Vector autoregression (VAR) is a statistical model used to capture the relationship between multiple quantities as they change over time. VAR is a type...

statistics and econometrics, Bayesian vector autoregression (BVAR) uses Bayesian methods to estimate a vector autoregression (VAR) model. BVAR differs with standard...

a vector space as a codomain Vectorization (mathematics), a linear transformation that converts a matrix into a column vector Vector autoregression, an...

The evolution of a k×1 random vector X {\displaystyle \mathbf {X} } through time can be modelled as a vector autoregression (VAR) as follows: X t = c +...

model is a special case of the vector autoregressive model, the computation of the impulse response in vector autoregression#impulse response applies here...

normal distribution to higher dimensions. One definition is that a random vector is said to be k-variate normally distributed if every linear combination...

expectations. A similar test involving more variables can be applied with vector autoregression. The validity of the Granger causality test has been challenged...

mean and the covariance matrix of the random vector X {\displaystyle \textstyle \mathbf {X} } , a vector whose jth element ( j = 1 , … , K ) {\displaystyle...

time series analysis, autoregressive–moving-average model (ARMA), vector autoregression (VAR), non-parametric statistics, ANOVA) Statistical Lab – R-based...

Bayesian statistics Bayesian tool for methylation analysis Bayesian vector autoregression BCMP network – queueing theory Bean machine Behrens–Fisher distribution...

is a vector norm: C = ‖ V − 1 m ‖ = ( m T V − 1 V − 1 m ) 1 / 2 {\displaystyle C=\|V^{-1}m\|=(m^{\mathsf {T}}V^{-1}V^{-1}m)^{1/2}} and the vector m, m...

decomposition (FEVD) is used to aid in the interpretation of a vector autoregression (VAR) model once it has been fitted. The variance decomposition...

average model (ARIMA). With multiple interrelated data series, vector autoregression (VAR) or its extensions are used. In ordinary least squares (OLS)...

equation, with different dependent variables, estimated together. Vector autoregression involves simultaneous regressions of various time series variables...

usually call shocks, and are often modeled in the context of a vector autoregression. Impulses that are often treated as exogenous from a macroeconomic...

{\displaystyle \mathbf {y} \sim f(\mathbf {x} ,{\boldsymbol {\beta }})} relates a vector of independent variables, x {\displaystyle \mathbf {x} } , and its associated...

of causality known as Granger causality can be tested for, and vector autoregression can be performed to examine the intertemporal linkages between the...

known as a vector error correction model (VECM), as it adds error correction features to a multi-factor model known as vector autoregression (VAR). The...

space are a sequence of p {\displaystyle p} unit vectors, where the i {\displaystyle i} -th vector is the direction of a line that best fits the data...

entries of two random vectors X {\displaystyle \mathbf {X} } and Y {\displaystyle \mathbf {Y} } , while the correlations of a random vector X {\displaystyle...

(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) Frequency domain Spectral density estimation Fourier analysis...

(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) Frequency domain Spectral density estimation Fourier analysis...

classification are: Decision trees Random forests Bayesian networks Support vector machines Neural networks Logistic regression Probit model Genetic Programming...

data set X, thought of as a vector x = (x1,…,xn), the dispersion about a point c is the "distance" from x to the constant vector c = (c,…,c) in the p-norm...

(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) Frequency domain Spectral density estimation Fourier analysis...

any random variable assuming values from a vector space, including the real numbers (a one-dimensional vector space) and the integers (which can be considered...

Spacek, Libor. "Rstats - Rust Implementation of Statistical Measures, Vector Algebra, Geometric Median, Data Analysis and Machine Learning". crates.io...

as a scalar or vector β {\displaystyle \beta } . The independent variables, which are observed in data and are often denoted as a vector X i {\displaystyle...

(Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR) Frequency domain Spectral density estimation Fourier analysis...

matrix giving the covariance between each pair of elements of a given random vector. Intuitively, the covariance matrix generalizes the notion of variance to...