MDUPLEX: 'DSAM' - MDUPLEX algorithm
In DSAM: Data Splitting Algorithms for Model Developments
MDUPLEX R Documentation
'DSAM' - MDUPLEX algorithm
Description
This is a modified MDUPLEX algorithm, which is also deterministic, with details given in Zheng et al. (2022).
Usage
MDUPLEX(data, control)
Arguments
data
The dataset should be matrix or Data.frame. The format should be as follows: Column one is a subscript vector used to mark each data point (each row is considered as a data point); Columns from 2 to N-1 are the input data, and Column N are the output data.
control
User-defined parameter list, where each parameter definition refers to the par.default function.
Value
Return the training, test and validation subsets. If the original data are required to be split into two subsets, the training and test subsets can be combined into a single calibration subset.
References
Chen, J., Zheng F., May R., Guo D., Gupta H., and Maier H. R.(2022), Improved data splitting methods for data-driven hydrological model development based on a large number of catchment samples, Journal of Hydrology, 613.
Zheng, F., Chen J., MaierH. R., and Gupta H.(2022), Achieving Robust and Transferable Performance for Conservation‐Based Models of Dynamical Physical Systems, Water Resources Research, 58(5).
DSAM documentation built on May 29, 2024, 3:05 a.m.
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| MDUPLEX | R Documentation |
'DSAM' - MDUPLEX algorithm
Description
This is a modified MDUPLEX algorithm, which is also deterministic, with details given in Zheng et al. (2022).
Usage
MDUPLEX(data, control)
Arguments
data |
The dataset should be matrix or Data.frame. The format should be as follows: Column one is a subscript vector used to mark each data point (each row is considered as a data point); Columns from 2 to N-1 are the input data, and Column N are the output data. |
control |
User-defined parameter list, where each parameter definition refers to the par.default function. |
Value
Return the training, test and validation subsets. If the original data are required to be split into two subsets, the training and test subsets can be combined into a single calibration subset.
References
Chen, J., Zheng F., May R., Guo D., Gupta H., and Maier H. R.(2022), Improved data splitting methods for data-driven hydrological model development based on a large number of catchment samples, Journal of Hydrology, 613.
Zheng, F., Chen J., MaierH. R., and Gupta H.(2022), Achieving Robust and Transferable Performance for Conservation‐Based Models of Dynamical Physical Systems, Water Resources Research, 58(5).
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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