STK_PARAM_ESTIM estimates the parameters of a covariance function CALL: PARAM = stk_param_estim (MODEL, XI, YI, PARAM0) CALL: [PARAM, LNV] = stk_param_estim (MODEL, XI, YI, PARAM0) estimates the parameters PARAM of the covariance function in MODEL from the data (XI, YI) using the restricted maximum likelihood (ReML) method. The value PARAM0 is used as a starting point for local optimization. The observations are assumed to be noisy if MODEL.lognoisevariance is not -inf. In this case, the variance of the noise is estimated if MODEL.lognoisevariance is nan, and assumed known otherwise. The estimated log-variance is returned as the second output argument LNV (equal to MODEL.lognoisevariance when it is assumed to be known). CALL: PARAM = stk_param_estim (MODEL, XI, YI) CALL: [PARAM, LNV] = stk_param_estim (MODEL, XI, YI) does the same thing but uses stk_param_init to provide a starting value automatically. CALL: [PARAM, LNV] = stk_param_estim (MODEL, XI, YI, PARAM0, LNV0) additionally provides an initial guess LNV0 for the logarithm of the noise variance. In this case the observations are automatically assumed to be noisy, and the value of MODEL.lognoisevariance is ignored. CALL: PARAM = stk_param_estim (MODEL, XI, YI, PARAM0, [], CRIT) CALL: [PARAM, LNV] = stk_param_estim (MODEL, XI, YI, PARAM0, LNV0, CRIT) uses the estimation criterion CRIT instead of the default ReML criterion. EXAMPLES: see, e.g., stk_example_kb02, stk_example_kb03, stk_example_kb04, stk_example_kb06, stk_example_misc02
Package: stk