grofit: S1

Comparing BGFit with R model and part of grofit experiment

Test estimations with grofit package

Description

Best fit by R - grofit

Nonlinear regression model
model: data ~ richards(time, A, mu, lambda, addpar)
data: parent.frame()
A mu lambda addpar
0.2310 0.0435 6.4402 23.1849

Measured data (65 lines)

XYZNote
0.00.017
0.250.015
0.50.016
0.750.018
1.00.022
1.250.021
1.50.025
1.750.028
2.00.026
2.250.028
2.50.03
2.750.032
3.00.033
3.250.037
3.50.041
3.750.042
4.00.042
4.250.046
4.50.048
4.750.049
5.00.051
5.250.054
5.50.057
5.750.061
6.00.064
6.250.067
6.50.071
6.750.075
7.00.079
7.250.083
7.50.087
7.750.095
8.00.099
8.250.106
8.50.114
8.750.118
9.00.124
9.250.134
9.50.141
9.750.151
10.00.16
10.250.169
10.50.177
10.750.19
11.00.201
11.250.208
11.50.217
11.750.227
12.00.229
12.250.232
12.50.233
12.750.237
13.00.236
13.250.235
13.50.237
13.750.232
14.00.234
14.250.232
14.50.23
14.750.228
15.00.227
15.250.226
15.50.229
15.750.224
16.00.224
Download table as .csv

Manual Regression Results

Equation Space Params
A + Bx log A=-4.09251,B=0.225142

Proxy Models (2)

ModelParamsRMSENote
Richards (log y = false)v=8.78601181779534, miu=0.05033299249904, lambda=6.69728948237046, A=0.214324448433860.00388gotodownload .csv
Richards (log y = false): grofitA=0.2310129794, lambda=6.440225, miu=0.043498997, v=23.18490.00687gotodownload .csv
Click here for the definition of RMSEclick here for more information

Root Mean Square Error (RMSE):

Rmse

For more information: link to Wikipedia articleTrans

Download table as .csv

Model and measurement plots