Package: COST 0.1.0
Yanlin Tang
COST: Copula-Based Semiparametric Models for Spatio-Temporal Data
Parameter estimation, one-step ahead forecast and new location prediction methods for spatio-temporal data.
Authors:
COST_0.1.0.tar.gz
COST_0.1.0.tar.gz(r-4.5-noble)COST_0.1.0.tar.gz(r-4.4-noble)
COST_0.1.0.tgz(r-4.4-emscripten)COST_0.1.0.tgz(r-4.3-emscripten)
COST.pdf |COST.html✨
COST/json (API)
| # Install 'COST' in R: |
| install.packages('COST', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- Wind6month - Wind speed data from 10 sites
- location - Locations of 10 sites
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 6 years agofrom:1665b2afd2. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 01 2024 |
| R-4.5-linux | OK | Sep 01 2024 |
Exports:Data.COSTexample.forecastexample.predictionForecasts.CFForecasts.COST.GForecasts.COST.tForecasts.GPlogL.CFlogL.COST.GlogL.COST.tlogL.GPPredictions.COST.GPredictions.COST.tPredictions.GPrank.multivariate
Dependencies:ADGofTestcolorspacecopulagsllatticeMatrixmvtnormnumDerivpcaPPpsplinestabledist
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Data Generation | Data.COST |
| example for one-step ahead forecast | example.forecast |
| example for new location prediction | example.prediction |
| one-step ahead forecast by separate time series analysis | Forecasts.CF |
| one-step ahead forecast by Gaussian copula | Forecasts.COST.G |
| one-step ahead forecast by t copula | Forecasts.COST.t |
| one-step ahead forecast by Gaussian process fitting | Forecasts.GP |
| Locations of 10 sites | location |
| negtive log-likelihood for separate time series analysis | logL.CF |
| negtive log-likelihood for Gaussian copula | logL.COST.G |
| negtive log-likelihood for t copula | logL.COST.t |
| negtive log-likelihood of Gaussian process | logL.GP |
| new location prediction by Gaussian copula | Predictions.COST.G |
| new location prediction by t copula | Predictions.COST.t |
| new location prediction by Gaussian process method | Predictions.GP |
| multivariate rank of a vector | rank.multivariate |
| Wind speed data from 10 sites | Wind6month |