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R version 3.3.3 (2017-03-06) -- "Another Canoe"
Copyright (C) 2017 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(drfit)
> data(IM1xIPC81)
> rIM1xIPC81 <- drfit(IM1xIPC81,linlogit=TRUE)
IM13 BF4: Fitting data...
IM14 BF4: Fitting data...
IM15 BF4: Fitting data...
IM16 BF4: Fitting data...
IM17 BF4: Fitting data...
Waiting for profiling to be done...
IM18 BF4: Fitting data...
Waiting for profiling to be done...
IM19 BF4: Fitting data...
Waiting for profiling to be done...
IM1-10 BF4: Fitting data...
Waiting for profiling to be done...
Warning messages:
1: In pnorm(-log10(dose), -logED50, scale) : NaNs produced
2: In pnorm(-log10(dose), -logED50, scale) : NaNs produced
3: In pnorm(-log10(dose), -logED50, scale) : NaNs produced
4: In pnorm(-log10(dose), -logED50, scale) : NaNs produced
> print(rIM1xIPC81,digits=4)
Substance ndl n lld lhd mtype logED50 2.5% 97.5% unit sigma
1 IM13 BF4 9 81 0.5918 3.000 inactive NA NA NA microM NA
2 IM14 BF4 20 216 -0.0103 3.176 no fit NA NA NA microM NA
3 IM15 BF4 9 135 0.5918 3.000 inactive NA NA NA microM NA
4 IM16 BF4 9 108 0.5918 3.000 inactive NA NA NA microM NA
5 IM17 BF4 9 81 0.5918 3.000 linlogit 2.5786 2.506 2.6617 microM 0.2376
6 IM18 BF4 9 135 0.5918 3.000 linlogit 1.6806 1.623 1.7419 microM 0.2325
7 IM19 BF4 9 81 0.5918 3.000 linlogit 1.6496 1.598 1.7031 microM 0.1453
8 IM1-10 BF4 11 162 -0.0103 3.000 linlogit 0.7697 0.687 0.8544 microM 0.2988
a b c
1 NA NA NA
2 NA NA NA
3 NA NA NA
4 NA NA NA
5 2.5786 2.300 0.01468
6 1.6806 2.237 0.05719
7 1.6496 1.977 0.10956
8 0.7697 1.936 0.45809
>
> proc.time()
user system elapsed
1.600 0.676 1.525
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