exp_cov_function: Exponential covariance function over a grid
In roahd: Robust Analysis of High Dimensional Data

Description Usage Arguments See Also Examples

This function computes the discretization of an exponential covariance function of the form:

C( s, t ) = α e^{ - β | s - t | }

over a 1D grid [t_0, t_1, …, t_{P-1}], thus obtaining the P \times P matrix of values:

C_{i,j} = C( t_i, t_j ) = α e^{ - β | t_i - t_j | } .

1	exp_cov_function(grid, alpha, beta)

`grid`	a vector of time points.
`alpha`	the alpha parameter in the exponential covariance formula.
`beta`	the beta parameter in the exponential covariance formula.

generate_gauss_fdata, generate_gauss_mfdata

grid = seq( 0, 1, length.out = 5e2 )

alpha = 0.2
beta = 0.3

dev.new()
image( exp_cov_function( grid, alpha, beta ),
       main = 'Exponential covariance function',
       xlab = 'grid', ylab = 'grid')