Functions for Benchmarking Time Series Prediction
Adaptive Normalization
Interpolation of unknown values using automatic ARIMA fitting and pred...
Get ARIMA model parameters.
Get ARIMA model parameters
Automatic ARIMA fitting and prediction
Box Cox Transformation
Benchmarking a time series prediction process
data.frames with filled NA's
Detrending Transformation
Differencing Transformation
Differencing Transformation
Automatic empirical mode decomposition
Evaluating prediction/modeling quality
Evaluate method for tspred objects
Prediction/modeling quality evaluation
Automatic ARIMA fitting, prediction and accuracy evaluation
Automatic ARIMA fitting and prediction with Kalman filter
Automatic prediction with empirical mode decomposition
Automatically finding fittest linear model for prediction
Automatic prediction with moving average smoothing
Automatic fitting and prediction of polynomial regression
Automatic fitting and prediction of polynomial regression with Kalman ...
Automatic prediction with wavelet transform
Logarithmic Transformation
MAPE error of prediction
Get parameters of multiple ARIMA models.
Multiple time series automatic ARIMA fitting and prediction
Moving average smoothing
Maximal error of prediction
Minmax Data Normalization
Subset sliding windows of data
Time series modeling and prediction
MSE error of prediction
NMSE error of prediction
Outlier removal from sliding windows of data
Percentage Change Transformation
Plot ARIMA predictions against actual values
Postprocess method for tspred objects
Predict method for modeling objects
Predict method for tspred objects
Time series prediction models
Preprocessing/Postprocessing time series data
Preprocess method for tspred objects
Time series data processing
Prediction/modeling quality metrics
Objects exported from other packages
Generating sliding windows of data
sMAPE error of prediction
Subsetting data into training and testing sets
Generating sliding windows of data
Training a time series model
Train method for tspred objects
Get training and testing subsets of data
Time series transformation methods
Deprecated Functions in Package TSPred
Functions for Benchmarking Time Series Prediction
Time series prediction process
Automatic wavelet transform
Executing a time series prediction process
Functions for defining and conducting a time series prediction process including pre(post)processing, decomposition, modelling, prediction and accuracy assessment. The generated models and its yielded prediction errors can be used for benchmarking other time series prediction methods and for creating a demand for the refinement of such methods. For this purpose, benchmark data from prediction competitions may be used.
Useful links