Package: utsf 1.3.4

Univariate time series forecasting (autoregressive models) and recursive forecasts | Recursive forecasts | The utsf package | Prediction intervals | Supported models | Using your own models | Example 1: k-nearest neighbors | Example 2: random forest and neural networks | Setting the parameters of the regression models | Setting the paramaters of a regression model supplied by the user | Example 2: random forest | Estimating forecast accuracy | Parameter tuning | Preprocessings and transformations | Differencing | The additive transformation | The multiplicative transformation | Default parameters | More on using your custom models