grofit: S5

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 ~ gompertz(time, A, miu, lambda)
data: parent.frame()
A miu lambda
0.07791557 0.003080715 -6.794163

Measured data (65 lines)

XYZNote
0.00.017
0.250.019
0.50.016
0.750.022
1.00.022
1.250.022
1.50.024
1.750.026
2.00.026
2.250.027
2.50.029
2.750.03
3.00.033
3.250.035
3.50.036
3.750.039
4.00.037
4.250.038
4.50.039
4.750.039
5.00.039
5.250.039
5.50.041
5.750.041
6.00.041
6.250.041
6.50.042
6.750.041
7.00.041
7.250.039
7.50.041
7.750.042
8.00.042
8.250.044
8.50.046
8.750.044
9.00.045
9.250.046
9.50.046
9.750.048
10.00.049
10.250.049
10.50.049
10.750.051
11.00.051
11.250.052
11.50.052
11.750.053
12.00.053
12.250.053
12.50.054
12.750.055
13.00.055
13.250.056
13.50.058
13.750.055
14.00.059
14.250.059
14.50.06
14.750.062
15.00.063
15.250.062
15.50.063
15.750.063
16.00.065
Download table as .csv

Manual Regression Results

Manual regression was not calculated, click here to calculate now

Proxy Models (2)

ModelParamsRMSENote
Gompertz (log y = false): grofitA=0.07791557, λ=-6.794163, μ max.=0.0030807150.00246gotodownload .csv
Gompertz (log y = false): bgfitA=0.07791573300614, λ=-6.79417839729744, μ max.=0.003080709809560.00246gotodownload .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