R: Copula-Based Semiparametric Models for Spatio-Temporal Data

# Copula-Based Semiparametric Models for Spatio-Temporal Data

## Documentation for package ‘COST’ version 0.1.0

- DESCRIPTION file

## Help Pages

Data.COST | Data Generation
example.forecast | example for one-step ahead forecast
example.prediction | example for new location prediction
Forecasts.CF | one-step ahead forecast by separate time series analysis
Forecasts.COST.G | one-step ahead forecast by Gaussian copula
Forecasts.COST.t | one-step ahead forecast by t copula
Forecasts.GP | one-step ahead forecast by Gaussian process fitting
location | Locations of 10 sites
logL.CF | negtive log-likelihood for separate time series analysis
logL.COST.G | negtive log-likelihood for Gaussian copula
logL.COST.t | negtive log-likelihood for t copula
logL.GP | negtive log-likelihood of Gaussian process
Predictions.COST.G | new location prediction by Gaussian copula
Predictions.COST.t | new location prediction by t copula
Predictions.GP | new location prediction by Gaussian process method
rank.multivariate | multivariate rank of a vector
Wind6month | Wind speed data from 10 sites