| logL.CF {COST} | R Documentation |
negtive log-likelihood for separate time series analysis
Description
negtive log-likelihood for separate time series analysis, copula-based semiparametric method from Chen and Fan (2006), assuming t copula for each time series and Markov process of order one, with marginal distribution estimated by espirical CDF, and it is for correlation parameter estimation
Usage
logL.CF(par,Yk,dfs)
Arguments
par |
correlation parameter in the t copula function, will be obtained by minimizing the negtive log-likelihood |
Yk |
observed data from k-th location |
dfs |
degrees of freedom for the t copula, obtained from COST method with t copula |
Value
the negative log-likelihood
Author(s)
Yanlin Tang and Huixia Judy Wang
References
1.Chen, X. and Fan, Y. (2006). Estimation of copula-based semiparametric time series models. Journal of Econometrics 130, 307–335.\ 2.Yanlin Tang, Huixia Judy Wang, Ying Sun, Amanda Hering. Copula-based semiparametric models for spatio-temporal data.