Time Series Prediction with Integrated Tuning


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Documentation for package ‘tspredit’ version 1.2.747

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adjust_ts_data Adjust 'ts_data'
do_fit Fit Time Series Model
do_predict Predict Time Series Model
fertilizers Fertilizers (Regression)
MSE.ts MSE
R2.ts R2
select_hyper.ts_tune Select Optimal Hyperparameters for Time Series Models
sMAPE.ts sMAPE
tsd Time series example dataset
ts_arima ARIMA
ts_aug_awareness Augmentation by Awareness
ts_aug_awaresmooth Augmentation by Awareness Smooth
ts_aug_flip Augmentation by Flip
ts_aug_jitter Augmentation by Jitter
ts_aug_none No Augmentation
ts_aug_shrink Augmentation by Shrink
ts_aug_stretch Augmentation by Stretch
ts_aug_wormhole Augmentation by Wormhole
ts_data ts_data
ts_elm ELM
ts_fil_ema Exponential Moving Average (EMA)
ts_fil_emd EMD Filter
ts_fil_fft FFT Filter
ts_fil_hp Hodrick-Prescott Filter
ts_fil_kalman Kalman Filter
ts_fil_lowess LOWESS Smoothing
ts_fil_ma Moving Average (MA)
ts_fil_none No Filter
ts_fil_qes Quadratic Exponential Smoothing
ts_fil_recursive Recursive Filter
ts_fil_remd Robust EMD Filter
ts_fil_seas_adj Seasonal Adjustment
ts_fil_ses Simple Exponential Smoothing
ts_fil_smooth Time Series Smooth
ts_fil_spline Smoothing Splines
ts_fil_wavelet Wavelet Filter
ts_fil_winsor Winsorization of Time Series
ts_head Extract the First Observations from a 'ts_data' Object
ts_integtune Time Series Integrated Tune
ts_knn KNN Time Series Prediction
ts_mlp MLP
ts_norm_an Adaptive Normalization
ts_norm_diff First Differences
ts_norm_ean Adaptive Normalization with EMA
ts_norm_gminmax Global Min–Max Normalization
ts_norm_none No Normalization
ts_norm_swminmax Sliding-Window Min–Max Normalization
ts_projection Time Series Projection
ts_reg TSReg
ts_regsw TSRegSW
ts_rf Random Forest
ts_sample Time Series Sample
ts_svm SVM
ts_tune Time Series Tune
[.ts_data Subset Extraction for Time Series Data