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Advanced Search Results For "AUTOREGRESSIVE models"

1 - 10 of 8,909 results for
 "AUTOREGRESSIVE models"
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A Bayesian Bivariate Model for Spatially Correlated Binary Outcomes.

Publication Type:Academic Journal

Source(s):Mathematical Problems in Engineering. 8/11/2022, p1-8. 8p.

Abstract:Diseases have been studied separately, but two diseases have inherent dependencies on each other, modelling them separately negates practical reality. The authors' modelling processes are based on univariate separate regressions, which connect each ill...

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Analysis of the Impacts of Health Cost and Risk Preference on Farmers' Protective Behavior of Pesticide Application Based on the Autoregressive Threshold Model: A Case Study of Wuhu City in China.

Publication Type:Academic Journal

Source(s):Journal of Function Spaces. 9/25/2022, p1-9. 9p.

Abstract:This paper is aimed at investigating the impacts of health cost and risk preference on farmers' protective behavior of pesticide in a case study of Wuhu city in China. Based on the field survey data from 523 farmers in the main grain-producing areas, t...

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Empirical Study on the Relationship between Agricultural Economic Structure Growth and Environmental Pollution Based on Time-Varying Parameter Vector Autoregressive Model.

Publication Type:Academic Journal

Source(s):Journal of Environmental & Public Health. 8/10/2022, p1-11. 11p.

Abstract:In order to better demonstrate the relationship between agricultural economic structure growth and environmental pollution, an autoregressive model based on time-varying parameter vector was proposed. In the process of developing the research, this pap...

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THE MEAN REVERTING ORNSTEIN-UHLENBECK PROCESSES WITH NONLINEAR AUTOREGRESSIVE DRIFT TERM INNOVATIONS.

Publication Type:Academic Journal

Source(s):TWMS Journal of Applied & Engineering Mathematics. 2022, Vol. 12 Issue 3, p931-939. 9p.

Abstract:The main purpose of this paper is to present a new approach for energy markets governed by a two-factor Ornstein-Uhlenbeck process with a stochastic nonlinear autoregressive drift term innovation and an unknown diffusion coefficient. This model has int...

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Research on Forest Conversation Analysis Using Autoregressive Neural Network-Based Model.

Publication Type:Academic Journal

Source(s):Computational & Mathematical Methods in Medicine. 6/20/2022, p1-7. 7p.

Abstract:Forest biodiversity is an important component of biological diversity that should not be disregarded. The question of how to evaluate it has sparked scholarly inquiry and discussion. The purpose of this paper is to describe the principles of general li...

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Machine-Learning-Based Road Soft Soil Foundation Treatment and Settlement Prediction Method.

Publication Type:Academic Journal

Source(s):Scientific Programming. 3/10/2022, p1-7. 7p.

Abstract:In order to effectively predict the settlement of soft soil foundation, improve the accuracy of road soft soil foundation settlement prediction, and improve the safety of the project, this paper proposes an optimized SVM-AR model and discusses the appl...

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ARX Models as a Useful Tool to Generate Design Hydrograph with Rainfall.

Publication Type:Academic Journal

Source(s):Hidraulica. Mar2022, Issue 1, p28-38. 11p.

Abstract:ARX-type parametric autoregressive models were used to identify the best fit to precipitation effective data and direct statistical runoff corresponding to a 100 years return period, under assumption that a runoff rain process can be treated as a linea...

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Identification of Denatured Biological Tissues Based on Improved Variational Mode Decomposition and Autoregressive Model during HIFU Treatment.

Publication Type:Academic Journal

Source(s):CMES-Computer Modeling in Engineering & Sciences. 2022, Vol. 130 Issue 3, p1547-1563. 17p.

Abstract:During high-intensity focused ultrasound (HIFU) treatment, the accurate identification of denatured biological tissue is an important practical problem. In this paper, a novel method based on the improved variational mode decomposition (IVMD) and autor...

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A Semiparametric Approach for Modeling Partially Linear Autoregressive Model with Skew Normal Innovations.

Publication Type:Academic Journal

Source(s):Advances in Mathematical Physics. 2/25/2022, p1-17. 17p.

Abstract:The nonlinear autoregressive models under normal innovations are commonly used for nonlinear time series analysis in various fields. However, using this class of models for modeling skewed data leads to unreliable results due to the disability of these...

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Autoregressive Asymmetric Linear Gaussian Hidden Markov Models.

Publication Type:Academic Journal

Source(s):IEEE Transactions on Pattern Analysis & Machine Intelligence. Sep2022, Vol. 44 Issue 9, p4642-4658. 17p.

Abstract:In a real life process evolving over time, the relationship between its relevant variables may change. Therefore, it is advantageous to have different inference models for each state of the process. Asymmetric hidden Markov models fulfil this dynamical...

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