run_loo: Function for running leave one out cross-validation
In PaulRegular/MSP: Multispecies production model incorporating covariance
run_loo R Documentation
Function for running leave one out cross-validation
Description
Function for running leave one out cross-validation
Usage
run_loo(fit, progress = TRUE)
Arguments
fit
Object from fit_model()
progress
Display progress bar? (Generated using the progressr and progress packages)
Value
Returns a list with three objects:
-
preds - log observations that were left out at each step with log predictions, and
-
mse - mean squared error of the predictions (leave one out cross validation score).
PaulRegular/MSP documentation built on Dec. 16, 2024, 1:59 p.m.
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| run_loo | R Documentation |
Function for running leave one out cross-validation
Description
Function for running leave one out cross-validation
Usage
run_loo(fit, progress = TRUE)
Arguments
fit |
Object from |
progress |
Display progress bar? (Generated using the progressr and progress packages) |
Value
Returns a list with three objects:
-
preds- log observations that were left out at each step with log predictions, and -
mse- mean squared error of the predictions (leave one out cross validation score).
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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