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Workspace Method covmat1DMarkov


Create Markov Process Covariance Matrix.

Create a markov process covariance matrix for a retrieval quantity on 
 evenly spaced 1D grid. The correlation between two grid points i,j is 
 is computed as 
 cov(i,j) = sigma[i] * sigma[j] * exp(- d(i,j) / lc)
 where d(i,j) = abs(grid[i] - grid[j]).

This function also sets covmat_inv_block to the analytically computed inverse
of the covariance matrix of the markov provess, which is tri-diagonal. Note
that this requires the retrieval grid to be evenly spaced.

Authors: Simon Pfreundschuh


covmat1DMarkov( out, out_inverse, grid, sigma, lc, co )


GOUTout(Matrix, Sparse)The matrix in which to store the covariance matrix.
GOUTout_inverse(Matrix, Sparse)The matrix in which to store the inverse of the covariance matrix.
GINgrid(Vector)The retrieval grid.
GINsigma(Vector)The vairance for each grid point.
GINlc(Numeric)The correlation length of the Markov process.
GINco(Numeric, Default: 0.0)The cutoff value below which elements will be set to 0.0