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