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Relevant bibliographies by topics / Nonlinear Autoregressive model / Dissertations / Theses

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Dissertations / Theses on the topic 'Nonlinear Autoregressive model'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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1

Uysal, Ela. "Application Of Nonlinear Unit Root Tests And Threshold Autoregressive Models." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614878/index.pdf.

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Popularity of nonlinear threshold models and unit root tests has increased after the recent empirical studies concerning the effects of business cycles on macroeconomic data. These studies have shown that an economic variable may react differently in response to downturns and recoveries in a business cycle. Inspiring from empirical results, this thesis investigates dynamics of Turkish key macroeconomic data, namely capacity utilization rate, growth of import and export volume indices, growth of gross domestic product, interest rate for cash loans in Turkish Liras and growth of industrial produ

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2

Rech, Gianluigi. "Modelling and forecasting economic time series with single hidden-layer feedforward autoregressive artificial neural networks." Doctoral thesis, Handelshögskolan i Stockholm, Ekonomisk Statistik (ES), 2001. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-591.

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This dissertation consists of 3 essays In the first essay, A Simple Variable Selection Technique for Nonlinear Models, written in cooperation with Timo Teräsvirta and Rolf Tschernig, I propose a variable selection method based on a polynomial expansion of the unknown regression function and an appropriate model selection criterion. The hypothesis of linearity is tested by a Lagrange multiplier test based on this polynomial expansion. If rejected, a kth order general polynomial is used as a base for estimating all submodels by ordinary least squares. The combination of regressors leading to the

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3

Ogbonna, Emmanuel. "A multi-parameter empirical model for mesophilic anaerobic digestion." Thesis, University of Hertfordshire, 2017. http://hdl.handle.net/2299/17467.

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Anaerobic digestion, which is the process by which bacteria breakdown organic matter to produce biogas (renewable energy source) and digestate (biofertiliser) in the absence of oxygen, proves to be the ideal concept not only for sustainable energy provision but also for effective organic waste management. However, the production amount of biogas to keep up with the global demand is limited by the underperformance in the system implementing the AD process. This underperformance is due to the difficulty in obtaining and maintaining the optimal operating parameters/states for anaerobic bacteria t

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4

Dupré, la Tour Tom. "Nonlinear models for neurophysiological time series." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT018/document.

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Dans les séries temporelles neurophysiologiques, on observe de fortes oscillations neuronales, et les outils d'analyse sont donc naturellement centrés sur le filtrage à bande étroite.Puisque cette approche est trop réductrice, nous proposons de nouvelles méthodes pour représenter ces signaux.Nous centrons tout d'abord notre étude sur le couplage phase-amplitude (PAC), dans lequel une bande haute fréquence est modulée en amplitude par la phase d'une oscillation neuronale plus lente.Nous proposons de capturer ce couplage dans un modèle probabiliste appelé modèle autoregressif piloté (DAR). Cette

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5

ALIEV, KHURSHID. "Internet of Things Applications and Artificial Neural Networks in Smart Agriculture." Doctoral thesis, Politecnico di Torino, 2018. http://hdl.handle.net/11583/2697287.

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Internet of Things (IoT) is receiving a great attention due to its potential strength and ability to be integrated into any complex systems and it is becoming a great tool to acquire data from particular environment to the cloud. Data that are acquired from Wireless Sensor Nodes(WSN) could be predicted using Artificial Neural Network(ANN) models. One of the use case fields of IoT is smart agriculture and there are still issues on developing low cost and power efficient WSN using advanced radio technologies for short and long-range applications and implementation of prediction tools. This is th

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6

Dupré, la Tour Tom. "Nonlinear models for neurophysiological time series." Electronic Thesis or Diss., Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLT018.

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Dans les séries temporelles neurophysiologiques, on observe de fortes oscillations neuronales, et les outils d'analyse sont donc naturellement centrés sur le filtrage à bande étroite.Puisque cette approche est trop réductrice, nous proposons de nouvelles méthodes pour représenter ces signaux.Nous centrons tout d'abord notre étude sur le couplage phase-amplitude (PAC), dans lequel une bande haute fréquence est modulée en amplitude par la phase d'une oscillation neuronale plus lente.Nous proposons de capturer ce couplage dans un modèle probabiliste appelé modèle autoregressif piloté (DAR). Cette

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7

Lee, Kian Lam. "Nonlinear time series modelling and prediction using polynomial and radial basis function expansions." Thesis, University of Sheffield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.246940.

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8

Zhou, Jia. "SMOOTH TRANSITION AUTOREGRESSIVE MODELS : A STUDY OF THE INDUSTRIAL PRODUCTION INDEX OF SWEDEN." Thesis, Uppsala University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-126752.

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<p>In this paper, we study the industrial production index of Sweden from Jan, 2000 to latest Feb, 2010. We find out there is a structural break at time point Dec, 2007, when the global financial crisis burst out first in U.S then spread to Europe. To model the industrial production index, one of the business cycle indicators which may behave nonlinear feature suggests utilizing a smooth transition autoregressive (STAR) model. Following the procedures given by Teräsvirta (1994), we carry out the linearity test against the STAR model, determine the delay parameter and choose between the LSTAR m

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9

Katsiampa, Paraskevi. "Nonlinear exponential autoregressive time series models with conditional heteroskedastic errors with applications to economics and finance." Thesis, Loughborough University, 2015. https://dspace.lboro.ac.uk/2134/18432.

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The analysis of time series has long been the subject of interest in different fields. For decades time series were analysed with linear models, which have many advantages. Nevertheless, an issue which has been raised is whether there exist other models that can explain and forecast real data better than linear ones. In this thesis, new nonlinear time series models are suggested, which consist of a nonlinear conditional mean model, such as an ExpAR or an Extended ExpAR, and a nonlinear conditional variance model, such as an ARCH or a GARCH. Since new models are introduced, simulated series of

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10

"Change point estimation for threshold autoregressive (TAR) model." 2012. http://library.cuhk.edu.hk/record=b5549066.

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時間序列之變點鬥檻模型是一種非線性的模型。此論文探討有關該模型之參數估計，同時對其參數估計作出統計分析。我們運用了遺傳式計算機運算來估計這些參數及對其作出研究。我們利用了MDL來對比不同的變點門檻模型，同時我們也利用了MDL來選取對應的變點門檻模型。<br>This article considers the problem of modeling non-linear time series by using piece-wise TAR model. The numbers of change points, the numbers of thresholds and the corresponding order of AR in each piecewise TAR segments are assumed unknown. The goal is to nd out the “best“ combination of the number of change points, the value of threshold in each time segment, and the underlying AR order for each threshold regime. A genetic algorithm is implemented to solve this op

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11

Lin, Gang-Yi, and 林罡亦. "Application of Nonlinear Autoregressive with Exogenous Input Model to Estimate the Linear Modal Parameters of Nonlinear Systems." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/76748314142063084574.

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碩士<br>國立臺灣大學<br>工程科學及海洋工程學研究所<br>97<br>Since the real mechanical systems have nonlinear factors, the only differences are the extent of nonlinearity, so the vibration phenomenon actually are nonlinear. Since the real system has damping, so the oscillation frequency of non-linear system change with amplitude. Thus it’s difficult to estimate the oscillation frequency of a non-linear systems. However, the natural frequency of any system is natural and is not influenced by other factors. This article purposes a set of identification process to estimate the linear modal parameters of nonlinear syst

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12

Shiu-TongJain and 簡旭彤. "Nonlinear Autoregressive Exogenous Model for Wind Power Forecasting and Wind Turbine Health Monitoring." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/djfnc8.

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碩士<br>國立成功大學<br>航空太空工程學系<br>104<br>In the recent years, renewable energy with zero pollution has been emphasized by many countries. Wind energy is wildly used due to its clean and renewable properties. Forecasting the output power of the wind turbine generators is a highly focus topic now. It’s important to the power company and the wind power company of predicting the wind energy precisely, which they applied to reduce cost and raise the quality. However, due to the randomness and the instability characteristics, it’s a great challenge to predict wind power accurately. Moreover, monitoring wi

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13

Wu, Chi-Hsueh, and 吳季學. "Application of Nonlinear Autoregressive with Exogenous Input Model to Estimate the Linear and Nonlinear Characteristic Parameters of Structural Systems." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/09580707115133272663.

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碩士<br>國立臺灣大學<br>工程科學及海洋工程學研究所<br>99<br>During the past decade, although the linear structural system identification had been well developed, the nonlinear response was often taken as noise or neglected throughout the linear system identification procedure. Therefore, in this thesis, using the NARX (Nonlinear AutoRegressive with eXogenous input) model, a nonlinear characteristic parameters identification formula was derived. And combining with state-space system identification theorem, the linear and nonlinear characteristic parameters were estimated successfully. Furthermore, the differences b

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14

Huang, Chung Yi, and 黃仲翊. "Applying Nonlinear Autoregressive with Exogenous Input Model to Predict Chiller Performance of Air - Conditioning System." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/h63h26.

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碩士<br>國立臺北科技大學<br>冷凍空調工程系所<br>105<br>Three methods are applied in this study to predict chiller performance.They are linear regression, backpropagation neural network and nonlinear autoregressive with exogenous input model. The power consumption models of chiller from two cases are established by using these three methods. After that, the simulated results and prediction are compared and the performance of models is improved by using these three methods under the same base. To compare two different cases, we need data accumulation, delete the irrational data, assort data to two

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15

Chen, Li-Yu, and 陳麗玉. "Nonlinear Dynamics between ADRs and the Underlying Stock- An Evaluation of the Smooth Transition Autoregressive Model." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/u4f5we.

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碩士<br>淡江大學<br>財務金融學系碩士在職專班<br>97<br>Abstract： Because of factors such as transaction costs, the prices of ADRs and their underlying shares converge within a non-linear framework. This paper selected the STAR（smooth transition autoregressive）model, proposed by Teräsvirta（1994）to model the convergence. We used the STAR model and a sample of 6 dually listed shares（listed in Taiwan and on the NYSE and NASDAQ）to investigate the convergence between the prices of ADRs and the prices of the Taiwanese-traded shares. These 6 dually listed shares are TSM, UMC, ASX, SPIL, AUO and CHT. We found that the co

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16

Lin, Jang-Ying, and 林瀼縈. "The Nonlinear Relationship Between The Bank Liquidity Risk And Operational Performance-Application of Panel Smooth Transition Autoregressive Model." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/z6z9kd.

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碩士<br>淡江大學<br>財務金融學系碩士班<br>102<br>The 2007 U.S. happened subprime mortgage crisis, coupled with the asset securitization and structured finance products. The financial institutions invest in subprime mortgage–related derivative financial instruments and suffered a shock, loss liquidity. A number of financial institutions went bankrupt, triggering the global financial crisis. To this end, BCBS released “International Framework for Liquidity Risk Measurement, Standards and Monitoring”. BSBC proposed liquidity coverage ratio and net stable funding ratio. This paper used panel smooth transition au

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17

Antwi, Emmanuel. "Modeling and Forecasting Ghana's Inflation Rate Under Threshold Models." Diss., 2017. http://hdl.handle.net/11602/963.

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MSc (Statistics)<br>Department of Statistics<br>Over the years researchers have been modeling inflation rate in Ghana using linear models such as Autoregressive Integrated Moving Average (ARIMA), Autoregressive Moving Average (ARMA) and Moving Average (MA). Empirical research however, has shown that financial data, such as inflation rate, does not follow linear patterns. This study seeks to model and forecast inflation in Ghana using nonlinear models and to establish the existence of nonlinear patterns in the monthly rates of inflation between the period January 1981 to August 2016 as obt

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