Displaying 3 results from an estimated 3 matches for "drmc".
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drm
2012 May 15
6
Curva dosis-respuesta
...76116462
)), .Names = c("y", "dose"), row.names = c(NA, -9L), class = "data.frame")
# curva
# install.packages(''drm'')
require(drm, quietly = TRUE, warn.conflicts = FALSE)
with(d, plot(dose, y, las = 1))
fit <- drm(y ~ dose, fct = LL.4(), control = drmc(maxIt = 100000, relTol =
1e-4), data = d)
# Error in optim(startVec, opfct, hessian = TRUE, method = optMethod,
control = list(maxit = maxIt, :
# non-finite finite-difference value [4]
# Error in drmOpt(opfct, opdfct1, startVecSc, optMethod, constrained,
warnVal, :
# Convergence failed
He camb...
2009 May 20
2
drc results differ for different versions
...5.495, -3.352, 102.464, 83.114, 50.631, 22.792, 18.348,
19.066, 27.794, 14.682, 11.992, 12.868))
m<- drm(response ~ (log10(dose*1e6)), data = d, fct = l4(fixed =
c(NA,NA,NA,NA), names = c("hs", "bottom", "top", "ec50")), logDose = 10,
control = drmc(useD = T))
summary(m)
results in:
Model fitted: Log-logistic (ED50 as parameter) (4 parms)
Parameter estimates:
Estimate Std. Error t-value p-value
hs:(Intercept) -9.8065e-01 2.5821e-03 -3.7979e+02 2.248e-33
bottom:(Intercept) 1.0955e+01 2.2546e-02 4.8591e+02...
2010 May 21
0
weighted regression using drm() in drc package
...drc package, and nls(), found very different
results derived from drm() vs. nls() using "weights=" argument.
d1<-read.table("d1.txt",sep='\t',header=T,row.names=1)
drm(y~x,weights=1/exp((-1.8286)+0.05481*y-0.000405225*(y-48.34177)^2),data = d1,fct = LL.4(),control=drmc(relTol=1e-12))
b:(Intercept) c:(Intercept) d:(Intercept) e:(Intercept)
-1.5859 0.7823 47.3591 38.7717
nls(y~c+(d-c)/(1+(x/e)^b),weights=1/exp((-1.8286)+0.05481*y-0.000405225*(y-48.34177)^2),data=d1,
start=list(b=-1, c =0, d=100, e=150))
b c d...