cov_joint function

Covariance for joint distribution

cov_joint(cov)

cov_par(cov, horizon = 1, n_var, joint = FALSE)

Arguments

• cov: Array of covariance matrices.
• horizon: Forecast horizon, default is 1.
• n_var: Number of locations.
• joint: Logical; True if cov is the joint covariance matrix.

Returns

The joint covariance matrix for the joint distribution of the current values and the past values for a Markov chain Gaussian field.

Details

The covariance matrix of the joint distribution has the block toeplitz structure. Input cov is assumed to be an array of cross-covariance matrices where the $i$th matrix slice correspond to the $(i-1)$th time lag. For example, cov[, , 1] is the cross-covariance matrix for time lag 0. All matrices in cov are used to construct the joint covariance matrix.

cov_par gives weights and covariance matrix for the current values..