this function gets the cross validation result by specific criteria.
cv.res(ts, c, d, b_time, b_timese, mp_type, ops, r = 1, s = 1, per = 0, k = 0)A data frame containing the criterion values corresponding to "c" and "d". The first element refers to the optimal number of basis for time input, and the second element refers to the optimal number of basis for variate.
ts is the data set which is a time series data typically
the maximum value of number of basis for time input
the maximum value of number of basis for variate input
type of basis for time input
type of basis for variate input
select type of mapping function, "algeb" indicates algebraic mapping on the real line. "logari" represents logarithmic mapping on the real line
Criteria for choosing the number of bases are provided by the package, offering four options: "AIC," "BIC," "CV," and "Kfold," each corresponding to a specific Criteria
indicates number of variate
s is a positive scaling factor, the default is 1
the percentage for test set used in "CV" option
the number of fold used in "Kfold" option