# Category: Multivariate time series

Epps effect
In econometrics and time series analysis, the Epps effect, named after T. W. Epps, is the phenomenon that the empirical correlation between the returns of two different stocks decreases with the lengt
Dynamic time warping
In time series analysis, dynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences, which may vary in speed. For instance, similarities in walking could be det
Bayesian vector autoregression
In statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard VAR models in that the model par
Growth curve (statistics)
The growth curve model in statistics is a specific multivariate linear model, also known as GMANOVA (Generalized Multivariate Analysis-Of-Variance). It generalizes MANOVA by allowing post-matrices, as
Cross-spectrum
In time series analysis, the cross-spectrum is used as part of a frequency domain analysis of the cross-correlation or cross-covariance between two time series.
Variance decomposition of forecast errors
In econometrics and other applications of multivariate time series analysis, a variance decomposition or forecast error variance decomposition (FEVD) is used to aid in the interpretation of a vector a
Multidimensional panel data
In econometrics, a multidimensional panel data is data of a phenomenon observed over three or more dimensions. This comes in contrast with panel data, observed over two dimensions (typically, time and
Panel data
In statistics and econometrics, panel data and longitudinal data are both multi-dimensional data involving measurements over time. Panel data is a subset of longitudinal data where observations are fo
Stationary subspace analysis
Stationary Subspace Analysis (SSA) in statistics is a blind source separation algorithm which factorizes a multivariate time series into stationary and non-stationary components.
Superposed epoch analysis
Superposed epoch analysis (SPE or SEA), also called Chree analysis after a paper by Charles Chree that employed the technique, is a statistical tool used in data analysis either to detect periodicitie
Panel analysis
Panel (data) analysis is a statistical method, widely used in social science, epidemiology, and econometrics to analyze two-dimensional (typically cross sectional and longitudinal) panel data. The dat
Granger causality
The Granger causality test is a statistical hypothesis test for determining whether one time series is useful in forecasting another, first proposed in 1969. Ordinarily, regressions reflect "mere" cor
Vector autoregression
Vector autoregression (VAR) is a statistical model used to capture the relationship between multiple quantities as they change over time. VAR is a type of stochastic process model. VAR models generali
Singular spectrum analysis
In time series analysis, singular spectrum analysis (SSA) is a nonparametric spectral estimation method. It combines elements of classical time series analysis, multivariate statistics, multivariate g