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Relevant bibliographies by topics / Threshold Regression Models

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Academic literature on the topic 'Threshold Regression Models'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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Journal articles on the topic "Threshold Regression Models"

1

Hidalgo, Javier, Jungyoon Lee, and Myung Hwan Seo. "Robust inference for threshold regression models." Journal of Econometrics 210, no. 2 (2019): 291–309. http://dx.doi.org/10.1016/j.jeconom.2019.01.008.

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Lee, Sokbae, Myung Hwan Seo, and Youngki Shin. "Testing for Threshold Effects in Regression Models." Journal of the American Statistical Association 106, no. 493 (2011): 220–31. http://dx.doi.org/10.1198/jasa.2011.tm09800.

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Wong, Man-Yu, and Shuanglin Zhang. "Wavelet threshold estimation for additive regression models." Annals of Statistics 31, no. 1 (2003): 152–73. http://dx.doi.org/10.1214/aos/1046294460.

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Fong, Youyi, Chongzhi Di, Ying Huang, and Peter B. Gilbert. "Model-robust inference for continuous threshold regression models." Biometrics 73, no. 2 (2016): 452–62. http://dx.doi.org/10.1111/biom.12623.

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Greb, Friederike, Tatyana Krivobokova, Axel Munk, and Stephan von Cramon-Taubadel. "Regularized Bayesian Estimation of Generalized Threshold Regression Models." Bayesian Analysis 9, no. 1 (2014): 171–96. http://dx.doi.org/10.1214/13-ba850.

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Zhang, Tianyi. "Statistical Estimation in Piecewise Linear Regression Models." Asian Research Journal of Mathematics 21, no. 4 (2025): 39–45. https://doi.org/10.9734/arjom/2025/v21i4909.

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The kink regression model assumes that linear regression forms are separately modelled on two sides of an unknown threshold but still continuous at the threshold. This paper considers statistical estimation for piecewise linear regression models which are widely used in various fields to capture nonlinear relationships between variables. The estimators for the kink locations and regression coefficients are obtained by using the least squares method, a detailed explanation of the estimation process is provided. Furthermore, the proposed methodology is validated through an illustrative example u

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Ngoc Son, Nguyen. "Public debt management and economic growth: A threshold regression approach." Public and Municipal Finance 12, no. 1 (2023): 62–72. http://dx.doi.org/10.21511/pmf.12(1).2023.06.

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This study deals with the impact of national debt on gross domestic product growth, which plays an essential role in economic development when the debt-to-GDP ratio achieves the optimal public debt ratio. The goal of this study is to comprehend the relationship between government debt and GDP growth, which becomes increasingly essential for economic development as the debt-to-GDP ratio approaches the optimal threshold of public debt. The study applied regression threshold models, unit roots, and Pearson correlation tests to the data collected in Vietnam from 2000 to 2020 to determine the optim

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Dimitriadou, Lida, Panagiotis Nastos, Kostas Eleftheratos, John Kapsomenakis, and Christos Zerefos. "Mortality Related to Air Temperature in European Cities, Based on Threshold Regression Models." International Journal of Environmental Research and Public Health 19, no. 7 (2022): 4017. http://dx.doi.org/10.3390/ijerph19074017.

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There is a wealth of scientific literature that scrutinizes the relationship between mortality and temperature. The aim of this paper is to identify the nexus between temperature and three different causes of mortality (i.e., cardiological, respiratory, and cardiorespiratory) for three countries (Scotland, Spain, and Greece) and eleven cities (i.e., Glasgow, Edinburgh, Aberdeen, Dundee, Madrid, Barcelona, Valencia, Seville, Zaragoza, Attica, and Thessaloniki), emphasizing the differences among these cities and comparing them to gain a deeper understanding of the relationship. To quantify the a

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Seo, Myung Hwan, and Oliver Linton. "A smoothed least squares estimator for threshold regression models." Journal of Econometrics 141, no. 2 (2007): 704–35. http://dx.doi.org/10.1016/j.jeconom.2006.11.002.

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FEINAUER, ERIKA, KENDRA M. HALL-KENYON, and KIMBERLEE C. EVERSON. "Rethinking the Linguistic Threshold Hypothesis: Modeling the Linguistic Threshold among young Spanish–English Bilinguals." Bilingualism: Language and Cognition 20, no. 5 (2016): 886–902. http://dx.doi.org/10.1017/s1366728916000626.

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This study uses a discontinuous-linear regression methodological approach to test the Linguistic Threshold Hypothesis (LTH). Specifically, we investigate the following hypotheses: (1) the rate of transfer of literacy skills from L1 to L2 is a function of L2 oral language ability, (2) the rate of transfer from L1 to L2 accelerates when students cross a specified threshold(s) of L2 language oral ability, and (3) discontinuous change-point regression models fit the data better than linear regression interaction models. Across literacy skills, discontinuous change-point regression models revealed

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Dissertations / Theses on the topic "Threshold Regression Models"

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Conroy, Sara A. "A simulation study of bivariate Wiener process models for an observable marker and latent health status." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1452015350.

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Stettler, John. "The Discrete Threshold Regression Model." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1440369876.

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Abreu, Daniel Sebastião. "Threshold effects in the wage Phillips curve." Master's thesis, Instituto Superior de Economia e Gestão, 2018. http://hdl.handle.net/10400.5/16573.

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Mestrado em Econometria Aplicada e Previsão<br>Neste trabalho, avaliamos a capacidade da curva de Phillips salarial Neo-Keynesiana (CPSNK) proposta por Galí (2011) para descrever a inflação dos salários nos EUA durante o período 1965-2018. De forma a estudar esta relação, empregamos um modelo de regressão de limiar que nos permite examinar a existência de não-linearidades. Os nossos resultados sugerem que a taxa de inflação salarial é bem descrita por um modelo de limiar com 3 regimes em que a variável de limiar é a taxa de desemprego. As estimativas para os parâmetros de limiar dividem a CPS

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Liu, Hai. "Semiparametric regression analysis of zero-inflated data." Diss., University of Iowa, 2009. https://ir.uiowa.edu/etd/308.

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Zero-inflated data abound in ecological studies as well as in other scientific and quantitative fields. Nonparametric regression with zero-inflated response may be studied via the zero-inflated generalized additive model (ZIGAM). ZIGAM assumes that the conditional distribution of the response variable belongs to the zero-inflated 1-parameter exponential family which is a probabilistic mixture of the zero atom and the 1-parameter exponential family, where the zero atom accounts for an excess of zeroes in the data. We propose the constrained zero-inflated generalized additive model (COZIGAM) for

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Shrestha, Shivesh. "Development of structural condition thresholds for TSD measurements." Thesis, Virginia Tech, 2017. http://hdl.handle.net/10919/78039.

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This thesis presents (a) results of a field evaluation of the Traffic Speed Deflectometer (TSD) in the United States (b) deflection thresholds to classify the pavement structural condition obtained from the TSD for a small subset of the Pennsylvania secondary road network. The results of the field evaluation included: (1) repeatability of the TSD, (2) ability of the TSD to identify pavement sections with varying structural conditions, and (3) consistency between the structural number (SNeff) calculated from the TSD and SNeff calculated by the Pennsylvania Department of Transportation (PennDOT)

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Koohi, Iraj. "Methods for Non-invasive Trustworthy Estimation of Arterial Blood Pressure." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/35830.

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The trustworthiness of the blood pressure (BP) readings acquired by oscillometric home-based monitoring systems is a challenging issue that requires patients to see the doctor for trusted measurements, especially those who are obese or have cardiovascular diseases such as hypertension or atrial fibrillation. Even with the most accurate monitors one may get different readings if BP is repeatedly measured. Trusted BP readings are those measured with accurate devices at proper measurement conditions. The accurate monitors need an indicator to assure the trustworthiness of the measured BP. In this

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Race, Jonathan Andrew. "Semi-parametric Survival Analysis via Dirichlet Process Mixtures of the First Hitting Time Model." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu157357742741077.

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Higa, Mali Naomi. "Determinação do limiar de anaerobiose pela análise visual gráfica e pelo modelo matemático de regressão linear bi-segmentado de Hinkley em mulheres saudáveis." Universidade de São Paulo, 2006. http://www.teses.usp.br/teses/disponiveis/17/17145/tde-07122006-084132/.

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O limiar de anaerobiose (LA) é definido como a intensidade de exercício físico em que a produção de energia pelo metabolismo aeróbio é suplementada pelo metabolismo anaeróbio. Este índice constitui-se de um delimitador fisiológico de grande importância para o fornecimento de informações concernentes aos principais sistemas biológicos do organismo, os quais estão envolvidos na realização de um exercício físico. O LA é um importante parâmetro de determinação da capacidade aeróbia funcional de um indivíduo. Diversos métodos são usados para estimar o LA durante exercício. Existem métodos invasivos

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Mukhopadhyay, Shraddha. "Comparison of existing ZOI estimation methods with different model specifications and data." Thesis, Högskolan Dalarna, Mikrodataanalys, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34397.

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With the increasing demand and interest in wind power worldwide, it is interesting to study the effects of running windfarms on the activity of reindeers and estimate the associated Zone of Influence (ZOI) relative to these disturbances. Through simulation, Hierarchical Likelihood (HL) and adaptive Lasso methods are used to estimate the ZOI of windfarms and catching the correct threshold at which the negative effect of the disturbances on the reindeer behaviour disappears. The results found some merit to the explanation that the negative effect may not disappear abruptly and more merit to the

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Saei, Ayoub. "Random component threshold models for ordered and discrete response data." Phd thesis, 1996. http://hdl.handle.net/1885/144100.

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Books on the topic "Threshold Regression Models"

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Dueker, Michael. Contemporaneous threshold autoregressive models: Estimation, forecasting, and rational expectations applications. Federal Reserve Bank of St. Louis, 2003.

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Durai, S. Raja Sethu, author, ed. A note on excess money growth and inflation dynamics: Evidence from threshold regression. Madras School of Economics, 2013.

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Book chapters on the topic "Threshold Regression Models"

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He, Xin, and G. A. Whitmore. "Connecting Threshold Regression and Accelerated Failure Time Models." In Risk Assessment and Evaluation of Predictions. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8981-8_3.

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Lee, Mei-Ling Ting, G. A. Whitmore, and Bernard Rosner. "Benefits of Threshold Regression: A Case-Study Comparison with Cox Proportional Hazards Regression." In Mathematical and Statistical Models and Methods in Reliability. Birkhäuser Boston, 2010. http://dx.doi.org/10.1007/978-0-8176-4971-5_28.

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Kardaun, O. J. W. F., and A. Kus. "Generalising Regression and Discriminant Analysis: Catastrophe Models for Plasma Confinement and Threshold Data." In COMPSTAT. Physica-Verlag HD, 1996. http://dx.doi.org/10.1007/978-3-642-46992-3_39.

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Das, Panchanan. "Threshold Regression Model with Panel Data: Investigating Inflation-Growth Relationship in Europe." In Contributions to Economics. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-4902-1_17.

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Liu, Yu, Yan Wang, Jieru Wu, and Shuo Liu. "Research on The Influence of Digital Level on Knowledge Evolution Based on Threshold Regression Model." In 2022 2nd International Conference on Management Science and Software Engineering (ICMSSE 2022). Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-056-5_113.

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Han, Ping, and Tingting He. "Empirical Analysis of Digital Economy Affecting Industrial Chain Modernisation Based on Panel Regression Model and Threshold Effect Model." In Atlantis Highlights in Economics, Business and Management. Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-270-5_55.

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Lam, Max W. Y., and Ho-fung Leung. "Phoenix: A Threshold Function Based Negotiation Strategy Using Gaussian Process Regression and Distance-Based Pareto Frontier Approximation." In Modern Approaches to Agent-based Complex Automated Negotiation. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51563-2_15.

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Liu, Mengzhe, Chenhong Zheng, Minquan Ye, and Shiming Zhang. "Study on the impact of economic development on electricity generation under different carbon price levels based on threshold regression model." In Advances in Energy Materials and Environment Engineering. CRC Press, 2022. http://dx.doi.org/10.1201/9781003332664-48.

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Wang, Zitong. "Digital Inclusive Finance, Advanced Industrial Structure and Quality of Economic Growth—Empirical Evidence Based on Provincial Panel Regressions with Threshold Effect Models." In Learning and Analytics in Intelligent Systems. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-38074-7_7.

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Krishna, Jillella Gopala, and Probir Kumar Ojha. "Artificial Neural Network (ANN) Modeling of Odor Threshold Property of Diverse Chemical Constituents of Black Tea and Coffee." In Research Anthology on Artificial Neural Network Applications. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch018.

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The authors have developed an artificial neural network model using odor threshold (OT) property data for diverse odorant components present in black tea (76 components) and coffee (46 components). The models were validated in terms of both internal and external validation criteria signifying acceptable results. The authors found the significant features controlling the OT property using Mean Absolute Error (MAE)-based criteria in a backward elimination of descriptors, one in each turn. The present results well-corroborated the previously published PLS-regression based chemometric model result

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Conference papers on the topic "Threshold Regression Models"

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Youzwishen, O. O., A. Van Aelst, P. F. Ehlers, and A. Nettel. "A Statistical Risk Model to Predict the Occurrence of SCC." In CORROSION 2004. NACE International, 2004. https://doi.org/10.5006/c2004-04556.

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Abstract Near-neutral stress corrosion cracking (SCC) is an operational integrity problem experienced by pipeline transportation companies since the 1970’s. Pipeline operators have used a number of different methods to predict and locate SCC. Current in-line inspection technology allows for the detection of SCC in pipelines using ultrasonic measurement. However, these tools have size limitations (not available for small diameter pipelines) and can only accurately detect cracks above a certain threshold dimension. To date, predictive models have focused mainly on establishing quantitative relat

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Negri, Francesco, Andrea Galeazzi, Francesco Gallo, and Flavio Manenti. "Enhancing Predictive Maintenance in Used Oil Re-Refining: a Hybrid Machine Learning Approach." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.125404.

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Maintenance is critical for industrial plants to ensure operational reliability and worker safety. In process industries, fouling, the accumulation of solid residues in equipment, poses a significant challenge, causing inefficiencies and productivity losses. Effective modeling of fouling evolution over time is essential for maintenance planning to prevent equipment from operating under suboptimal conditions. Traditional approaches to fouling prediction include equation-based models, which offer high precision but may struggle with continuously changing process boundaries, and machine learning

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Wangensteen, Magnus, Ali Fatemi, Tonni Franke Johansen, and Erlend Magnus Viggen. "Pitting Corrosion Detection by Ultrasound Monitoring." In CONFERENCE 2024. AMPP, 2024. https://doi.org/10.5006/c2024-20810.

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Abstract Early diagnosis is essential for successful mitigation of pitting corrosion, a localized form of corrosion that causes cavities and structural failure in metallic materials. Although ultrasonic inspection techniques are effective in detecting uniform wall thinning, they have challenges in accurately identifying pitting corrosion. The present work proposes a technique for early-stage pitting detection utilizing time-lapse pulse-echo signals. The generation of two-dimensional time-lapse images of ultrasonic reflectivity may be achieved by capturing several ultrasonic traces over a perio

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Abdullah, Lazim, and Nurnadiah Zamri. "Road traffic accidents models using threshold levels of fuzzy linear regression." In 2012 International Conference on Statistics in Science, Business and Engineering (ICSSBE2012). IEEE, 2012. http://dx.doi.org/10.1109/icssbe.2012.6396563.

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Randell, David, Yanyun Wu, Philip Jonathan, and Kevin Ewans. "Modelling Covariate Effects in Extremes of Storm Severity on the Australian North West Shelf." In ASME 2013 32nd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/omae2013-10187.

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Careful modelling of covariate effects is critical to reliable specification of design criteria. We present a spline based methodology to incorporate spatial, directional, temporal and other covariate effects in extreme value models for environmental variables such as storm severity. For storm peak significant wave height events, the approach uses quantile regression to estimate a suitable extremal threshold, a Poisson process model for the rate of occurrence of threshold exceedances, and a generalised Pareto model for size of threshold. Multidimensional covariate effects are incorporated at e

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Randell, David, Elena Zanini, Michael Vogel, Kevin Ewans, and Philip Jonathan. "Omnidirectional Return Values for Storm Severity From Directional Extreme Value Models: The Effect of Physical Environment and Sample Size." In ASME 2014 33rd International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/omae2014-23156.

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Ewans and Jonathan [2008] shows that characteristics of extreme storm severity in the northern North Sea vary with storm direction. Jonathan et al. [2008] demonstrates, when directional effects are present, that omnidirectional return values should be estimated using a directional extreme value model. Omnidirectional return values so calculated are different in general to those estimated using a model which incorrectly assumes stationarity with respect to direction. The extent of directional variability of extreme storm severity depends on a number of physical factors, including fetch variabil

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White, Kathleen D., and Steven F. Daly. "Predicting Ice Jams With Discriminant Function Analysis." In ASME 2002 21st International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/omae2002-28563.

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Breakup ice jam prediction methods are desirable to provide early warning and allow rapid, effective ice jam mitigation due to the suddenness with which breakup jams and related flooding occur. However, prediction models are limited to empirical or stochastic models rather than deterministic models because of the difficulties in using deterministic models to forecast the formation of breakup ice jams. Existing ice jam prediction methods range from empirical single-variable threshold-type analyses to statistical methods such as logistic regression and discriminant function analysis. Empirical m

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Wang, Zheng, Adrian A. Clarke, James R. Moyne, and Dawn M. Tilbury. "Utilizing Intra-Day Prediction Modification Strategies to Improve Peak Power Shaving Using Energy Storage Systems for Smart Buildings." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-5933.

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Peak power shaving is a technique that can be used to reduce monthly electricity bills. As control of Energy Storage Systems (ESS) is based on predicted power demand, power demand forecasting is a necessary component of entire building power optimization. Various forecasting methods have been developed. However, the importance of intra-day prediction error is overlooked by present models. In this paper, a variety of dynamic intra-day model modification strategies utilizing intra-day prediction error are proposed to improve power demand prediction and peak shaving performance. These modificatio

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Tallman, James A., Michal Osusky, Nick Magina, and Evan Sewall. "An Assessment of Machine Learning Techniques for Predicting Turbine Airfoil Component Temperatures, Using FEA Simulations for Training Data." In ASME Turbo Expo 2019: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/gt2019-91004.

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Abstract This paper provides an assessment of three different machine learning techniques for accurately reproducing a distributed temperature prediction of a high-pressure turbine airfoil. A three-dimensional Finite Element Analysis thermal model of a cooled turbine airfoil was solved repeatedly (200 instances) for various operating point settings of the corresponding gas turbine engine. The response surface created by the repeated solutions was fed into three machine learning algorithms and surrogate model representations of the FEA model’s response were generated. The machine learning algor

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Danilov, Georgiana. "The role of ESG factors in shaping firm performance: insights from us healthcare companies." In International scientific conference "Development Through Research and Innovation" IDSC-2025. Academy of Economic Studies, 2025. https://doi.org/10.53486/dri2025.33.

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Corporate finance is continuously evolving, placing increased emphasis on various performance indicators. This research evaluates the financial performance of 60 healthcare companies listed on the S and P 500 index, using data from 2000 to 2024. By employing advanced analytical methods, including linear regression, nonlinear regression, and interaction-effect models, the study investigates the influence of key environmental, social, and governance components on corporate profitability. The findings indicate that total water consumption consistently exhibits a positive correlation with the fina

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Reports on the topic "Threshold Regression Models"

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Shin, Youngki, Myung Hwan Seo, and Sokbae (Simon) Lee. Testing for threshold effects in regression models. Institute for Fiscal Studies, 2010. http://dx.doi.org/10.1920/wp.cem.2010.3610.

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de Luis, Mercedes, Emilio Rodríguez, and Diego Torres. Machine learning applied to active fixed-income portfolio management: a Lasso logit approach. Banco de España, 2023. http://dx.doi.org/10.53479/33560.

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The use of quantitative methods constitutes a standard component of the institutional investors’ portfolio management toolkit. In the last decade, several empirical studies have employed probabilistic or classification models to predict stock market excess returns, model bond ratings and default probabilities, as well as to forecast yield curves. To the authors’ knowledge, little research exists into their application to active fixed-income management. This paper contributes to filling this gap by comparing a machine learning algorithm, the Lasso logit regression, with a passive (buy-and-hold)

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Reyes-Tagle, Gerardo, and Jorge E. Muñoz-Ayala. Debt and Economic Growth: Does Size Matter? Evidence from Dynamic Parametric and Static Non-parametric Approaches. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0004818.

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This paper provides new evidence on the effect of debt on economic growth through two alternative methodological approaches. On the one hand, by using a panel error correction model with a sample of 130 countries between 1980 and 2020, we found evidence of the existence of a range of debt-to-GDP ratios for which economic growth remains positive after debt surges. This threshold may lie between 32 percent and 136 percent, with optimal economic growth achieved at an 84 percent debt-to-GDP ratio for the whole sample of countries. The error correction form for the economic growth was dynamically c

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Dütsch, Matthias, and Ralf Himmelreicher. Characteristics contributing to low- and minimum-wage labour in Germany. Otto-Friedrich-Universität, 2022. http://dx.doi.org/10.20378/irb-54129.

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In this article we examine the characteristics of individuals, companies, and industries involved in low-wage labour in Germany to understand their impact on the risks workers face of earning hourly wages that are below the minimum-wage and low-wage thresholds. To identify these characteristics, we use the Structure of Earnings Survey 2014 (SES). The SES is a mandatory survey of companies which provides information on wages and working hours from about 1 million jobs and nearly 70,000 compa-nies from all industries. This data allows us to present the first systematic analysis of the interactio

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Edeh, Henry C. Assessing the Equity and Redistributive Effects of Taxation Reforms in Nigeria. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/ictd.2021.020.

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Achieving the Sustainable Development Goals (SDGs) of poverty and inequality reduction through redistribution have indeed become critical concerns in many low- and middle-income countries, including Nigeria. Although redistribution results from the effect of tax revenue collections, micro household-level empirical analyses of the distributional effect of personal income tax (PIT) and value added tax (VAT) reforms in Nigeria have been scarcely carried out. This study for the first time quantitatively assessed both the equity and redistributive effects of PIT and VAT across different reform scen

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Turner, Nigel E., Nicolas Trajtenberg, Steve Cook, Olga Sanchez de Ribera, Jing Shi, and Henrietta Bowden-Jones. A health inequality examination of problem gambling, substance abuse, mental health, and poverty in the United Kingdom; A secondary analysis and stakeholder interviews. Greo Evidence Insights, 2023. https://doi.org/10.33684/2024.003.

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Purpose: This project is focused on the social determinants of health associated with problem gambling and examined gambling-related disparities and the determinants of negative health outcomes. Social determinants include social class education, ethnic group, age, and sex (Elton-Marshall, et al., 2017). The main aims of the study were as follows: Aim 1: In this study, we used the large data set to determine subpopulations who are experiencing social inequity (e.g., youth, older adults, women, Black people and other minority ethnic groups, and people with low income; see Elton-Marshall, et al.

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