Results 21 to 30 of about 22,182 (267)
Application of SARIMA model to forecasting monthly flows in Waterval River, South Africa
Knowledge of future river flow information is fundamental for development and management of a river system. In this study, Waterval River flow was forecasted by SARIMA model using GRETL statistical software. Mean monthly flows from 1960 to 2016 were used
Tadesse Kassahun Birhanu +1 more
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Efficient Estimation in Heteroscedastic Varying Coefficient Models
This paper considers statistical inference for the heteroscedastic varying coefficient model. We propose an efficient estimator for coefficient functions that is more efficient than the conventional local-linear estimator.
Chuanhua Wei, Lijie Wan
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This paper reviews common challenges encountered in statistical analyses of epidemiological data for epidemiologists. We focus on the application of linear regression, multivariate logistic regression, and log-linear modeling to epidemiological data ...
Lihan Yan +4 more
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Modeling the exchange rate of the euro against the dollar using the ARCH/GARCH models [PDF]
The analysis of time series with conditional heteroskedasticity (changeable time variability, conditional variance instability, the phenomenon called volatility) is the main task of ARCH and GARCH models.
Kovačević Radovan
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Fitting functional response surfaces to data: a best practice guide
Describing how resource consumption rates depend on resource density, conventionally termed “functional responses,” is crucial to understanding the population dynamics of trophically interacting organisms.
Wojciech Uszko +2 more
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The purpose of this article was to describe the ability of the quantile regression method in overcoming the violation of classical assumptions. The classical assumptions that are violated in this study are variations of non-homogeneous error or ...
Ferra Yanuar
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Investment Risk Analysis On Bitcoin With Applied of VaR-APARCH Model
Investment can be defined as an activity to postpone consumption at the present time with the aim to obtain maximum profits in the future. However, the greater the benefits, the greater the risk.
Irwan Kasse +3 more
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Massively Scaling Heteroscedastic Classifiers
Accepted to ICLR ...
Mark Collier +5 more
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In this paper, we provide a mathematical and statistical methodology using heteroscedastic estimation to achieve the aim of building a more precise mathematical model for complex financial data.
Chih-Wen Hsiao +3 more
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Comparing Linear Regression to Shrinkage Regression Algorithms (RR, Lasso, El Net) Using PTSD Patients’ Data [PDF]
The purpose of this research was to introduce the alternative model of regression algorithms and having it compared to linear regression. To do this, we need to use modern algorithms such as Ridge, Lasso, and Elastic net regression in which precision is ...
Hojjatollah Farahani
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