Man pages for smimodel
Sparse Multiple Index Models for Nonparametric Forecasting
| allpred_index | Constructing index coefficient vectors with all predictors in... |
| augment.backward | Augment function for class 'backward' |
| augment.gaimFit | Augment function for class 'gaimFit' |
| augment.gamFit | Augment function for class 'gamFit' |
| augment.lmFit | Augment function for class 'lmFit' |
| augment.pprFit | Augment function for class 'pprFit' |
| augment.smimodel | Augment function for class 'smimodel' |
| augment.smimodelFit | Augment function for class 'smimodelFit' |
| autoplot.smimodel | Plot estimated smooths from a fitted 'smimodel' |
| avgCoverage | Calculate interval forecast coverage |
| avgWidth | Calculate interval forecast width |
| bb_cvforecast | Single season block bootstrap prediction intervals through... |
| blockBootstrap | Futures through single season block bootstrapping |
| cb_cvforecast | Conformal bootstrap prediction intervals through time series... |
| eliminate | Eliminate a variable and fit a nonparametric additive model |
| forecast.backward | Forecasting using nonparametric additive models with backward... |
| forecast.gaimFit | Forecasting using GAIMs |
| forecast.gamFit | Forecasting using GAMs |
| forecast.pprFit | Forecasting using PPR models |
| forecast.smimodel | Forecasting using SMI models |
| greedy.fit | Greedy search for tuning penalty parameters |
| greedy_smimodel | SMI model estimation through a greedy search for penalty... |
| init_alpha | Initialising index coefficients |
| inner_update | Updating index coefficients and non-linear functions... |
| lag_matrix | Function for adding lags of time series variables |
| loss | Calculating the loss of the MIP used to estimate a SMI model |
| make_smimodelFit | Converting a fitted 'gam' object to a 'smimodelFit' object |
| model_backward | Nonparametric Additive Model with Backward Elimination |
| model_gaim | Groupwise Additive Index Models (GAIM) |
| model_gam | Generalised Additive Models |
| model_lm | Linear Regression models |
| model_ppr | Projection Pursuit Regression (PPR) models |
| model_smimodel | Sparse Multiple Index (SMI) Models |
| new_smimodelFit | Constructor function for the class 'smimodelFit' |
| normalise_alpha | Scaling index coefficient vectors to have unit norm |
| point_measures | Point estimate accuracy measures |
| possibleFutures_benchmark | Possible future sample paths (multi-step) from residuals of a... |
| possibleFutures_smimodel | Possible future sample paths (multi-step) from 'smimodel'... |
| predict.backward | Obtaining forecasts on a test set from a fitted 'backward' |
| predict.gaimFit | Obtaining forecasts on a test set from a fitted 'gaimFit' |
| predict_gam | Obtaining recursive forecasts on a test set from a fitted... |
| predict.gamFit | Obtaining forecasts on a test set from a fitted 'gamFit' |
| predict.lmFit | Obtaining forecasts on a test set from a fitted 'lmFit' |
| predict.pprFit | Obtaining forecasts on a test set from a fitted 'pprFit' |
| predict.smimodel | Obtaining forecasts on a test set from a fitted 'smimodel' |
| predict.smimodelFit | Obtaining forecasts on a test set from a 'smimodelFit' |
| prep_newdata | Prepare a data set for recursive forecasting |
| print.backward | Printing a 'backward' object |
| print.gaimFit | Printing a 'gaimFit' object |
| print.pprFit | Printing a 'pprFit' object |
| print.smimodel | Printing a 'smimodel' object |
| print.smimodelFit | Printing a 'smimodelFit' object |
| randomBlock | Randomly sampling a block |
| reexports | Objects exported from other packages |
| remove_lags | Remove actual values from a data set for recursive... |
| residBootstrap | Generate multiple single season block bootstrap series |
| residuals.smimodel | Extract residuals from a fitted 'smimodel' |
| scaling | Scale data |
| seasonBootstrap | Single season block bootstrap |
| smimodel.fit | SMI model estimation |
| smimodel-package | smimodel: Sparse Multiple Index Models for Nonparametric... |
| split_index | Splitting predictors into multiple indices |
| truncate_vars | Truncating predictors to be in the in-sample range |
| tune_smimodel | SMI model with a given penalty parameter combination |
| unscaling | Unscale a fitted 'smimodel' |
| update_alpha | Updating index coefficients using MIP |
| update_smimodelFit | Updating a 'smimodelFit' |
