# Category: Nonlinear time series analysis

Empirical dynamic modeling
Empirical dynamic modeling (EDM) is a framework for analysis and prediction of nonlinear dynamical systems. Applications include population dynamics, ecosystem service, medicine, neuroscience, dynamic
Transfer entropy
Transfer entropy is a non-parametric statistic measuring the amount of directed (time-asymmetric) transfer of information between two random processes. Transfer entropy from a process X to another pro
Autoregressive conditional heteroskedasticity
In econometrics, the autoregressive conditional heteroskedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current error term or innovation as a fun
STAR model
In statistics, Smooth Transition Autoregressive (STAR) models are typically applied to time series data as an extension of autoregressive models, in order to allow for higher degree of flexibility in
Bispectrum
In mathematics, in the area of statistical analysis, the bispectrum is a statistic used to search for nonlinear interactions.
Phase dispersion minimization
Phase dispersion minimization (PDM) is a data analysis technique that searches for periodic components of a time series data set. It is useful for data sets with gaps, non-sinusoidal variations, poor
Surrogate data
Surrogate data, sometimes known as analogous data, usually refers to time series data that is produced using well-defined (linear) models like ARMA processes that reproduce various statistical propert
Surrogate data testing
Surrogate data testing (or the method of surrogate data) is a statistical proof by contradiction technique and similar to permutation tests and as a resampling technique related (but different) to par
Chronological calculus
Chronological calculus is a formalism for the analysis of flows of non-autonomous dynamical systems. It was introduced by and in the late 1970s. The scope of the formalism is to provide suitable tools
False nearest neighbor algorithm
Within abstract algebra, the false nearest neighbor algorithm is an algorithm for estimating the embedding dimension. The concept was proposed by Kennel et al. (1992). The main idea is to examine how
Convergent cross mapping
Convergent cross mapping (CCM) is a statistical test for a cause-and-effect relationship between two variables that, like the Granger causality test, seeks to resolve the problem that correlation does
Nonlinear autoregressive exogenous model
In time series modeling, a nonlinear autoregressive exogenous model (NARX) is a nonlinear autoregressive model which has exogenous inputs. This means that the model relates the current value of a time
Recurrence quantification analysis
Recurrence quantification analysis (RQA) is a method of nonlinear data analysis (cf. chaos theory) for the investigation of dynamical systems. It quantifies the number and duration of recurrences of a