pretty_seq: Set sampling parameters
In NINAnor/oneimpact: Tools for the assessment of the cumulative impacts of anthropogenic features in ecological studies
pretty_seq R Documentation
Set sampling parameters
Description
This function sets the sampling parameters.
Usage
pretty_seq(x, name = "Resample")
Arguments
max_validation_size_blockH0
= 1000,
max_number_blocksH1_train
Default = 10. Maximum number of blocks at level H1,
used for fitting the model. Why do we set a maximum here?
If all blocks should be used, use max_number_blocksH1_train = Inf.
max_fit_size
1000
Value
List of sampling parameters for the spatial stratified cross-validation,
with size of blocks of H0, H1, and H2.
Examples
set_sampling_params(1000, 10, 1000)
NINAnor/oneimpact documentation built on June 14, 2025, 12:27 a.m.
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| pretty_seq | R Documentation |
Set sampling parameters
Description
This function sets the sampling parameters.
Usage
pretty_seq(x, name = "Resample")
Arguments
max_validation_size_blockH0 |
= 1000, |
max_number_blocksH1_train |
Default = 10. Maximum number of blocks at level H1,
used for fitting the model. Why do we set a maximum here?
If all blocks should be used, use |
max_fit_size |
1000 |
Value
List of sampling parameters for the spatial stratified cross-validation, with size of blocks of H0, H1, and H2.
Examples
set_sampling_params(1000, 10, 1000)
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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