Cookfarm Profiles Regression Task
Source:R/Task_regr_cookfarm_profiles.R
mlr_tasks_cookfarm_mlr3.Rd
The R.J. Cook Agronomy Farm (cookfarm) is a Long-Term Agroecosystem Research Site operated by Washington State University, located near Pullman, Washington, USA. Contains spatio-temporal (3D+T) measurements of three soil properties and a number of spatial and temporal regression covariates.
Here, only the "Profiles" dataset is used from the collection.
The Date
column was appended from the readings
dataset.
In addition coordinates were appended to the task as variables "x"
and "y"
.
The dataset was borrowed and adapted from package GSIF which was on archived on CRAN in 2021-03.
Usage
data(cookfarm_mlr3)
Format
R6::R6Class inheriting from mlr3::TaskRegr.
Column roles
The task has set column roles "space" and "time" for variables "Date"
and
"SOURCEID"
, respectively.
These are used by certain methods during partitioning, e.g.,
mlr_resamplings_sptcv_cstf
with variant "Leave-location-and-time-out".
If only one of space or time should left out, the column roles must be
adjusted by the user!
References
Gasch, C.K., Hengl, T., Gräler, B., Meyer, H., Magney, T., Brown, D.J., 2015. Spatio-temporal interpolation of soil water, temperature, and electrical conductivity in 3D+T: the Cook Agronomy Farm data set. Spatial Statistics, 14, pp.70–90.
Gasch, C.K., D.J. Brown, E.S. Brooks, M. Yourek, M. Poggio, D.R. Cobos, C.S. Campbell, 2016? Retroactive calibration of soil moisture sensors using a two-step, soil-specific correction. Submitted to Vadose Zone Journal.
Gasch, C.K., D.J. Brown, C.S. Campbell, D.R. Cobos, E.S. Brooks, M. Chahal, M. Poggio, 2016? A field-scale sensor network data set for monitoring and modeling the spatial and temporal variation of soil moisture in a dryland agricultural field. Submitted to Water Resources Research.
See also
Dictionary of Tasks: mlr3::mlr_tasks
as.data.table(mlr_tasks)
for a complete table of all (also dynamically created) Tasks.
Other Task:
TaskClassifST
,
TaskRegrST
,
mlr_tasks_diplodia
,
mlr_tasks_ecuador