Runs a batch of optimization tasks
batch.RdRuns a batch of optimization tasks
Usage
batch(
case,
lowerBounds,
upperBounds,
path,
additionalParameters,
seed = NA,
npop = 40,
ngen = 200,
Topology = "random",
errorThreshold = -Inf,
num_rep = 1,
num_cores = 1
)Arguments
- case
is a character argument which specifies the optimization case. Either "dba_dye_const", "dba_host_const", "ida" or "gda"
- lowerBounds
is a numeric vector with the lower bounds for the optimization
- upperBounds
is a numeric vector with the upper bounds for the optimization
- path
is a character argument which specifies the path to the data
- additionalParameters
is a numeric vector with additional parameters In case of dba_dye_const or *dba_host_const the order of the parameters is: khd, I0, IHD and ID In case of ida and ga the order of the parameters is: kg, I0, IHD and ID.
- seed
is an optional integer argument defining the seed which is set directly for the optimization. In case the argument is not set the current time is used as seed.
- npop
is an optional integer argument defining the number of particles during optimization. The default value is set to 40.
- ngen
is an optional integer argument defining the number of generations of the particle swarm optimization. The default value is set to 200.
- Topology
is an optional character argument defining which topology should be used by the particle swarm algorithm. The options are "star" and "random". The default topology is the "random" topology.
- errorThreshold
is an optional numeric argument defining a sufficient small error which acts as a stop signal for the particle swarm algorithm. The default value is set to -Inf.
- num_rep
is an optional integer argument defining the number of replicates for each dataset
- num_cores
is an optional integer argument defining the maximum number of cores which should be used for the optimization
Examples
path <- paste0(system.file("examples", package = "tsf"), "/IDABatch.csv")
lowerBounds <- c(
kG = 1000,
I0 = 0,
IHD = 0,
ID = 0
)
upperBounds <- c(
kG = 10^8,
I0 = 100,
IHD = 10^7,
ID = 10^7
)
additionalParameters <- c(
host = 1e-6,
dye = 1e-6,
kHD = 3e6
)
tsf::batch(
"ida",
lowerBounds, upperBounds,
path, additionalParameters,
ngen = 20
)
#> Warning: NAs introduced by coercion
#>
#>
#>
#>
#>
#> Dataset = 1; Replicate = 1; Generation = 2; Ka(HG) = 5.526e+06; I(0) = 2.457e-06; I(HD) = 1.277e+06; I(D) = 8.561e+03; Error = 9.009e+00
#> Dataset = 1; Replicate = 1; Generation = 2; Ka(HG) = 5.526e+06; I(0) = 2.457e-06; I(HD) = 1.277e+06; I(D) = 8.561e+03; Error = 9.009e+00
#> Dataset = 1; Replicate = 1; Generation = 4; Ka(HG) = 1.151e+07; I(0) = 6.772e-03; I(HD) = 9.493e+05; I(D) = 1.357e+05; Error = 5.210e+00
#> Dataset = 1; Replicate = 1; Generation = 6; Ka(HG) = 1.875e+07; I(0) = 1.465e-02; I(HD) = 9.706e+05; I(D) = 1.984e+05; Error = 2.223e+00
#> Dataset = 1; Replicate = 1; Generation = 7; Ka(HG) = 1.495e+07; I(0) = 1.000e-15; I(HD) = 8.141e+05; I(D) = 2.049e+05; Error = 1.943e+00
#> Dataset = 1; Replicate = 1; Generation = 8; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 9; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 10; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 11; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 12; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 13; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 14; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 15; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 16; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 17; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 18; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 19; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 20; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 20; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 20; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 20; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 20; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 1; Replicate = 1; Generation = 20; Ka(HG) = 2.895e+07; I(0) = 2.704e-02; I(HD) = 1.048e+06; I(D) = 1.789e+05; Error = 1.102e+00
#> Dataset = 2; Replicate = 1; Generation = 2; Ka(HG) = 2.932e+04; I(0) = 2.025e-10; I(HD) = 4.300e-06; I(D) = 4.948e+05; Error = 1.186e+01
#> Dataset = 2; Replicate = 1; Generation = 2; Ka(HG) = 2.932e+04; I(0) = 2.025e-10; I(HD) = 4.300e-06; I(D) = 4.948e+05; Error = 1.186e+01
#> Dataset = 2; Replicate = 1; Generation = 4; Ka(HG) = 2.456e+06; I(0) = 3.391e-08; I(HD) = 1.107e+06; I(D) = 4.540e+00; Error = 5.908e+00
#> Dataset = 2; Replicate = 1; Generation = 4; Ka(HG) = 2.456e+06; I(0) = 3.391e-08; I(HD) = 1.107e+06; I(D) = 4.540e+00; Error = 5.908e+00
#> Dataset = 2; Replicate = 1; Generation = 6; Ka(HG) = 7.533e+06; I(0) = 2.757e-04; I(HD) = 9.766e+05; I(D) = 1.239e+05; Error = 3.237e+00
#> Dataset = 2; Replicate = 1; Generation = 8; Ka(HG) = 6.108e+06; I(0) = 2.918e-02; I(HD) = 8.372e+05; I(D) = 1.275e+05; Error = 2.687e+00
#> Dataset = 2; Replicate = 1; Generation = 8; Ka(HG) = 6.108e+06; I(0) = 2.918e-02; I(HD) = 8.372e+05; I(D) = 1.275e+05; Error = 2.687e+00
#> Dataset = 2; Replicate = 1; Generation = 9; Ka(HG) = 1.114e+07; I(0) = 7.067e-02; I(HD) = 1.025e+06; I(D) = 8.838e+04; Error = 2.618e+00
#> Dataset = 2; Replicate = 1; Generation = 11; Ka(HG) = 1.114e+07; I(0) = 7.067e-02; I(HD) = 1.025e+06; I(D) = 8.838e+04; Error = 2.618e+00
#> Dataset = 2; Replicate = 1; Generation = 12; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 13; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 14; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 15; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 16; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 17; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 18; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 19; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Dataset = 2; Replicate = 1; Generation = 19; Ka(HG) = 7.837e+06; I(0) = 1.000e-15; I(HD) = 9.143e+05; I(D) = 1.665e+05; Error = 2.280e+00
#> Warning: Multiple components found; returning the first one. To return all, use `return_all = TRUE`.
#> Warning: Multiple components found; returning the first one. To return all, use `return_all = TRUE`.
#> [[1]]
#> [[1]]$states
#> [[1]]$states[[1]]
#> total Guest measured [M] Signal measured Signal simulated
#> 1 0.0e+00 0.6525932 0.6973886
#> 2 1.0e-07 0.6258308 0.6672067
#> 3 2.0e-07 0.5976011 0.6349859
#> 4 3.0e-07 0.5683364 0.6011339
#> 5 4.0e-07 0.5386060 0.5662572
#> 6 5.0e-07 0.5090762 0.5311499
#> 7 6.0e-07 0.4804428 0.4967386
#> 8 7.0e-07 0.4533454 0.4639783
#> 9 8.0e-07 0.4282865 0.4337107
#> 10 9.0e-07 0.4055805 0.4065300
#> 11 1.0e-06 0.3853446 0.3827091
#> 12 1.1e-06 0.3675292 0.3622144
#> 13 1.2e-06 0.3519687 0.3447905
#> 14 1.3e-06 0.3384343 0.3300640
#> 15 1.4e-06 0.3266753 0.3176300
#> 16 1.5e-06 0.3164472 0.3071058
#> 17 1.6e-06 0.3075263 0.2981559
#> 18 1.7e-06 0.2997164 0.2904990
#> 19 1.8e-06 0.2928491 0.2839044
#> 20 1.9e-06 0.2867826 0.2781858
#> 21 2.0e-06 0.2813977 0.2731931
#> 22 2.1e-06 0.2765953 0.2688056
#> 23 2.2e-06 0.2722924 0.2649260
#> 24 2.3e-06 0.2684201 0.2614755
#> 25 2.4e-06 0.2649204 0.2583898
#> 26 2.5e-06 0.2617448 0.2556163
#> 27 2.6e-06 0.2588524 0.2531117
#> 28 2.7e-06 0.2562084 0.2508399
#> 29 2.8e-06 0.2537834 0.2487708
#> 30 2.9e-06 0.2515523 0.2468793
#> 31 3.0e-06 0.2494933 0.2451440
#> 32 3.1e-06 0.2475880 0.2435467
#> 33 3.2e-06 0.2458201 0.2420719
#> 34 3.3e-06 0.2441758 0.2407064
#> 35 3.4e-06 0.2426428 0.2394387
#> 36 3.5e-06 0.2412104 0.2382587
#> 37 3.6e-06 0.2398692 0.2371578
#> 38 3.7e-06 0.2386109 0.2361285
#> 39 3.8e-06 0.2374283 0.2351640
#> 40 3.9e-06 0.2363148 0.2342586
#> 41 4.0e-06 0.2352647 0.2334070
#> 42 4.1e-06 0.2342726 0.2326046
#> 43 4.2e-06 0.2333342 0.2318473
#> 44 4.3e-06 0.2324450 0.2311314
#> 45 4.4e-06 0.2316015 0.2304537
#> 46 4.5e-06 0.2308002 0.2298113
#> 47 4.6e-06 0.2300382 0.2292014
#> 48 4.7e-06 0.2293125 0.2286217
#> 49 4.8e-06 0.2286206 0.2280700
#> 50 4.9e-06 0.2279604 0.2275443
#> 51 6.0e-06 0.2273297 0.2230640
#> free Dye simulated [M] Host-Dye simulated [M] repetition dataset
#> 1 4.342585e-07 5.657415e-07 1 1
#> 2 4.690050e-07 5.309950e-07 1 1
#> 3 5.060990e-07 4.939010e-07 1 1
#> 4 5.450708e-07 4.549292e-07 1 1
#> 5 5.852223e-07 4.147777e-07 1 1
#> 6 6.256393e-07 3.743607e-07 1 1
#> 7 6.652549e-07 3.347451e-07 1 1
#> 8 7.029699e-07 2.970301e-07 1 1
#> 9 7.378152e-07 2.621848e-07 1 1
#> 10 7.691067e-07 2.308933e-07 1 1
#> 11 7.965304e-07 2.034696e-07 1 1
#> 12 8.201246e-07 1.798754e-07 1 1
#> 13 8.401837e-07 1.598163e-07 1 1
#> 14 8.571374e-07 1.428626e-07 1 1
#> 15 8.714519e-07 1.285481e-07 1 1
#> 16 8.835678e-07 1.164322e-07 1 1
#> 17 8.938712e-07 1.061288e-07 1 1
#> 18 9.026862e-07 9.731379e-08 1 1
#> 19 9.102781e-07 8.972185e-08 1 1
#> 20 9.168617e-07 8.313834e-08 1 1
#> 21 9.226095e-07 7.739053e-08 1 1
#> 22 9.276605e-07 7.233949e-08 1 1
#> 23 9.321268e-07 6.787315e-08 1 1
#> 24 9.360992e-07 6.390076e-08 1 1
#> 25 9.396516e-07 6.034838e-08 1 1
#> 26 9.428446e-07 5.715545e-08 1 1
#> 27 9.457280e-07 5.427201e-08 1 1
#> 28 9.483434e-07 5.165661e-08 1 1
#> 29 9.507253e-07 4.927466e-08 1 1
#> 30 9.529029e-07 4.709707e-08 1 1
#> 31 9.549007e-07 4.509928e-08 1 1
#> 32 9.567396e-07 4.326041e-08 1 1
#> 33 9.584374e-07 4.156261e-08 1 1
#> 34 9.600094e-07 3.999057e-08 1 1
#> 35 9.614689e-07 3.853107e-08 1 1
#> 36 9.628274e-07 3.717263e-08 1 1
#> 37 9.640947e-07 3.590527e-08 1 1
#> 38 9.652797e-07 3.472027e-08 1 1
#> 39 9.663900e-07 3.360996e-08 1 1
#> 40 9.674324e-07 3.256758e-08 1 1
#> 41 9.684128e-07 3.158715e-08 1 1
#> 42 9.693366e-07 3.066339e-08 1 1
#> 43 9.702084e-07 2.979155e-08 1 1
#> 44 9.710326e-07 2.896744e-08 1 1
#> 45 9.718127e-07 2.818727e-08 1 1
#> 46 9.725524e-07 2.744764e-08 1 1
#> 47 9.732545e-07 2.674552e-08 1 1
#> 48 9.739219e-07 2.607813e-08 1 1
#> 49 9.745570e-07 2.544299e-08 1 1
#> 50 9.751622e-07 2.483782e-08 1 1
#> 51 9.803200e-07 1.967996e-08 1 1
#>
#> [[1]]$states[[2]]
#> total Guest measured [M] Signal measured Signal simulated
#> 1 0.0e+00 0.6525932 0.5895924
#> 2 1.0e-07 0.6258308 0.5684414
#> 3 2.0e-07 0.5976011 0.5469778
#> 4 3.0e-07 0.5683364 0.5255474
#> 5 4.0e-07 0.5386060 0.5044895
#> 6 5.0e-07 0.5090762 0.4841061
#> 7 6.0e-07 0.4804428 0.4646402
#> 8 7.0e-07 0.4533454 0.4462645
#> 9 8.0e-07 0.4282865 0.4290826
#> 10 9.0e-07 0.4055805 0.4131363
#> 11 1.0e-06 0.3853446 0.3984188
#> 12 1.1e-06 0.3675292 0.3848883
#> 13 1.2e-06 0.3519687 0.3724798
#> 14 1.3e-06 0.3384343 0.3611151
#> 15 1.4e-06 0.3266753 0.3507105
#> 16 1.5e-06 0.3164472 0.3411820
#> 17 1.6e-06 0.3075263 0.3324483
#> 18 1.7e-06 0.2997164 0.3244331
#> 19 1.8e-06 0.2928491 0.3170660
#> 20 1.9e-06 0.2867826 0.3102828
#> 21 2.0e-06 0.2813977 0.3040257
#> 22 2.1e-06 0.2765953 0.2982428
#> 23 2.2e-06 0.2722924 0.2928875
#> 24 2.3e-06 0.2684201 0.2879186
#> 25 2.4e-06 0.2649204 0.2832991
#> 26 2.5e-06 0.2617448 0.2789962
#> 27 2.6e-06 0.2588524 0.2749807
#> 28 2.7e-06 0.2562084 0.2712266
#> 29 2.8e-06 0.2537834 0.2677106
#> 30 2.9e-06 0.2515523 0.2644120
#> 31 3.0e-06 0.2494933 0.2613122
#> 32 3.1e-06 0.2475880 0.2583947
#> 33 3.2e-06 0.2458201 0.2556444
#> 34 3.3e-06 0.2441758 0.2530481
#> 35 3.4e-06 0.2426428 0.2505936
#> 36 3.5e-06 0.2412104 0.2482700
#> 37 3.6e-06 0.2398692 0.2460675
#> 38 3.7e-06 0.2386109 0.2439772
#> 39 3.8e-06 0.2374283 0.2419908
#> 40 3.9e-06 0.2363148 0.2401012
#> 41 4.0e-06 0.2352647 0.2383016
#> 42 4.1e-06 0.2342726 0.2365858
#> 43 4.2e-06 0.2333342 0.2349484
#> 44 4.3e-06 0.2324450 0.2333841
#> 45 4.4e-06 0.2316015 0.2318882
#> 46 4.5e-06 0.2308002 0.2304565
#> 47 4.6e-06 0.2300382 0.2290851
#> 48 4.7e-06 0.2293125 0.2277702
#> 49 4.8e-06 0.2286206 0.2265084
#> 50 4.9e-06 0.2279604 0.2252968
#> 51 5.0e-06 0.2273297 0.2241324
#> free Dye simulated [M] Host-Dye simulated [M] repetition dataset
#> 1 4.342585e-07 5.657415e-07 1 2
#> 2 4.625420e-07 5.374580e-07 1 2
#> 3 4.912435e-07 5.087565e-07 1 2
#> 4 5.199005e-07 4.800995e-07 1 2
#> 5 5.480595e-07 4.519405e-07 1 2
#> 6 5.753165e-07 4.246835e-07 1 2
#> 7 6.013467e-07 3.986533e-07 1 2
#> 8 6.259188e-07 3.740812e-07 1 2
#> 9 6.488948e-07 3.511052e-07 1 2
#> 10 6.702185e-07 3.297815e-07 1 2
#> 11 6.898989e-07 3.101011e-07 1 2
#> 12 7.079921e-07 2.920079e-07 1 2
#> 13 7.245850e-07 2.754150e-07 1 2
#> 14 7.397821e-07 2.602179e-07 1 2
#> 15 7.536952e-07 2.463048e-07 1 2
#> 16 7.664369e-07 2.335631e-07 1 2
#> 17 7.781157e-07 2.218843e-07 1 2
#> 18 7.888338e-07 2.111662e-07 1 2
#> 19 7.986852e-07 2.013148e-07 1 2
#> 20 8.077558e-07 1.922442e-07 1 2
#> 21 8.161229e-07 1.838771e-07 1 2
#> 22 8.238559e-07 1.761441e-07 1 2
#> 23 8.310170e-07 1.689830e-07 1 2
#> 24 8.376615e-07 1.623385e-07 1 2
#> 25 8.438388e-07 1.561612e-07 1 2
#> 26 8.495927e-07 1.504073e-07 1 2
#> 27 8.549623e-07 1.450377e-07 1 2
#> 28 8.599824e-07 1.400176e-07 1 2
#> 29 8.646840e-07 1.353160e-07 1 2
#> 30 8.690950e-07 1.309050e-07 1 2
#> 31 8.732401e-07 1.267599e-07 1 2
#> 32 8.771415e-07 1.228585e-07 1 2
#> 33 8.808191e-07 1.191809e-07 1 2
#> 34 8.842910e-07 1.157090e-07 1 2
#> 35 8.875732e-07 1.124268e-07 1 2
#> 36 8.906803e-07 1.093197e-07 1 2
#> 37 8.936255e-07 1.063745e-07 1 2
#> 38 8.964208e-07 1.035792e-07 1 2
#> 39 8.990769e-07 1.009231e-07 1 2
#> 40 9.016037e-07 9.839629e-08 1 2
#> 41 9.040102e-07 9.598980e-08 1 2
#> 42 9.063045e-07 9.369546e-08 1 2
#> 43 9.084942e-07 9.150580e-08 1 2
#> 44 9.105860e-07 8.941397e-08 1 2
#> 45 9.125863e-07 8.741371e-08 1 2
#> 46 9.145007e-07 8.549925e-08 1 2
#> 47 9.163347e-07 8.366530e-08 1 2
#> 48 9.180930e-07 8.190699e-08 1 2
#> 49 9.197802e-07 8.021980e-08 1 2
#> 50 9.214004e-07 7.859958e-08 1 2
#> 51 9.229575e-07 7.704250e-08 1 2
#>
#>
#> [[1]]$params
#> [[1]]$params[[1]]
#> Ka(HG) [1/M] I(0) I(HD) [1/M] I(D) [1/M] repetition dataset
#> 1 28947000 0.02704154 1047556 178927.9 1 1
#>
#> [[1]]$params[[2]]
#> Ka(HG) [1/M] I(0) I(HD) [1/M] I(D) [1/M] repetition dataset
#> 1 7837202 1e-15 914340.6 166518.3 1 2
#>
#>
#> [[1]]$metrices
#> [[1]]$metrices[[1]]
#> MeanSquareError RootMeanSquareError MeanAbsoluteError R2 R2 adjusted
#> 1 0.0001776496 0.01332853 0.008385414 0.9974275 0.997375
#> repetition dataset
#> 1 1 1
#>
#> [[1]]$metrices[[2]]
#> MeanSquareError RootMeanSquareError MeanAbsoluteError R2 R2 adjusted
#> 1 0.0004455837 0.02110885 0.01562856 0.9814356 0.9810567
#> repetition dataset
#> 1 1 2
#>
#>
#> [[1]]$lowerBounds
#> Ka(HG) [1/M] I(0) I(HD) [1/M] I(D) [1/M]
#> 1000 0 0 0
#>
#> [[1]]$upperBounds
#> Ka(HG) [1/M] I(0) I(HD) [1/M] I(D) [1/M]
#> 1e+08 1e+02 1e+07 1e+07
#>
#> [[1]]$additionalParameters
#> Host [M] Dye [M] Ka(HD) [1/M]
#> 1e-06 1e-06 3e+06
#>
#> [[1]]$seeds
#> [[1]]$seeds[[1]]
#> [1] 841111
#>
#> [[1]]$seeds[[2]]
#> [1] 731199
#>
#>
#> [[1]]$npop
#> [1] 40
#>
#> [[1]]$ngen
#> [1] 20
#>
#> [[1]]$Topology
#> [1] "random"
#>
#>
#> [[2]]
#> [[2]][[1]]
#>
#> [[2]][[2]]
#>
#>
#> [[3]]
#>
#> [[4]]
#>