"Charactersitic","Description"
"entropy","Spectral entropy of the time series."
"lumpiness","Lumpiness is based on tiled (non-overlapping) windows." Vvariances are produced for all tiled windows." The lumpiness is the variance of the variances."
"stability","Stability is based on tiled (non-overlapping) windows." Means are produced for all tiled windows." The stability is the variance of the means."
"hurst","Hurst measues the long-term memory of a time series."
"trend","Strength of trend component after decomposition."
"spikiness","Spikeness  is computed as the variance of the leave-one-out variances of the remainder component."
"linearity","Linearity measures the linearity of a time series calculated based on the coefficients of an orthogonal quadratic regression."
"curvature","Curvature measures the curvature of a time series calculated based on the coefficients of an orthogonal quadratic regression."
"e_acf1","E_acf1 is the first auto-correlation coefficent of the remainder component."
"y_acf1","Y_acf1 is the first auto-correlation coefficent of the time series."
"diff1y_acf1","Diff1y_acf1 is the first auto-correlation coefficent of the differenced time series."
"diff2y_acf1","Diff2y_acf1 is the first auto-correlation coefficent of the twiced-differenced time series."
"y_pacf5","Y_pacf5 is the sum of squares of the first 5 partial autocorrelation coefficients of the time series."
"diff1y_pacf5","Diff1y_pacf5 the sum of squares of the first 5 partial autocorrelation coefficients of the differenced time series."
"diff2y_pacf5","Diff2y_pacf5 the sum of squares of the first 5 partial autocorrelation coefficients of the twiced-differenced time series."
"nonlinearity","Nonlinearity is computed using a modification of the statistic used in Teraesvirta's nonlinearity test."
"lmres_acf1","lmres_acf1 is the first auto-correlation coefficent of the resuiduals or a linear model titted to the time series."
"ur_pp","Ur_pp is the statistic for the "Z-alpha" version of PP unit root test with constant trend and lag one."
"ur_kpss","Ur_kpss is a vector comprising the statistic for the KPSS unit root test with linear trend and lag one."
"N","N is the time series length."
"y_acf5","Y_acf5 is the sum of the first ten squared autocorrelation coefficients of the time series." 
"diff1y_acf5","Diff1y_acf5 is the sum of the first ten squared autocorrelation coefficients of the differenced time series." 
"diff2y_acf5","Diff2y_acf5 is the sum of the first ten squared autocorrelation coefficients of the twiced-differenced time series." 
"alpha","Alpha is the smoothing parameter for the level-alpha of the Holt's linear trend method."
"beta","Beta is the smoothing parameter for the trend-beta of the Holt's linear trend method."