STK_EXAMPLE_KB02N  Noisy ordinary kriging in 1D with parameter estimation

 This example shows how to estimate covariance parameters and compute
 ordinary kriging predictions on a one-dimensional noisy dataset.

 The model and data are the same as in stk_example_kb02, but this time the
 parameters of the covariance function and the variance of the noise are
 jointly estimated using the Restricted Maximum Likelihood (ReML) method.

 See also: stk_example_kb01n, stk_example_kb02