Man pages for snarf-snarf/karma
Complementary tools for automated time-series machine learning.
| auto.boxjen | Automated Box-Jenkins method - Improved model selection with... |
| auto.karma | Train ARIMA model for automated univariate time series... |
| cforecastIn | Evaluate autoregressive moving average model (ARMA) model... |
| cforecastOut | Evaluate autoregressive moving average model (ARMA) model... |
| karma.adf | Augmented Dickey-Fuller test for stationarity. |
| karma.ann | ARIMA model optimisation: Improved automatic model selection... |
| karma.boxjenkins | Box-Jenkins method for ARMA model selection on a stationary... |
| karma.cast | Convert "ARIMA" object to "karma.fit" object. |
| karma.cv | Fitted model validation and cross-validation (and related... |
| karma.ensemble | Ensemble learning for time-series: Train an ensemble of weak... |
| karma.fit | Fit ARIMA model to univariate time-series. Mostly a wrapper... |
| karma.forecast | #Forecast and plot future periods: Combine multiple weak... |
| karma.fry | Train multiple time series datasets using multiple algorithms |
| karma.hillclimbing | Combinatorial optimisation local search algorithm (modified... |
| karma.orderbin | Convert fixed order terms to 0/NA mask (needed for function... |
| karma.portmanteau | Portmanteau test to detect statistically significant... |
| karma.rfpermute | Autoregressive Random Forest with random permutations for... |
| karma.transform | Find transformation steps required for stationarity. |
| karma.undiff | Reverse the effect of diff(). |
| karma.validate | Model validation metrics. |
| magic.karma | Train multitude of models on a univariate time series |
| ModelEvaluationFunction | Automated ARIMA model selection according to flexible... |
