea6abd8cbdfa849a672d2abcfde5af4bfc180bcf6 /R/drfit.R
parent22c11d5dbc118881f9cfd7c9c2ac9711295a0f16 (diff)
Import version 0.6.7 from CRAN
I had deleted the git commits between 0.6.4 and 0.6.7 while removing drfit from github, while the latest changes were not pushed to jrwb.de yet.
Diffstat (limited to 'R/drfit.R')
-rw-r--r--R/drfit.R47
1 files changed, 20 insertions, 27 deletions
diff --git a/R/drfit.R b/R/drfit.R
index 65ab8e4..7fa53bf 100644
--- a/R/drfit.R
+++ b/R/drfit.R
@@ -18,7 +18,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
# model result was appended
rsubstance <- array() # the substance names in the results
rndl <- vector() # number of dose levels
- rn <- vector() # mean number of replicates
+ rn <- vector() # mean number of replicates
# in each dose level
runit <- vector() # vector of units for each result row
rlhd <- rlld <- vector() # highest and lowest doses tested
@@ -75,13 +75,12 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
active <- TRUE
} else {
active <- FALSE
- if (linlogit &&
+ if (linlogit &&
length(subset(linlogitWrong,linlogitWrong == i))==0 &&
length(subset(allWrong,allWrong == i))==0) {
m <- try(nls(response ~ linlogitf(dose,1,f,logED50,b),
- data=tmp, algorithm="port",
- start=list(f=f0,logED50=startlogED50[[i]],b=b0)),
- silent = TRUE)
+ data=tmp, algorithm="port",
+ start=list(f=f0,logED50=startlogED50[[i]],b=b0)))
if (!inherits(m, "try-error")) {
fit <- TRUE
ri <- ri + 1
@@ -105,8 +104,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
c[[ri]] <- NA
} else {
mtype[[ri]] <- "linlogit"
- logED50conf <- try(confint(m,"logED50",level=level),
- silent = TRUE)
+ logED50conf <- try(confint(m,"logED50",level=level))
if (!inherits(logED50conf, "try-error")) {
logED50low[[ri]] <- logED50conf[[1]]
logED50high[[ri]] <- logED50conf[[2]]
@@ -124,9 +122,8 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
if (probit &&
length(subset(allWrong,allWrong == i))==0) {
m <- try(nls(response ~ pnorm(-log10(dose),-logED50,scale),
- data=tmp, algorithm="port",
- start=list(logED50=startlogED50[[i]],scale=ps0)),
- silent = TRUE)
+ data=tmp, algorithm="port",
+ start=list(logED50=startlogED50[[i]],scale=ps0)))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
fit <- TRUE
@@ -151,8 +148,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
b[[ri]] <- NA
} else {
mtype[[ri]] <- "probit"
- logED50conf <- try(confint(m,"logED50",level=level),
- silent = TRUE)
+ logED50conf <- try(confint(m,"logED50",level=level))
if (!inherits(logED50conf, "try-error")) {
logED50low[[ri]] <- logED50conf[[1]]
logED50high[[ri]] <- logED50conf[[2]]
@@ -170,9 +166,8 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
if (logit &&
length(subset(allWrong,allWrong == i))==0) {
m <- try(nls(response ~ plogis(-log10(dose),-logED50,scale),
- data=tmp, algorithm="port",
- start=list(logED50=startlogED50[[i]],scale=ls0)),
- silent = TRUE)
+ data=tmp, algorithm="port",
+ start=list(logED50=startlogED50[[i]],scale=ls0)))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
fit <- TRUE
@@ -198,8 +193,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
b[[ri]] <- NA
} else {
mtype[[ri]] <- "logit"
- logED50conf <- try(confint(m,"logED50",level=level),
- silent = TRUE)
+ logED50conf <- try(confint(m,"logED50",level=level))
if (!inherits(logED50conf, "try-error")) {
logED50low[[ri]] <- logED50conf[[1]]
logED50high[[ri]] <- logED50conf[[2]]
@@ -215,9 +209,8 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
if (weibull &&
length(subset(allWrong,allWrong == i))==0) {
m <- try(nls(response ~ pweibull(-log10(dose)+location,shape),
- data=tmp, algorithm="port",
- start=list(location=startlogED50[[i]],shape=ws0)),
- silent = TRUE)
+ data=tmp, algorithm="port",
+ start=list(location=startlogED50[[i]],shape=ws0)))
if (chooseone==FALSE || fit==FALSE) {
if (!inherits(m, "try-error")) {
ri <- ri + 1
@@ -225,7 +218,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
a[[ri]] <- coef(m)[["location"]]
b[[ri]] <- coef(m)[["shape"]]
sqrdev <- function(logdose) {
- (0.5 - pweibull( - logdose + a[[ri]], b[[ri]]))^2
+ (0.5 - pweibull( - logdose + a[[ri]], b[[ri]]))^2
}
logED50[[ri]] <- nlm(sqrdev,startlogED50[[i]])$estimate
if (sqrdev(logED50[[ri]]) > 0.1) {
@@ -298,7 +291,7 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
c[[ri]] <- NA
}
}
- results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype,
+ results <- data.frame(rsubstance, rndl, rn, rlld, rlhd, mtype,
logED50, logED50low, logED50high, runit, sigma, a, b)
lower_level_percent = paste(100 * (1 - level)/2, "%", sep = "")
upper_level_percent = paste(100 * (1 + level)/2, "%", sep = "")
@@ -318,18 +311,18 @@ drfit <- function(data, startlogED50 = NA, chooseone=TRUE,
if (mtype[[row.i]] %in% c("probit", "logit", "weibull", "linlogit")) {
for (ED in EDx) {
of <- function(x) {
- abs(predict(models[[row.i]], data.frame(dose = 10^x)) -
+ abs(predict(models[[row.i]], data.frame(dose = 10^x)) -
(1 - (ED/100)))
- }
- # Search over interval starting an order of magnitude below
+ }
+ # Search over interval starting an order of magnitude below
# the lowest dose up to one order of magnitude above the
# highest dose
- o = optimize(of,
+ o = optimize(of,
results[row.i, c("lld", "lhd")] + c(-1, 1))
# Only keep results within the tolerance
if ((o$objective) < EDx.tolerance) {
logdose.ED = o$minimum
- results[row.i, paste0("EDx", ED)] <- 10^logdose.ED
+ results[row.i, paste0("EDx", ED)] <- 10^logdose.ED
}
}
}

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