List of included code files

Last updated 10 months ago

Here we provide a full list of Matlab code files, organized loosely into broad categories, and with brief descriptions.

The full default set of over 7700 features in hctsa is produced by running all of the code files below, many of which produce a large number of outputs (e.g., some functions fit a time-series model and then output statistics including the parameters of the best-fitting model, measures of the model's goodness of fit, the optimal model order, and autocorrelation statistics on the residuals). In our default feature set, each function is also run with different sets of input parameters, with each parameter set yielding characteristic outputs. For example, different inputs to CO_AutoCorr determine the method in which autocorrelation is computed, as well as the time lag at which autocorrelation is calculated, e.g., lag 1, lag 2, lag 3, etc.; WL_dwtcoeff has inputs that set the mother wavelet to use, and level of wavelet decomposition; FC_LocalSimple has inputs that determine the time-series forecasting method to use and the size of the training window. The set of code files below and their input parameters that define the default hctsa feature set are in the INP_mops.txt file of the hctsa repository.

Distribution

Code summarizing properties of the distribution of values in a time series (disregarding their sequence through time).

Code file

Description

DN_Burstiness

Burstiness statistic of a time series.

DN_CompareKSFit

Fits a distribution to data.

DN_CustomSkewness

Custom skewness measures.

DN_FitKernelSmooth

Statistics of a kernel-smoothed distribution of the data.

DN_Fit_mle

Maximum likelihood distribution fit to data.

DN_HighLowMu

The highlowmu statistic.

DN_HistogramMode

Mode of a data vector.

DN_Mean

A given measure of location of a data vector.

DN_MinMax

The maximum and minimum values of the input data vector

DN_Moments

A moment of the distribution of the input time series.

DN_OutlierInclude

How statistics depend on distributional outliers.

DN_OutlierTest

How distributional statistics depend on distributional outliers.

DN_ProportionValues

Proportion of values in a time-series vector.

DN_Quantile

Quantiles of the distribution of values in the time series data vector.

DN_RemovePoints

How time-series properties change as points are removed.

DN_SimpleFit

Fit distributions or simple time-series models to the data.

DN_Spread

Measure of spread of the input time series.

DN_TrimmedMean

Mean of the trimmed time series using trimmean.

DN_Unique

The proportion of the time series that are unique values.

DN_Withinp

Proportion of data points within p standard deviations of the mean.

DN_cv

Coefficient of variation.

DN_pleft

Distance from the mean at which a given proportion of data are more distant.

EN_DistributionEntropy

Distributional entropy.

HT_DistributionTest

Hypothesis test for distributional fits to a data vector.

Correlation

Code summarizing basic properties of how values of a time series are correlated through time.

Code file

Description

CO_AddNoise

Changes in the automutual information with the addition of noise.

CO_AutoCorr

Compute the autocorrelation of an input time series.

CO_AutoCorrShape

How the autocorrelation function changes with the time lag.

CO_Embed2

Statistics of the time series in a 2-dimensional embedding space.

CO_Embed2_AngleTau

Angle autocorrelation in a 2-dimensional embedding space.

CO_Embed2_Basic

Point density statistics in a 2-d embedding space.

CO_Embed2_Dist

Analyzes distances in a 2-d embedding space of a time series.

CO_Embed2_Shapes

Shape-based statistics in a 2-d embedding space.

CO_FirstMin

Time of first minimum in a given correlation function.

CO_FirstZero

The first zero-crossing of a given autocorrelation function.

CO_NonlinearAutocorr

A custom nonlinear autocorrelation of a time series.

CO_StickAngles

Analysis of line-of-sight angles between time-series data points.

CO_TranslateShape

Statistics on datapoints inside geometric shapes across the time series.

CO_f1ecac

The 1/e correlation length.

CO_fzcglscf

The first zero-crossing of the generalized self-correlation function.

CO_glscf

The generalized linear self-correlation function of a time series.

CO_tc3

Normalized nonlinear autocorrelation function, tc3.

CO_trev

Normalized nonlinear autocorrelation, trev function of a time series.

DK_crinkle

Computes James Theiler's crinkle statistic.

DK_theilerQ

Computes Theiler's Q statistic.

DK_timerev

Time reversal asymmetry statistic.

NL_embed_PCA

Principal Components analysis of a time series in an embedding space.

Automutual information:

CO_RM_AMInformation

Automutual information (Rudy Moddemeijer implementation).

CO_CompareMinAMI

Variability in first minimum of automutual information.

CO_HistogramAMI

The automutual information of the distribution using histograms.

IN_AutoMutualInfoStats

Statistics on automutual information function for a time series.

Entropy and information theory

Entropy and complexity measures for time series

Code file

Description

EN_ApEn

Approximate Entropy of a time series.

EN_CID

Simple complexity measure of a time series.

EN_MS_LZcomplexity

Lempel-Ziv complexity of a n-bit encoding of a time series.

EN_MS_shannon

Approximate Shannon entropy of a time series.

EN_PermEn

Permutation Entropy of a time series.

EN_RM_entropy

Entropy of a time series using Rudy Moddemeijer's code.

EN_Randomize

How time-series properties change with increasing randomization.

EN_SampEn

Sample Entropy of a time series.

EN_mse

Multiscale entropy of a time series.

EN_rpde

Recurrence period density entropy (RPDE).

EN_wentropy

Entropy of time series using wavelets.

Time-series model fitting and forecasting

Fitting time-series models, and doing simple forecasting on time series.

Code file

Description

MF_ARMA_orders

Compares a range of ARMA models fitted to a time series.

MF_AR_arcov

Fits an AR model of a given order, p.

MF_CompareAR

Compares model fits of various orders to a time series.

MF_CompareTestSets

Robustness of test-set goodness of fit.

MF_ExpSmoothing

Exponential smoothing time-series prediction model.

MF_FitSubsegments

Robustness of model parameters across different segments of a time series.

MF_GARCHcompare

Comparison of GARCH time-series models.

MF_GARCHfit

GARCH time-series modeling.

MF_GP_FitAcross

Gaussian Process time-series modeling for local prediction.

MF_GP_LocalPrediction

Gaussian Process time-series model for local prediction.

MF_GP_hyperparameters

Gaussian Process time-series model parameters and goodness of fit.

MF_StateSpaceCompOrder

Change in goodness of fit across different state space models.

MF_StateSpace_n4sid

State space time-series model fitting.

MF_arfit

Statistics of a fitted AR model to a time series.

MF_armax

Statistics on a fitted ARMA model.

MF_hmm_CompareNStates

Hidden Markov Model (HMM) fitting to a time series.

MF_hmm_fit

Fits a Hidden Markov Model to sequential data.

MF_steps_ahead

Goodness of model predictions across prediction lengths.

FC_LocalSimple

Simple local time-series forecasting.

FC_LoopLocalSimple

How simple local forecasting depends on window length.

FC_Surprise

How surprised you would be of the next data point given recent memory.

PP_ModelFit

Investigates whether AR model fit improves with different preprocessings.

Stationarity and step detection

Quantifying how properties of a time series change over time.

Code file

Description

SY_DriftingMean

Mean and variance in local time-series subsegments.

SY_DynWin

How stationarity estimates depend on the number of time-series subsegments.

SY_KPSStest

The KPSS stationarity test.

SY_LocalDistributions

Compares the distribution in consecutive time-series segments.

SY_LocalGlobal

Compares local statistics to global statistics of a time series.

SY_PPtest

Phillips-Peron unit root test.

SY_RangeEvolve

How the time-series range changes across time.

SY_SlidingWindow

Sliding window measures of stationarity.

SY_SpreadRandomLocal

Bootstrap-based stationarity measure.

SY_StatAv

Simple mean-stationarity metric, StatAv.

SY_StdNthDer

Standard deviation of the nth derivative of the time series.

SY_StdNthDerChange

How the output of SY_StdNthDer changes with order parameter.

SY_TISEAN_nstat_z

Cross-forecast errors of zeroth-order time-series models.

SY_VarRatioTest

Variance ratio test for random walk.

Step detection:

CP_ML_StepDetect

Analysis of discrete steps in a time series.

CP_l1pwc_sweep_lambda

Dependence of step detection on regularization parameter.

CP_wavelet_varchg

Variance change points in a time series.

Nonlinear time-series analysis and fractal scaling

Nonlinear time-series analysis methods, including embedding dimensions and fluctuation analysis.

Code file

Description

NL_BoxCorrDim

Correlation dimension of a time series.

NL_DVV

Delay Vector Variance method for real and complex signals.

NL_MS_fnn

False nearest neighbors of a time series.

NL_MS_nlpe

Normalized drop-one-out constant interpolation nonlinear prediction error.

NL_TISEAN_c1

Information dimension.

NL_TISEAN_d2

d2 routine from the TISEAN package.

NL_TISEAN_fnn

False nearest neighbors of a time series.

NL_TSTL_FractalDimensions

Fractal dimension spectrum, D(q), of a time series.

NL_TSTL_GPCorrSum

Correlation sum scaling by Grassberger-Proccacia algorithm.

NL_TSTL_LargestLyap

Largest Lyapunov exponent of a time series.

NL_TSTL_PoincareSection

Poincare sectino analysis of a time series.

NL_TSTL_ReturnTime

Analysis of the histogram of return times.

NL_TSTL_TakensEstimator

Taken's estimator for correlation dimension.

NL_TSTL_acp

acp function in TSTOOL

NL_TSTL_dimensions

Box counting, information, and correlation dimension of a time series.

NL_crptool_fnn

Analyzes the false-nearest neighbors statistic.

SD_SurrogateTest

Analyzes test statistics obtained from surrogate time series.

SD_TSTL_surrogates

Surrogate time-series analysis.

TSTL_delaytime

Optimal delay time using the method of Parlitz and Wichard.

TSTL_localdensity

Local density estimates in the time-delay embedding space.

Fluctuation analysis:

SC_MMA

Physionet implementation of multiscale multifractal analysis

SC_fastdfa

Matlab wrapper for Max Little's ML_fastdfa code

SC_FluctAnal

Implements fluctuation analysis by a variety of methods.

Fourier and wavelet transforms, periodicity measures

Properties of the time-series power spectrum, wavelet spectrum, and other periodicity measures.

Code file

Description

SP_Summaries

Statistics of the power spectrum of a time series.

DT_IsSeasonal

A simple test of seasonality.

PD_PeriodicityWang

Periodicity extraction measure of Wang et al.

WL_DetailCoeffs

Detail coefficients of a wavelet decomposition.

WL_coeffs

Wavelet decomposition of the time series.

WL_cwt

Continuous wavelet transform of a time series.

WL_dwtcoeff

Discrete wavelet transform coefficients.

WL_fBM

Parameters of fractional Gaussian noise/Brownian motion in a time series.

WL_scal2frq

Frequency components in a periodic time series.

Symbolic transformations

Properties of a discrete symbolization of a time series.

Code file

Description

SB_BinaryStats

Statistics on a binary symbolization of the time series.

SB_BinaryStretch

Characterizes stretches of 0/1 in time-series binarization.

SB_MotifThree

Motifs in a coarse-graining of a time series to a 3-letter alphabet.

SB_MotifTwo

Local motifs in a binary symbolization of the time series.

SB_TransitionMatrix

Transition probabilities between different time-series states.

SB_TransitionpAlphabet

How transition probabilities change with alphabet size.

Statistics from biomedical signal processing

Simple time-series properties derived mostly from the heart rate variability (HRV) literature.

Code file

Description

MD_hrv_classic

Classic heart rate variability (HRV) statistics.

MD_pNN

pNNx measures of heart rate variability.

MD_polvar

The POLVARd measure of a time series.

MD_rawHRVmeas

Heart rate variability (HRV) measures of a time series.

Basic statistics, trend

Basic statistics of a time series, including measures of trend.

Code file

Description

SY_Trend

Quantifies various measures of trend in a time series.

ST_FitPolynomial

Goodness of a polynomial fit to a time series.

ST_Length

Length of an input data vector.

ST_LocalExtrema

How local maximums and minimums vary across the time series.

ST_MomentCorr

Correlations between simple statistics in local windows of a time series.

ST_SimpleStats

Basic statistics about an input time series.

Others

Other properties, like extreme values, visibility graphs, physics-based simulations, and dependence on pre-processings applied to a time series.

Code file

Description

EX_MovingThreshold

Moving threshold model for extreme events in a time series.

HT_HypothesisTest

Statistical hypothesis test applied to a time series.

NW_VisibilityGraph

Visibility graph analysis of a time series.

PH_ForcePotential

Couples the values of the time series to a dynamical system.

PH_Walker

Simulates a hypothetical walker moving through the time domain.

PP_Compare

Compare how time-series properties change after pre-processing.

PP_Iterate

How time-series properties change in response to iterative pre-processing.