Man pages for jbrowell/ProbCast
Flexible Probabilistic Forecasting
| add_calendar_variables | Add Calendar Features |
| contCDF | Continuous CDF from 'MultiQR' object |
| covcor_matrix | Multivariate Gaussian covariance/correlation matrices |
| cv_control | cross validation set-up for model fitting functions |
| exclude_fun | set up exclude index for modelling fitting |
| gamboostLSS_2_MultiQR | Generate predictions from 'gamboostLSS' object |
| gamboostLSS_2_PIT | Probability integral transform for Para_gamboostLSS objects |
| MQR_gbm | Multiple Quantile Regression Using Gradient Boosted Decision... |
| MQR_qreg_gam | DEPRECIATED: Multiple Quantile Regression Using Generalised... |
| MQR_qreg_mboost | Multiple Quantile Regression using 'mboost' (depreciated) |
| Para_gamboostLSS | Fit boosted 'gamlss'-type semi-parametric models... |
| Para_gamlss | Fit 'gamlss'-type semi-parametric models (depreciated) |
| pinball | Pinball Score for 'MultiQR' Objects |
| PIT | Probability integral transform: S3 Generic Method |
| PIT.gamboostLSS | Probability integral transform for Para_gamboostLSS objects |
| PIT.MultiQR | Probability integral transform: S3 Method for for MultiQR |
| PIT.PPD | Probability integral transform: S3 Method for for PPD |
| plot.MultiQR | Fan plot for 'MultiQR' objects |
| PPD_2_MultiQR | Produce a MultiQR object from a Parametric Predictive... |
| ppd_gamboostlss | Fit boosted 'gamlss'-type semi-parametric models |
| ppd_gamlss | Fit 'gamlss'-type semi-parametric models |
| predict.qreg_gam | Predict from model based on Generalised Additive Model and... |
| predict.qreg_gbm | Predict method for Multiple Quantile Regression from Gradient... |
| predict.qreg_lightgbm | Predict method for Multiple Quantile Regression from lightgbm... |
| predict.qreg_mboost | Predict method for Multiple Quantile Regression using... |
| print.qreg_gam | Print 'qreg_gbm' object |
| print.qreg_gbm | Print 'qreg_gbm' object |
| print.qreg_lightgbm | Print 'qreg_lightgbm' object |
| print.qreg_mboost | Print 'qreg_mboost' object |
| qreg_gam | Multiple Quantile Regression Using Generalised Additive... |
| qreg_gam.add_quantiles | Add new qunatile regression models and predictions to... |
| qreg_gam.update | Update a GAM with new training data. |
| qreg_gbm | Multiple Quantile Regression Using Gradient Boosted Decision... |
| qreg_lightgbm | Multiple Quantile Regression Using Gradient Boosted Decision... |
| qreg_mboost | Multiple Quantile Regression using 'mboost' |
| qreg_mrq | Multiple quantile regression, and quantile dressing, using... |
| read_holiday_ics | Load data of UK Holidays |
| reliability | Reliability Diagram for MultiQR |
| rescaleMQR | Re-scale MultiQR object |
| retrain_all | Model retraining: S3 Generic Method |
| retrain_all.qreg_lightgbm | Method for repeated model retraining throughout the Test set,... |
| samps_to_scens | Generate multivariate forecasts |
| sharpness | Sharpness/Interval Width for 'MultiQR' Objects |
| SortQuantiles | Sort multiple quantiles to remove quantile crossing |
| summary.qreg_gam | Summary 'qreg_gbm' object |
| summary.qreg_gbm | Summary 'qreg_gbm' object |
| summary.qreg_lightgbm | Summary 'qreg_lightgbm' object |
| summary.qreg_mboost | Summary 'qreg_mboost' object |
| tails_ev | Extreme value distirbutions for distribution tails |
| update.qreg_lightgbm | Model update (retraining) method for Multiple Quantile... |
