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Bibliografias temáticas / Deming regression

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Literatura científica selecionada sobre o tema "Deming regression"

Autor: Grafiati

Publicado: 7 de junho de 2025

Última modificação: 2 de agosto de 2025

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Artigos de revistas sobre o assunto "Deming regression"

1

Adarkwa, Samuel Akwasi, Frank Kofi Owusu, and Samuel Okyere. "Impact of Using Double Positive Samples in Deming Regression." International Journal of Mathematics and Mathematical Sciences 2022 (August 12, 2022): 1–8. http://dx.doi.org/10.1155/2022/3984857.

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In the method comparison approach, two measurement errors are observed. The classical regression approach (linear regression) method cannot be used for the analysis because the method may yield biased and inefficient estimates. In view of that, the Deming regression is preferred over the classical regression. The focus of this work is to assess the impact of censored data on the traditional regression, which deletes the censored observations compared to an adapted version of the Deming regression that takes into account the censored data. The study was done based on simulation studies with NLM

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Dhanoa, M. S., and R. Sanderson. "Comment on “The structural relationship: regression in biology”." Canadian Journal of Zoology 88, no. 8 (2010): 821–23. http://dx.doi.org/10.1139/z10-050.

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Supplementary information relevant to structural relationship regression in biology as discussed by McArdle (1988; Can. J. Zool. 66(11): 2329–2339) is presented. Although McArdle presented both linear and multiple linear regression models, we limit our comment to the linear model only. McArdle’s eq. 2 is corrected. Deming’s alternative form of the maximum likelihood (ML) solution (Deming 1943; Statistical adjustment of data. John Wiley and Sons, Inc., New York) is introduced. In the ML solution, the ratio of the mean measurement variances of the y and x variables is assumed constant over the r

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Bazilevskiy, Mikhail. "ANALYTICAL DEPENDENCES FOR SOME ADEQUACY CRITERIA OF DEMING REGRESSION MODEL." Proceedings of Irkutsk State Technical University 117, no. 10 (2016): 81–89. http://dx.doi.org/10.21285/1814-3520-2016-10-81-89.

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Martin, Robert F. "General Deming Regression for Estimating Systematic Bias and Its Confidence Interval in Method-Comparison Studies." Clinical Chemistry 46, no. 1 (2000): 100–104. http://dx.doi.org/10.1093/clinchem/46.1.100.

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Abstract Background: Various forms of least-squares regression analyses are used to estimate average systematic error (bias) and its confidence interval in method-comparison studies. When assumptions that underlie a particular regression method are inappropriate for the data, errors in estimated statistics result. In this report, I present an improved method for regression analysis that is free from the usual simplifying assumptions and is generally applicable to linearly related method-comparison data. Methods: Theoretical equations based on the Deming approach, further developed by physicist

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Linnet, Kristian. "Performance of Deming regression analysis in case of misspecified analytical error ratio in method comparison studies." Clinical Chemistry 44, no. 5 (1998): 1024–31. http://dx.doi.org/10.1093/clinchem/44.5.1024.

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Abstract Application of Deming regression analysis to interpret method comparison data presupposes specification of the squared analytical error ratio (λ), but in cases involving only single measurements by each method, this ratio may be unknown and is often assigned a default value of one. On the basis of simulations, this practice was evaluated in situations with real error ratios deviating from one. Comparisons of two electrolyte methods and two glucose methods were simulated. In the first case, misspecification of λ produced a bias that amounted to two-thirds of the maximum bias of the ord

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Zrikem, Hind, Soumia Nachate, Ibtissam Mhirig, Saliha Chellak, and Abderrahman Boukhira. "Serum creatinine and urea assays on Atellica® CH and Architect® ci4100: method comparison." European Journal of Biological Research 13, no. 1 (2023): 1–9. https://doi.org/10.5281/zenodo.7542158.

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Serum creatinine and urea are markers of renal function usually measured in conjunction. This study aims to evaluate the comparability of a new analyzer incorporated to our laboratory, Atellica® with the established analyzer, Architect ® ci 4100 in serum creatinine and urea assays. We ran 110 tests for creatinine and 107 for urea. In both analyzers, serum creatinine assay is based on the Jaffe reaction while urea measurement is based on the Roch-Ramel enzymatic reaction. Linear association between methods was evaluated using Pearson's correlation coefficient. Methods comparability

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Yeo, Chin-Pin, Carol Hui-Chen Tan, and Edward Jacob. "Haemoglobin A1c: evaluation of a new HbA1c point-of-care analyser Bio-Rad in2it in comparison with the DCA 2000 and central laboratory analysers." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 46, no. 5 (2009): 373–76. http://dx.doi.org/10.1258/acb.2009.009008.

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Background Point-of-care-testing (POCT) of haemoglobin Alc (HbA1c) is popular due to its fast turnaround of results in the outpatient setting. The aim of this project was to evaluate the performance of a new HbA1c POCT analyser, the Bio-Rad in2it, and compare it with the Siemens DCA 2000, Bio-Rad Variant II and Roche Tina-quant HbA1c Gen 2 assay on the cobas c501. Methods Imprecision of the four methods were compared by computing total imprecision from within-run and between-run data. A total of 80 samples were also compared and analysed by Deming regression and Altman–Bland difference test. R

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Mercader, Josep V., Antonio Abad-Fuentes, Consuelo Agulló, Antonio Abad-Somovilla, and Francesc A. Esteve-Turrillas. "Development of a sensitive and specific enzyme-linked immunosorbent assay for the determination of fludioxonil residues in fruit juices." Anal. Methods 6, no. 22 (2014): 8924–29. http://dx.doi.org/10.1039/c4ay01756k.

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The generation and performance of the first-ever described monoclonal antibodies to fludioxonil are herein reported, and a competitive immunoassay was developed and validated for residue analysis in fruit juices by comparison with GC-MS using Deming regression and Bland–Altman analyses.

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Payne, R. B. "Method Comparison: Evaluation of Least Squares, Deming and Passing/Bablok Regression Procedures Using Computer Simulation." Annals of Clinical Biochemistry: International Journal of Laboratory Medicine 34, no. 3 (1997): 319–20. http://dx.doi.org/10.1177/000456329703400317.

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Bazilevskiy, Mikhail P. "Multi-criteria approach to pair-multiple linear regression models constructing." Izvestiya of Saratov University. New Series. Series: Mathematics. Mechanics. Informatics 21, no. 1 (2021): 88–99. http://dx.doi.org/10.18500/1816-9791-2021-21-1-88-99.

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A pair-multiple linear regression model which is a synthesis of Deming regression and multiple linear regression model is considered. It is shown that with a change in the type of minimized distance, the pair-multiple regression model transforms smoothly from the pair model into the multiple linear regression model. In this case, pair-multiple regression models retain the ability to interpret the coefficients and predict the values of the explained variable. An aggregated quality criterion of regression models based on four well-known indicators: the coefficient of determination, Darbin – Wats

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Mais fontes

Teses / dissertações sobre o assunto "Deming regression"

1

Kim, Young Suk Sohn So Young. "Regression analysis of demand for U.S. military labor." Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from the National Technical Information Service, 1991. http://handle.dtic.mil/100.2/ADA245760.

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Kim, Young Suk. "Regression analysis of demand for U.S. military labor." Thesis, Monterey, California. Naval Postgraduate School, 1991. http://hdl.handle.net/10945/43743.

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Approved for public release; distribution is unlimited<br>The past year has been one of unprecedented change for the U.S. military organization. It would be of interest to analyze the impact of the changing situation on U.S. military labor demand. In this thesis, several demand models for U.S. military labor are considered to identify influential factors that predict the size of future military labor. A stepwise regression analysis is used to select some significant demand models. Data used to construct demand models in this thesis over the period of 1963-1986 while actual data (1987-1990) are

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AndrÃ, Diego de Maria. "Space and economic determinants of demand for residential water in fortaleza, cearÃ." Universidade Federal do CearÃ, 2012. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=7425.

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nÃo hÃ<br>This paper aims to estimate a residential water demand function for the city of Fortaleza (CearÃ), considering the potential impact of the spatial effects on water consumption. The analysis is developed from the investigation of presence of spatial autocorrelation in residential water consumption. For this, the tools of exploratory spatial data analysis (ESDA) were utilized. Subsequently, specific tests are performed to determine the sources of spatial autocorrelation, i.e., if the autocorrelation is caused by the spatial distribution of water consumption or by effects not modeled. I

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Lindner, Anabele. "Análise desagregada de dados de demanda por transportes através de modelagem geoestatística e tradicional." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/18/18144/tde-09042015-090539/.

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O conhecimento do padrão de deslocamento populacional bem como a estimativa de demanda por transportes são de fundamental importância para a tomada de decisões relativas ao planejamento urbano e de transportes. Em geral, a obtenção destas informações é realizada por modelos tradicionais como o modelo quatro etapas. Entretanto, modelos clássicos não levam em conta a dependência espacial das variáveis . A Geoestatística, valendo-se da utilização de variáveis regionalizadas, apresenta-se como uma ferramenta auxiliar capaz de modelar informaçõe

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Moreira, Sara Patricia Ferreira. "Double Coverage and Health Care Demand: Evidence from Quantile Regression." Master's thesis, Instituto Superior de Economia e Gestão, 2009. http://hdl.handle.net/10400.5/3334.

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Mestrado em Econometria Aplicada e Previsão<br>This paper examines the impact of double health insurance coverage on the demand for health care services, focusing on the effect of special public and private protection schemes (designated as health subsystems) beyond the statutory National Health Service Data from the last Portuguese Health Survey is used to estimate the effects of double insurance on the consumption of doctor visits. The novelty of this work is that within the context of count data modelling, the analysis is made for the whole distribution, not only for the location of the con

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Tong, Fan. "Capacity demand and climate in Ekerö : Development of tool to predict capacity demand underuncertainty of climate effects." Thesis, KTH, Elektroteknisk teori och konstruktion, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-152522.

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The load forecasting has become an important role in the operation of power system, and several models by using different techniques have been applied to solve these problems. In the literature, the linear regression models are considered as a traditional approach to predict power consumption, and more recently, the artificial neural network (ANN) models have received more attention for a great number of successful and practical applications. This report introduces both linear regression and ANN models to predict the power consumption for Fortum in Ekerö. The characteristics of power consumpti

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Pattiz, Brian. "Count regression models for recreation demand: an application to Clear Lake /." [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1473245.

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Alsalous, Osama. "Global Demand Forecast Model." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/78331.

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Air transportation demand forecasting is a core element in aviation planning and policy decision making. NASA Langley Research Center addressed the need of a global forecast model to be integrated into the Transportation Systems Analysis Model (TSAM) to fulfil the vision of the Aeronautics Research Mission Directorate (ARMD) at NASA Headquarters to develop a picture of future demand worldwide. Future forecasts can be performed using a range of techniques depending on the data available and the scope of the forecast. Causal models are widely used as a forecasting tool by looking for relationshi

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Dheeriya, P. L. (Prakash Lachmandas). "A Comparison of Money Demand in Four Industrialized Countries Using Seemingly Unrelated Regressions." Thesis, North Texas State University, 1987. https://digital.library.unt.edu/ark:/67531/metadc330950/.

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In this study, the possibility that money demand of one country might be affected by macroeconomic activities of other countries is investigated. We use the seemingly unrelated regression (SUR) technique, which takes into account all covariances between residuals of country-specific money demand equations. Efficiency of estimates using the SUR technique is enhanced because it uses information contained in the contemporaneous correlation of the error terms. The hypothesis of economic interdependence is tested. A proxy for foreign influence, deviation from interest rate parity (DIRP), is tested

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10

Mougeot, Sylvie R. (Sylvie Renee) Carleton University Dissertation Management Studies. "Demand for Canadian bank notes by denomination; a combined share/ regression approach." Ottawa, 1997.

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Mais fontes

Livros sobre o assunto "Deming regression"

1

Valdman, Edouard. Demain, l'Occident!: Essai. L'Harmattan, 2013.

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2

El-Shaarawi, A. H. Modelling the dissolved oxygen change in streams using nonlinear regression analysis. Inland Waters Directorate, National Water Research Institute, Canada Centre for Inland Waters, 1988.

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3

Urga, Giovanni. Panel data vs. time series regression analysis: An aggregation issue : a comparison using labour demand functions. London University, Queen Mary and Westfield College, Department of Economics, 1993.

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4

Jeske, Karsten. U.S. tax policy and health insurance demand: Can a regressive policy improve welfare? Federal Reserve Bank of Atlanta, 2007.

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5

Bordo, Michael D. The long-run behavior of velocity: The institutional approach revisited. National Bureau of Economic Research, 1989.

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6

Toyoda, Toshihisa. Switching regression model with different change-points for individual coefficients and its application to the energy demand equations for Japan. University of Essex, Dept. of Economics, 1988.

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7

Grigor'ev, Anatoliy, and Evgeniy Isaev. Methods and algorithms of data processing. INFRA-M Academic Publishing LLC., 2020. http://dx.doi.org/10.12737/1032305.

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The tutorial deals with selected methods and algorithms of data processing, the sequence of solving problems of processing and analysis of data to create models behavior of the object taking into account all the components of its mathematical model. Describes the types of technological methods for the use of software and hardware for solving problems in this area. The algorithms of distributions, regressions vremenny series, transform them with the aim of obtaining mathematical models and prediction of the behavior information and economic systems (objects). The second edition is supplem

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Baird, Sarah, Craig McIntosh, and Berk Özler. The Regressive Demands of Demand-Driven Development. The World Bank, 2011. http://dx.doi.org/10.1596/1813-9450-5883.

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Baird, Sarah, Craig McIntosh, and Berk Özler. The Regressive Demands of Demand-Driven Development. Elsevier, 2013. https://doi.org/10.1596/16222.

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Choi, Ji-Hyeon. Estimation of a vegetable demand system: A censored regression approach. 1993.

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Capítulos de livros sobre o assunto "Deming regression"

1

Taylor, Lester D. "Quantile Regression Analysis of Asymmetrically Distributed Residuals." In Consumer Demand in the United States. Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-0510-9_9.

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2

Manojpraphakar, T., and Soundarrajan A. "Energy Demand Prediction Using Linear Regression." In Proceedings of International Conference on Artificial Intelligence, Smart Grid and Smart City Applications. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-24051-6_40.

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3

Wani, Tanveer Ahmad, and Mohd Shiraz. "Electricity Demand Forecasting Using Regression Techniques." In Lecture Notes in Civil Engineering. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-7557-6_9.

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Taylor, Lester D. "Quantile Regression: A Robust Alternative to Least Squares." In Consumer Demand in the United States. Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-0510-9_3.

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Bartels, Robert, and Denzil G. Fiebig. "Efficiency of Alternative Estimators in Generalized Seemingly Unrelated Regression Models." In Contributions to Consumer Demand and Econometrics. Palgrave Macmillan UK, 1992. http://dx.doi.org/10.1007/978-1-349-12221-9_7.

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Kirthika, N., K. I. Ramachandran, and Sasi K. Kottayil. "Deep Quantile Regression Based Wind Generation and Demand Forecasts." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-49345-5_12.

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Korasawala, Husain, Satyajit Pangaonkar, Reena Gunjan, and Prakash Rokade. "Use of Regression Algorithm for Bike Ride Sharing Demand Projection." In Springer Proceedings in Mathematics & Statistics. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-51167-7_18.

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Deepak, R., R. Sathyanarayanan, and J. Arunnehru. "Demand and Sales Forecasting Using Random Forest and Linear Regression." In Lecture Notes in Networks and Systems. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-1981-8_42.

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Höpken, Wolfram, Dominic Regitz, Nadine Liedtke, and Matthias Fuchs. "Estimating Tourist Arrivals by User Generated Content Volume in Periods of Extraordinary Demand Fluctuations." In Information and Communication Technologies in Tourism 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-25752-0_25.

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AbstractIn extraordinary situations, like the Covid-19 pandemic, irregular demand fluctuations can hardly be predicted by traditional forecasting approaches. Even the current extent of decline of demand is typically unknown since tourism statistics are only available with a time delay. This study presents an approach to benefit from user generated content (UGC) in form of online reviews from TripAdvisor as input to estimate current tourism demand in near real-time. The approach builds on an additive time series component model and linear regression to estimate tourist arrivals. Results indicat

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Yanyan, Peng. "Intellectualization Projection Pursuit Regression Model Used in the Water Demand Forecasting." In Lecture Notes in Electrical Engineering. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-24820-7_80.

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Trabalhos de conferências sobre o assunto "Deming regression"

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Jiang, Haozhe, Xiangyu Kong, Xiyuan Zhang, Zhengtao Wang, and Mingxing Guo. "Deep Learning-based Quantile Regression for Demand Response Potential Assessment." In 2024 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2024. http://dx.doi.org/10.1109/pesgm51994.2024.10689120.

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2

Pollock, Sam, Merkebe Getachew Demissie, and Lina Kattan. "Modelling Link-Level Shared Micromobility Demand: Regression and Neural Network Approaches." In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2024. https://doi.org/10.1109/itsc58415.2024.10919661.

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Kachalla, Ibrahim Ali, and Christian Ghiaus. "Forecasting Hot Water Consumption Demand for Residential Dwellings Using Hybrid Regression Technique." In 2024 IEEE International Conference on Green Energy and Smart Systems (GESS). IEEE, 2024. https://doi.org/10.1109/gess63533.2024.10784974.

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Chatuanramtharnghaka, Benjamin, Subhasish Deb, and Ksh Robert Singh. "Enhancing Demand Response Forecasting Through Random Forest Regression: A Case Study Analysis." In 2024 6th International Conference on Energy, Power and Environment (ICEPE). IEEE, 2024. http://dx.doi.org/10.1109/icepe63236.2024.10668929.

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Niembro, Antonio Martinez, and Ernesto L. Gudiño Ortiz. "Cathodic Protection Design Using the Regression and Correlation Method." In CORROSION 1997. NACE International, 1997. https://doi.org/10.5006/c1997-97556.

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Abstract A computerized statistical method which calculates the current demand requirement based on potential measurements for cathodic protection systems is introduced. The method uses the regression and correlation analysis of statistical measurements of current and potentials of the piping network. This approach involves four steps: field potential measurements, statistical determination of the current required to achieve full protection, installation of more cathodic protection capacity with distributed anodes around the plant and examination of the protection potentials. The procedure is

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Makin, Amirudin Hj, Muhammad Irsyad Abdullah, and Rabab Alayham Abbas Helmi. "Demand Prediction for Perishable Products Using Machine Learning Regression Techniques: A Narrative Review." In 2024 IEEE International Conference on Agrosystem Engineering, Technology & Applications (AGRETA). IEEE, 2024. https://doi.org/10.1109/agreta61912.2024.10948994.

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Isa, Siti Nursyafiqah Md, Kamarulazhar Daud, Mohammad Nizam Ibrahim, Ahmad Asri Abd Samat, Saodah Omar, and Mohd Affandi Shafie. "Analysis of Power Consumption and Maximum Demand on Power Factor Using Support Vector Machine Regression." In 2024 IEEE 14th International Conference on Control System, Computing and Engineering (ICCSCE). IEEE, 2024. http://dx.doi.org/10.1109/iccsce61582.2024.10696146.

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Li, Lingbo, Tongjun Wu, Yan Xia, and Pizhen Zhang. "Prediction and Analysis of Shared Bicycle Rental Demand Based on Feature Engineering and Regression Algorithm." In 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2024. https://doi.org/10.1109/ei264398.2024.10990777.

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Mittas, Nikolaos, Makrina Viola Kosti, Vasiliki Argyropoulou, and Lefteris Angelis. "Modeling the relationship between software effort and size using deming regression." In the 6th International Conference. ACM Press, 2010. http://dx.doi.org/10.1145/1868328.1868339.

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Cetinkaya, Mert, and Tankut Acarman. "Next-Day Electricity Demand Forecasting Using Regression*." In 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS). IEEE, 2021. http://dx.doi.org/10.1109/icais50930.2021.9395926.

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Relatórios de organizações sobre o assunto "Deming regression"

1

Valencia, Oscar, Juliana Gamboa-Arbeláez, and Gustavo Sánchez. Debt Erosion: Asymmetric Response to Demand and Supply Shocks. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005027.

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This paper explores the effect of inflation supply and demand shocks on government debt. It identifies the shocks using a sign-restricted Structural Vector Autoregression (SVAR) model with quarterly data. Estimations of dynamic panel regressions and local projections suggest that supply shocks lead to persistent increases in government debt, while demand shocks result in long-lasting declines. Furthermore, high debt levels increase economic vulnerability, amplifying the impacts of both supply and demand shocks by more than three times. Specifically, supply shocks increase debt through higher b

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2

Grimm, Kevin. Structural Equation Modeling 1: Foundations & Programs. Instats Inc., 2023. http://dx.doi.org/10.61700/8eni7h9r63sa3469.

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'Structural Equation Modeling I: Foundations & Programs' is an on-demand workshop led by professor Kevin Grimm, providing a comprehensive review of covariance analysis, regression, covariance expectations, path diagrams, SEM notation, and SEM programs. Participants will gain a solid understanding of SEM and be prepared to specify, estimate, and interpret SEMs. An official Instats certificate of completion and 1 ECTS Equivalent point are provided at the conclusion of the seminar

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3

Garabato, Natalia, and Magdalena Ramada. Housing Markets in Uruguay: Determinants of Housing Demand and Its Interaction with Public Policies. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0011348.

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This paper analyzes the determinants of housing demand for Uruguay and the extent to which housing policies have an impact on their target population. The paper first analyzes the determinants of housing demand, following an approach based on Rosen's (1974) two-step procedure consisting of fitting a hedonic price regression in 34 different geographical units (or markets) to estimate a housing demand function. The determinants of formality and ownership choices were examined using a multinomial logit framework. Determinants of these choices include both household demographic attributes and acce

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Ardanaz, Martín, Evelyne Hübscher, Philip Keefer, and Thomas Sattler. Policy Misperceptions, Information, and the Demand for Redistributive Tax Reform: Experimental evidence from Latin America. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004473.

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Scholars have long struggled to understand why individual preferences for redistribution often diverge widely from their material self-interest. The puzzle is acute in Latin America, largely democratic and yet one of the most unequal regions in the world. Using an original online survey experiment spanning 8 countries and 12,000 respondents across Latin America, we find significant evidence for an under-explored explanation: misconceptions regarding the distributional effects of current tax policy. Treated respondents who are informed that an increase in the value-added tax (VAT) is regressive

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Corseuil, Carlos Henrique, and Ricardo Paes De Barros. The Impact of Regulations on Brazilian Labor Market Performance. Inter-American Development Bank, 2001. http://dx.doi.org/10.18235/0011245.

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The objective of this paper is to identify whether the prevailing Brazilian labor market regulations, largely the result of the 1988 constitutional change, have any impact on labor market performance. To reach this objective the authors explore alternative methodologies, sources of information and measures of labor market performance. The paper briefly describes the 1988 constitutional change, with special emphasis on topics related to labor costs; two alternative measures of labor market performance, the first of which is based on parameters estimated from a labor demand model, and the second

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Deutsch, Anne, and Steven Lutzky. Risk adjustment for home and community-based services quality measurement. RTI Press, 2025. https://doi.org/10.3768/rtipress.2025.pb.0030.2505.

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Home and community-based services are support services provided to persons with disabilities that enable them to live in the community. The growing demand for home and community-based services has led to an increase in efforts to measure the quality, including the effectiveness, of these services and supports in helping people to achieve their desired health and quality-of-life outcomes. Quality measures that focus on outcomes may need to be risk adjusted. This is because each provider serves a unique mix of persons with varying characteristics, and a provider’s case-mix can confound their out

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Ardanaz, Martín, Evelyne Hübscher, Philip Keefer, and Thomas Sattle. Policy Misperceptions, Information, and the Demand for Redistributive Tax Reform: Experimental Evidence from Latin American Countries. Inter-American Development Bank, 2022. http://dx.doi.org/10.18235/0004655.

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Why do individuals preferences for redistribution often diverge widely from their material self-interest? Using an original online survey experiment spanning eight countries and 12,000 respondents across Latin America, one of the most unequal regions in the world, we find significant evidence for an under-explored explanation: misconceptions regarding the distributional effects of current tax policy. Treated respondents who are informed that an increase in the value added tax (VAT) is regressive are significantly more likely to prefer policy reforms that make the tax more progressive. Treatmen

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Micco, Alejandro, and Carmen Pagés. The Economic Effects of Employment Protection: Evidence from International Industry-Level Data. Inter-American Development Bank, 2007. http://dx.doi.org/10.18235/0010723.

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This paper examines the economic effects of employment protection legislation in a sample of developed and developing countries. Implementing a difference-in-differences test lessens the potentially severe endogeneity and omitted variable problems associated with cross-country regressions. This test is based on the hypothesis that employment protection regulations are more binding in sectors of activity exposed to higher volatility in demand or supply shocks. The analysis indicates that more stringent legislation slows down job turnover by a significant amount, and that this effect is more pro

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Micco, Alejandro, and Carmen Pagés. Employment Protection and Gross Job Flows: A Differences-in-Differences Approach. Inter-American Development Bank, 2004. http://dx.doi.org/10.18235/0010730.

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This paper examines the effect of employment protection regulation on gross job flows in a sample of developed and developing countries. By implementing a differences-in-differences test we lessen the potentially severe endogeneity and omitted variable problems associated with cross-country regressions. This test is based on the hypothesis that job security regulations are more binding in some sectors of economic activity than in others, depending on sector-specific characteristics such as the variance of demand or technological shocks. Unlike most of the existing literature, our analysis indi

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Zang, Emma. Bayesian Statistics for Social and Health Scientists in R and Python + 2 Free Seminars. Instats Inc., 2022. http://dx.doi.org/10.61700/bgfpomu3wdhe5469.

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This seminar will introduce you to Bayesian statistics, which are increasingly popular and offer a powerful alternative to more traditional forms of statistical analysis. Targeted at a social and health science audience, the seminar will cover the fundamentals of Bayesian inference and illustrate a variety of techniques with applied examples of Bayesian regressions and hierarchical models. You will gain an understanding of Markov chain Monte Carlo (MCMC) methods and learn how to develop and validate Bayesian models so that you can apply them in your daily research, with the kinds of intuitive

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