TIMECON

This function selects a time-consecutive data from the original data set as the calibration (training and test) subset, and the remaining data is taken as the evaluation subset.

Providing six different algorithms that can be used to split the
available data into training, test and validation subsets with similar distribution
for hydrological model developments. The dataSplit() function will help you divide
the data according to specific requirements, and you can refer to the par.default()
function to set the parameters for data splitting. The getAUC() function will help
you measure the similarity of distribution features between the data subsets.
For more information about the data splitting algorithms, please refer to:
Chen et al. (2022) <doi:10.1016/j.jhydrol.2022.128340>,
Zheng et al. (2022) <doi:10.1029/2021WR031818>.

Junyi Chen

DSAM

Data Splitting Algorithms for Model Developments

Feifei Zheng

TIMECON function

<dl><dt>data</dt>
<dd>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.</dd>
<dt>control</dt>
<dd>User-defined parameter list, where each parameter definition refers to the <code>par.default</code> function.</dd></dl>

Arguments

'DSAM' - Time-consecutive algorithm — TIMECON

<dl>

<dt>data</dt>
<dd>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.</dd>


<dt>control</dt>
<dd>User-defined parameter list, where each parameter definition refers to the <code>par.default</code> function.</dd>

</dl>

TIMECON: 'DSAM' - Time-consecutive algorithm

Description

Usage

Value

Arguments