Results 21 to 30 of about 2,044,246 (250)

Relative effects of statistical preprocessing and postprocessing on a regional hydrological ensemble prediction system [PDF]

Hydrology and Earth System Sciences, 2018
The relative roles of statistical weather preprocessing and streamflow postprocessing in hydrological ensemble forecasting at short- to medium-range forecast lead times (day 1–7) are investigated.
S. Sharma, R. Siddique, S. Reed, P. Ahnert, P. Mendoza, A. Mejia   +5 more
doaj   +1 more source

A General Probabilistic Forecasting Framework for Offshore Wind Power Fluctuations

Energies, 2012
Accurate wind power forecasts highly contribute to the integration of wind power into power systems. The focus of the present study is on large-scale offshore wind farms and the complexity of generating accurate probabilistic forecasts of wind power ...
Henrik Madsen, Pierre Pinson, Pierre-Julien Trombe   +2 more
doaj   +1 more source

Generalized Nonlinear Least Squares Method for the Calibration of Complex Computer Code Using a Gaussian Process Surrogate

Entropy, 2020
The approximated nonlinear least squares (ALS) method has been used for the estimation of unknown parameters in the complex computer code which is very time-consuming to execute.
Youngsaeng Lee, Jeong-Soo Park
doaj   +1 more source

Probabilistic modeling of heteroscedastic laboratory experiments using Gaussian process regression [PDF]

, 2018
: This paper proposes an extension to Gaussian process regression (GPR) for data sets composed of only a few replicated specimens and displaying a heteroscedastic behavior.
Charron, Jean-Philippe, Desmettre, Clelia, Lucie Tabor, Clelia Desmettre, Goulet, James Alexandre, James-A. Goulet, Tabor, Lucie, Jean-Philippe Charron   +7 more
core   +1 more source

Skill improvement of dynamical seasonal Arctic sea ice forecasts

Geophysical Research Letters, 2016
We explore the error and improve the skill of the outcome from dynamical seasonal Arctic sea ice reforecasts using different bias correction and ensemble calibration methods. These reforecasts consist of a five‐member ensemble from 1979 to 2012 using the
Folmer Krikken, Maurice Schmeits, Willem Vlot, Virginie Guemas, Wilco Hazeleger   +4 more
doaj   +1 more source

An iterative algorithm of NWTLS-EC for three dimensional-datum transformation with large rotation angle

Geodesy and Geodynamics, 2014
The Gauss-Markov (GM) model and the Errors-in-Variables (EIV) model are frequently used to perform 3D coordinate transformations in geodesy and engineering surveys.
Hu Chuan, Chen Yi
doaj   +1 more source

Letter to the editors

Журнал Белорусского государственного университета: Математика, информатика, 2020
Error in the article "Construction D-optimal designs of experiments for linear multiple regression with heteroscedastic observations"
Valery P. Kirlitsa
doaj  

Forecasting Volatility Spillovers Using Advanced GARCH Models: Empirical Evidence for Developed Stock Markets from Austria and USA [PDF]

Annals of Dunarea de Jos University. Fascicle I : Economics and Applied Informatics
The research study voyage commences with the foundational objective of fitting a suitable Generalized Autoregressive Conditional Heteroscedastic (GARCH) model to assess market volatility, a fundamental pillar of financial analysis.
Bharat Kumar Meher, Puja Kumari, Ramona Birau, Cristi Spulbar, Abhishek Anand, Ion Florescu   +5 more
doaj   +1 more source

Empirical array quality weights in the analysis of microarray data

BMC Bioinformatics, 2006
Background Assessment of array quality is an essential step in the analysis of data from microarray experiments. Once detected, less reliable arrays are typically excluded or "filtered" from further analysis to avoid misleading results.
Holloway Andrew, Dobrovic Alexander, van Laar Ryan, Neilson Jody, Diyagama Dileepa, Ritchie Matthew E, Smyth Gordon K   +6 more
doaj   +1 more source

Robust Hausman Pretest for Panel Data Model in the Presence of Heteroscedasticity and Influential Observations

Journal of Basics and Applied Sciences Research
The classical Hausman pretest (HT) is used to specified the right model between random and fixed effect panel data models. However, in the presence of heteroscedastic error variances and influential observations (IOs) in the data set, it may not correctly identify the right model.
Sani , Muhammad, Suleiman, Shamsuddeen, Isyaku, Mustapha   +2 more
openaire   +2 more sources