Ensemble techniques have been used to generate daily numerical weather forecasts since the 1990’s in numerical centers around the world due to the increase of computation ability. One of the main purposes of numerical ensemble forecast tends to assimilate initial uncertainty (both observation and analysis errors) and forecast uncertainty (model errors) by applying either initial perturbation me...

Statistical analysis methods are generally derived under the assumption that forecast errors are strictly random and zero in the mean. If the short-term forecast, used as the background eld in the statistical analysis equation, is in fact biased, so will the resulting analysis be biased. The only way to properly account for bias in a statistical analysis is to do so explicitly, by estimating th...

This paper compares model-based and reduced-form forecasts of financial volatility when high-frequency return data are available. We derived exact formulas for the forecast errors and analyzed the contribution of the “wrong” data modeling and errors in forecast inputs. The comparison is made for “feasible” forecasts, i.e. we assumed that the true data generating process, latent states and param...

The quantification of perfusion using dynamic susceptibility contrast MRI (DSC-MRI) requires deconvolution to obtain the residual impulse response function (IRF). In this work, a method using the Gaussian process for deconvolution (GPD) is proposed. The fact that the IRF is smooth is incorporated as a constraint in the method. The GPD method, which automatically estimates the noise level in eac...

cDNA clones encoding the major subunit of the Duffy blood group were isolated from a human bone marrow cDNA library using a PCR-amplified DNA fragment encoding an internal peptide sequence of glycoprotein D (gpD) protein. The open reading frame of the 1267-bp cDNA clone indicated that gpD protein was composed of 338 amino acids, predicting a M(r) of 35,733, which was the same as a deglycosylate...

Abstract. In this paper, a technique is presented for assessing the predictive uncertainty of rainfall-runoff and hydraulic forecasts. The technique conditions forecast uncertainty on the forecasted value itself, based on retrospective Quantile Regression of hindcasted water level forecasts and forecast errors. To test the robustness of the method, a number of retrospective forecasts for differ...