STK_EXAMPLE_MISC05 Parameter estimation for heteroscedastic noise variance DESCRIPTION We consider a 1d prediction problem with noisy data, where the variance of the noise depends on the input location. A simple heteroscedastic model is used, where the only parameter to be estimated is a dispersion parameter (the square of a scale parameter). More preciesely, the variance of the noise is assumed to be of the form tau^2(x) = phi * (x + 1) ^ 2, and the dispersion parameter phi is estimated together with the parameters of the covariance function. EXPERIMENTAL FEATURE WARNING This script demonstrates an experimental feature of STK (namely, gaussian noise model objects). STK users that wish to experiment with it are welcome to do so, but should be aware that API-breaking changes are likely to happen in future releases. We invite them to direct any questions, remarks or comments about this experimental feature to the STK mailing list. See also: stk_example_kb09
Package: stk