Search Results - subject:"Generalized regression"

Review of how the generalized regression estimators contribute to estimating the financial and economic data with missing observations under unequal probability sampling

Lawson, Nuanpan - In: Asian journal of economics and banking : AJEB 8 (2024) 3, pp. 445-459

generalized regression estimators for population total can be applied to financial, economic and other data when missing data are … present. Design/methodology/approach - The generalized regression estimators for estimating population total, including the …/value - The generalized regression estimators can assist in estimating financial and economic data that contain missing values …

Persistent link: https://www.econbiz.de/10015163606

Regional now- and forecasting for data reported with delay: toward surveillance of COVID-19 infections

De Nicola, Giacomo; Schneble, Marc; Kauermann, Göran; … - In: AStA Advances in Statistical Analysis 106 (2022) 3, pp. 407-426

Governments around the world continue to act to contain and mitigate the spread of COVID-19. The rapidly evolving situation compels officials and executives to continuously adapt policies and social distancing measures depending on the current state of the spread of the disease. In this context,...

Persistent link: https://www.econbiz.de/10015327400

Generalized regression neuronal networks to predict the value of numismatic assets: Evidence for the walking liberty half dollar

Alcázar-Blanco, Antonio Carlos; Paule-Vianez, Jessica; … - In: European Research on Management and Business Economics … 27 (2021) 3, pp. 1-8

Generalized Regression Neural Networks has been proposed over a sample 25 coins of the Walking Liberty Half Dollar with several …

Persistent link: https://www.econbiz.de/10014525573

The Use of Data-driven Transformations and Their Applicability in Small Area Estimation

Rojas-Perilla, Natalia - In: WISTA – Wirtschaft und Statistik 73 (2021) 1, pp. 59-66

In general, researchers have been using data transformations as a go-to tool to assist scientific work under the classical and linear mixed regression models instead of developing new theories, applying complex methods or extending software functions. However, transformations are often...

Persistent link: https://www.econbiz.de/10012434941

The use of data-driven transformations and their applicability in small area estimation

Rojas-Perilla, Natalia - In: Wirtschaft und Statistik : WISTA (2021) 1, pp. 59-66

Im Allgemeinen nutzen Forscherinnen und Forscher Daten-Transformationen als Hilfsmittel für die wissenschaftliche Arbeit unter den klassischen und linearen gemischten Regressionsmodellen, anstatt neue Theorien zu entwickeln, komplexe Methoden anzuwenden oder Softwarefunktionen zu erweitern....

Persistent link: https://www.econbiz.de/10012433536

Generalized regression neuronal networks to predict the value of numismatic assets : evidence for the walking liberty half dollar

Alcázar-Blanco, Antonio Carlos; Paule-Vianez, Jessica; … - In: European research on management and business economics 27 (2021) 3, pp. 1-8

Generalized Regression Neural Networks has been proposed over a sample 25 coins of the Walking Liberty Half Dollar with several …

Persistent link: https://www.econbiz.de/10012650575

LINEAR LAYER AND GENERALIZED REGRESSION COMPUTATIONAL INTELLIGENCE MODELS FOR PREDICTING SHELF LIFE OF PROCESSED CHEESE

SUMIT, GOYAL; KUMAR, GOYAL GYANENDRA - In: Russian Journal of Agricultural and Socio-Economic Sciences 3 (2012) 3, pp. 28-32

cheese stored at 7-8oC. Linear Layer and Generalized Regression models were developed with input parameters: Soluble nitrogen … ability of the models. The study revealed that Generalized Regression computational intelligence models are quite effective in …

Persistent link: https://www.econbiz.de/10011222463

Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk

Rockafellar, R.T.; Royset, J.O.; Miranda, S.I. - In: European Journal of Operational Research 234 (2014) 1, pp. 140-154

The paper presents a generalized regression technique centered on a superquantile (also called conditional value …-squares and quantile regression. In contrast to other generalized regression techniques that approximate conditional …

Persistent link: https://www.econbiz.de/10010730182

Modeling Nonlinear Monthly Evapotranspiration Using Soft Computing and Data Reconstruction Techniques

Kim, Sungwon; Singh, Vijay; Seo, Youngmin; Kim, Hung - In: Water Resources Management 28 (2014) 1, pp. 185-206

autocorrelation function, phase space reconstruction, and close returns plot. The generalized regression neural networks and genetic …. The generalized regression neural networks and backpropagation algorithm (GRNN-BP) conjunction model is compared with the …

Persistent link: https://www.econbiz.de/10010997446

Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk

Rockafellar, Ralph Tyrrell; Royst, Johannes O.; … - In: European journal of operational research : EJOR 234 (2014) 1, pp. 140-154

Persistent link: https://www.econbiz.de/10010247347