# exp_cov_function: Exponential covariance function over a grid

### Description

This function computes the discretisation 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 | } .

### Usage

 1 exp_cov_function(grid, alpha, beta) 

### Arguments

 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

### Examples

 1 2 3 4 5 6 7 8 9 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') 

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