Time Series Representations


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Documentation for package ‘TSrepr’ version 1.0.3

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TSrepr-package TSrepr package
clipping Creates bit-level (clipped representation) from a vector
coefComp Functions for linear regression model coefficients extraction
denorm_min_max Min-Max denormalisation
denorm_z Z-score denormalisation
elec_load 2 weeks of electricity load data from 50 consumers.
fast_stat Fast statistic functions (helpers)
l1Coef Functions for linear regression model coefficients extraction
lmCoef Functions for linear regression model coefficients extraction
maape MAAPE
mae MAE
mape MAPE
mase MASE
maxC Fast statistic functions (helpers)
mdae MdAE
meanC Fast statistic functions (helpers)
medianC Fast statistic functions (helpers)
minC Fast statistic functions (helpers)
mse MSE
norm_min_max Min-Max normalisation
norm_min_max_list Min-Max normalization list
norm_z Z-score normalisation
norm_z_list Z-score normalization list
repr_dct DCT representation
repr_dft DFT representation by FFT
repr_dwt DWT representation
repr_exp Exponential smoothing seasonal coefficients as representation
repr_feaclip FeaClip representation of time series
repr_feacliptrend FeaClipTrend representation of time series
repr_featrend FeaTrend representation of time series
repr_gam GAM regression coefficients as representation
repr_lm Regression coefficients from linear model as representation
repr_matrix Computation of matrix of representations from matrix of time series
repr_paa PAA - Piecewise Aggregate Approximation
repr_pip PIP representation
repr_pla PLA representation
repr_sax SAX - Symbolic Aggregate Approximation
repr_seas_profile Mean seasonal profile of time series
repr_sma Simple Moving Average representation
repr_windowing Windowing of time series
rleC RLE (Run Length Encoding) written in C++
rlmCoef Functions for linear regression model coefficients extraction
rmse RMSE
smape sMAPE
sumC Fast statistic functions (helpers)
trending Creates bit-level (trending) representation from a vector
TSrepr TSrepr package