Search Results - subject:"covariance function"

Patilea, Valentin; Racine, Jeffrey - 2024

Persistent link: https://www.econbiz.de/10014546088

Property analysis of multivariate conditional linear random processes in the problems of mathematical modelling of signals

Fryz, Mykhailo; Mlynko, Bogdana - In: Technology audit and production reserves 3 (2022) 2/65, pp. 29-32

Persistent link: https://www.econbiz.de/10013326596

Gaussian process regression for forecasting gasoline prices in Jordan

Ajlouni, Sameh Asim; Alodat, Moh'd Taleb - In: International Journal of Energy Economics and Policy : IJEEP 11 (2021) 3, pp. 502-509

Persistent link: https://www.econbiz.de/10012622773

New approaches to prediction using functional data analysis

Laha, Arnab Kumar; Rathi, Poonam - 2017

Persistent link: https://www.econbiz.de/10011809757

Are the temperature of Indian cities increasing? : some insights using change point analysis with functional data

Laha, Arnab Kumar; Rathi, Poonam - 2017

Persistent link: https://www.econbiz.de/10011809776

Estimation of low-rank covariance function

Koltchinskii, Vladimir; Lounici, K.; Cybakov, Aleksandr B. - 2016

Persistent link: https://www.econbiz.de/10011855350

Diffusion approximation for efficiency-driven queues when customers are patient

He, Shuangchi - In: Operations research 68 (2020) 4, pp. 1265-1284

Persistent link: https://www.econbiz.de/10012288441

Efficient Approximation of the Spatial Covariance Function for Large Datasets - Analysis of Atmospheric CO2 Concentrations

Gneuss, Patrick; Schmid, Wolfgang; Schwarze, Reimund - Wirtschaftswissenschaftliche Fakultät, … - 2013

reducing the dimension of the problem are required. The present work analyzes approaches to approximate the spatial covariance … function in a real dataset of remotely sensed carbon dioxide concentrations, obtained from the Atmospheric Infrared Sounder of …

Persistent link: https://www.econbiz.de/10011212934

Genomic Prediction for Quantitative Traits: Using Kernel Methods and Whole Genome Sequence Based Approaches ; Genomische Vorhersage für quantitative Merkmale: Verwendung von Kernel-Methoden und Verfahren, die auf vollständigen Genomsequenzen basieren

Ober, Ulrike - 2013

Persistent link: https://www.econbiz.de/10010353233

Prognostics of slow speed bearings using a composite integrated Gaussian process regression model

Aye, Sylvester A.; Heyns, P. Stephan - In: International journal of production research 56 (2018) 14, pp. 4860-4873

Persistent link: https://www.econbiz.de/10011925135