Displaying 3 results from an estimated 3 matches for "conc2".
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2012 Nov 30
1
help on "stacking" matrices up
...E1))
CAFTINF1 <-((Dose/Tinf)*(1/(0.088*76.9)))*(1-exp(-0.088*Tinf))*(exp(-0.088*(TIME1)))
CONC1 <-ifelse(TIME1<=Tinf,CDURINF1,CAFTINF1)
CDURINF2 <-((Dose/Tinf)*(1/(0.088*76.9)))*(1-exp(-0.088*TIME2))
CAFTINF2 <-((Dose/Tinf)*(1/(0.088*76.9)))*(1-exp(-0.088*Tinf))*(exp(-0.088*(TIME2)))
CONC2 <-ifelse(TIME2<=Tinf,CDURINF2,CAFTINF2)
CDURINF3 <-((Dose/Tinf)*(1/(0.088*76.9)))*(1-exp(-0.088*TIME3))
CAFTINF3 <-((Dose/Tinf)*(1/(0.088*76.9)))*(1-exp(-0.088*Tinf))*(exp(-0.088*(TIME3)))
CONC3 <-ifelse(TIME3<=Tinf,CDURINF3,CAFTINF3)
CDURINF4 <-((Dose/Tinf)*(1/(0.088*76.9)))*(...
2013 Apr 15
2
regression with paired left-censored data
...a = cenreg(Cen(conc, cens_ind) ~ Gp_ident))?
with all X and Y data stacked and using a group identifier to look at the differences
this doesn't take account of the paired data though.
I have also tried splitting the data and regessing one on the other
rega = cenreg(Cen(conc1, censind1) ~ Cen(conc2,censind2))
which doesn't work.
Does anyone know of a command that will work - or perhaps suggest another package that I could use?
I have also looked at multiple imputation packages but they all seem to impute data depending on other columns - whereas I would want to impute data between zero...
2011 Jan 11
0
modified FAST Script from package SensoMineR for the R community - Reg
...ut = matrix(NA, I, J)
lev = rep(NA, J)
for (i in 1:J) {
lev[i] = length(levels(don[, i]))
}
tdc = tab.disjonctif(don)
gp = 0
for (i in 1:J) {
conc = cbind(c(1:lev[i]), acm$var$coord[(1 + gp):(gp +
lev[i]), 1])
o = order(conc[, 2])
conc2 = cbind(conc[o, ], c(1:lev[i]))
o2 = order(conc2[, 1])
conc3 = conc2[o2, ]
out[, i] = tdc[, (1 + gp):(gp + lev[i])] %*% conc3[,
3]
gp = gp + lev[i]
}
out = data.frame(out)
for (i in 1:J) {
out[, i] = as.factor(out[, i])
}
cate...