Man pages for jonlachmann/sparsecoint
Forecasting using sparse cointegration
| calcResiduals | Calculate the residuals |
| checkExo | Check the formatting of exogenous data |
| ciPlot | Create a confidence interval plot for a forecast |
| crossValidate | Run cross validation to determine the optimal lambda value |
| determineRank | Function to determine the cointegration rank using the rank... |
| fit.sparsecoint | Fit a sparsecoint model to data |
| fitted.sparsecoint | Calculate fitted values as single step ahead forecasts |
| ginv | Moore-Penrose pseudoinverse adapted from the package MASS |
| lagNames | Create names for lagged variables for summary |
| matrixQuantiles | Function for calculating the quantiles and mean of many... |
| new_sparsecoint | Create a new model object |
| nts.alpha.procrusted | Function to estimate alpha |
| nts.beta | Function to estimate beta and omega First step: Determine... |
| nts.gamma.lassoreg | Function to estimate gamma, using l1 penalty ### |
| nts.omega | Determine Omega, conditional on alpha,beta and gamma |
| plot.sparsecoint_pred | Plot function for sparsecoint_pred |
| predict.sparsecoint | Predict using a model of class sparsecoint. |
| rankSelectionCriterion | Sparse cointegration function used in determine_rank function... |
| rearrangeYX | Rearrange X and Y to be in the appropriate order for cross... |
| refit.sparsecoint | Refit a sparsecoint model to a new set of data |
| residuals.sparsecoint | Calculate fitted values as single step ahead forecasts |
| restrictLambda | Restrict the lambda sequence: exclude all-zero solutions |
| samples.predict.sparsecoint | Sample many predictions from a sparesecoint model to create... |
| setupData | Set up data for the sparsecoint model by differencing and... |
| shiftLag | Shift lagged data one step by adding a new observation |
| singlestep.sparsecoint | Single step predictions on the diff scale |
| sparsecoint | Create and fit a sparsecoint model |
| SparseCointegration_Lasso | Main function to perform sparse cointegration |
| sparsecoint-package | Forecasting using sparse cointegration |
| summary.sparsecoint | Summary function for sparsecoint models |
