MVcovmatrix: The Complete Covariance Matrix of a Multivariate Data Set

In XiulinXie/SPCmonitor2: Process Control Chart for Monitoring Short-Range Serially Correlated Data

Description

The function MVcovmatrix computes the Complete Covariance Matrix of a multivariate data set x and the covariance or correlation matrix between x(i) and x(i+b). Covariance γ(q) = Cov(Xi,Xi+q) of a Data Set where X is a multivariate data set

Usage

MVcovmatrix(x, bmax = 10)

Arguments

x	data
bmax	γ(q) = Cov(Xi,Xi+q) , the maximun value of q

Details

The input x must be a matrix. MVcovmatrix() computes complete covariance matrix between X(i) and X(i+q),where X(i) and X(i+q) are multivariate process observations obtained at times i and i + q where q =0,1,2.....bmax. Covariance γ(q) = Cov(Xi,Xi+q), where X is a p-dimensinal vector and γ(q) will be a p by p matrix. The default value of bmax is 10, which means the output will be [[γ(0),γ(1),.....γ(10)],.....[γ(i-1),γ(i),.....γ(11-i),...[γ(10),γ(9),.....γ(0)]] where γ(q) = Cov(X(i),X(i+q)) a p by p matrix, so the output will be a 11*p by 11*p matrix.

Value

Multivariate Covariance Matrix M.

Author(s)

Xiulin Xie

Examples

MVcovmatrix(matrix(rnorm(900,0,1),nrow = 3))

XiulinXie/SPCmonitor2 documentation built on Dec. 10, 2019, 12:10 a.m.