Description Usage Arguments Value
View source: R/cross_validate.R
Obtain predictions of a given test set and the mean absolute errors
1 2 3 4 5 6  cross_validate(time_series, model = "inar", p = 1, h = 1,
training_epoch = NULL, prior = list(a_alpha = NULL, a0 = NULL, b0 =
NULL, tau = NULL, k0 = NULL, a_tau = NULL, b_tau = NULL, a_w = NULL, b_w
= NULL, a_theta = NULL, b_theta = NULL, sigma = NULL, lambda_max = NULL),
burn_in = 10^3, chain_length = 10^4, random_seed = 1761,
verbose = TRUE)

time_series 
A univariate time series. 
h 
Number of steps ahead to be predicted. 
training_epoch 
The last observation of the first training set. 
prior 
List of prior hyperparameters where:

burn_in 
Number of iterations for the "burnin" period which are discarded in the chain. 
chain_length 
Number of iterations of the chain. 
random_seed 
Value of the random seed generator. 
verbose 
If 
A list with the following elements:
Predictions of the test set.
Mean Absolute Error of the test set predictions.
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