cv_core {stressor}

Cross Validation Function

Description

This is the machinery to run cross validation. It subsets the test and train set based on the groups it receives.

Usage

cv_core(object, data, t_groups, ...)

Arguments

object

Currently '"reg_sine", "reg_asym", "lm", "mlm_stressor"' objects are accepted.

data

A data.frame object that has the same formula that was fitted on the data.

t_groups

The groups for cross validation: standard cross validation, LOO cross_validation, or spatial cross validation.

...

Additional arguments that are passed to the predict function.

Value

Either a vector of predictions for '"reg_sine", "reg_asym", "lm"' and a data frame for '"mlm_stressor"'.

Examples

 # lm example
 lm_test <- data_gen_lm(20)
 lm <- lm(Y ~ ., lm_test)
 cv(lm, lm_test, n_folds = 2)


 lm_test <- data_gen_lm(20)
 create_virtualenv()
 mlm_lm <- mlm_regressor(Y ~ ., lm_test)
 cv(mlm_lm, lm_test, n_folds = 2)

 # Asymptotic example
 asym_data <- data_gen_asym(10)
 asym_fit <- reg_asym(Y ~ ., asym_data)
 cv(asym_fit, asym_data, n_folds = 2)

 # Sine example
 sine_data <- data_gen_sine(10)
 sine_fit <- reg_sine(Y ~ ., sine_data)
 cv(sine_fit, sine_data, n_folds = 2)