create pred_obs_mc method for all the estimators that samples from bel(theta), using the full cov or DLR approximation, and then returns a SNC matrix of predictions on the N test points. Similar to xmap_yhat_sample and xmap_yhat_sample_lofi_dlr, but methods of the estimator class, not buried inside a notebook.
change xmap_yhat_sample_lofi_lin in demos/nonstat-1d-regression to use the predict_obs_cov method.
For the linear plugin approximation , plot +- confidence intervals on each predicted output, rather than drawing independent samples from the marginals p(y_t|xt; mu{t|t-1})..
pred_obs_mc
method for all the estimators that samples from bel(theta), using the full cov or DLR approximation, and then returns a SNC matrix of predictions on the N test points. Similar toxmap_yhat_sample
andxmap_yhat_sample_lofi_dlr
, but methods of the estimator class, not buried inside a notebook.