Relevant bibliographies by topics / Regressive dependence

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Regressive dependence'

Author: Grafiati
Published: 28 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Regressive dependence"

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Cohn, Daniel. "Regressive Taxation and the Welfare State: Path Dependence and Policy Diffusion." Canadian Journal of Political Science 38, no. 4 (2005): 1079–80. http://dx.doi.org/10.1017/s0008423905309978.

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Regressive Taxation and the Welfare State: Path Dependence and Policy Diffusion, Junko Kato, Cambridge: Cambridge University Press, 2003, pp. 260.This book provides a surprisingly interesting look at an understudied problem within the field of comparative welfare state research: the relationship between funding and welfare state regime characteristics. The author proposes that researchers take a second look at regressive taxation, specifically value-added taxes (VATs) such as Canada's GST. While it is commonly assumed that a sustainable and extensive welfare state goes hand-in-hand with a heav
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Rixen, Thomas. "Regressive Taxation and the Welfare State: Path Dependence and Policy Diffusion." Contemporary Sociology: A Journal of Reviews 34, no. 4 (2005): 409–10. http://dx.doi.org/10.1177/009430610503400444.

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G.A., Salimova. "CORRELATION-REGRESSIVE MODELING OF THE EMPLOYMENT LEVEL OF THE POPULATION." Russian Electronic Scientific Journal 54, no. 4 (2024): 192–202. https://doi.org/10.31563/2308-9644-2024-54-4-192-202.

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The article presents the results of constructing correlation and regression analysis models of the dependence of the employment level of the population in the regions of the Central and Volga Federal Districts of the Russian Federation on factors in a dynamic aspect. Based on the results of the correlation and regression analysis, a significant influence of factors on the employment level of the population of the regions was revealed for almost all years. The combined influence of the selected factors on the employment level of the population increases until 2020, then sharply decreases in 202
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Avdulaj, Krenar, and Ladislav Kristoufek. "On Tail Dependence and Multifractality." Mathematics 8, no. 10 (2020): 1767. http://dx.doi.org/10.3390/math8101767.

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We study whether, and if yes then how, a varying auto-correlation structure in different parts of distributions is reflected in the multifractal properties of a dynamic process. Utilizing the quantile autoregressive process with Gaussian copula using three popular estimators of the generalized Hurst exponent, our Monte Carlo simulation study shows that such dynamics translate into multifractal dynamics of the generated series. The tail-dependence of the auto-correlations forms strong enough non-linear dependencies to be reflected in the estimated multifractal spectra and separated from the cas
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Chikr Elmezouar, Zouaoui, Abderrahmane Belguerna, Hamza Daoudi, Fatimah Alshahrani, and Zoubeyr Kaddour. "Advancing the Analysis of Extended Negative Dependence Random Variables: A New Concentration Inequality and Its Applications for Linear Models." Axioms 13, no. 8 (2024): 511. http://dx.doi.org/10.3390/axioms13080511.

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This paper introduces an innovative concentration inequality for Extended Negative Dependence (END) random variables, providing new insights into their almost complete convergence. We apply this inequality to analyze END variable sequences, particularly focusing on the first-order auto-regressive (AR(1)) model. This application highlights the dynamics and convergence properties of END variables, expanding the analytical tools available for their study. Our findings contribute to both the theoretical understanding and practical applications of END variables in fields such as finance and machine
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Phillips, Jonathan D. "Progressive and Regressive Pedogenesis and Complex Soil Evolution." Quaternary Research 40, no. 2 (1993): 169–76. http://dx.doi.org/10.1006/qres.1993.1069.

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AbstractThe simultaneous operation of regressive and progressive pedogenetic pathways raises the possibility that soil evolution may exhibit patterns far richer and more complex than increasing development over time. This possibility is explored via a numerical model incorporating the relative rates of progressive and regressive pedogenesis and feedbacks between these rates and the degree of soil development. This model may exhibit deterministic chaos and sensitive dependence on initial conditions with realistic parameter values. Variations in profile development in a region of the North Carol
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Kim, Yunji. "Limits of Property Taxes and Charges: City Revenue Structures After the Great Recession." Urban Affairs Review 55, no. 1 (2017): 185–209. http://dx.doi.org/10.1177/1078087417697199.

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Public finance theories argue local governments should primarily use broad-based and stable property taxes. However, the housing bust after the Great Recession challenges this argument, and historical trends show cities have heavily relied on charges since the late 1970s. Using 2012 Census of Governments data for 2,396 cities, this article explores which cities rely more on charges and the links between property tax dependence and city stress. Regression results show property tax dependence is linked to capacity, while charges dependence is linked to stress. Charges can be a useful revenue too
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Goodhart, Lucy. "Book Review: Regressive Taxation and the Welfare State: Path Dependence and Policy Diffusion." Comparative Political Studies 38, no. 2 (2005): 225–28. http://dx.doi.org/10.1177/0010414004271373.

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Muhammad Umair Ali, Saliha Gul Abbasi, Mazhar Abbas, and Ghulam Dastgeer. "Impact of Infaltion, Exchange Rate and Interest Rate on the Private Sector Credit of Pakistan." Journal of Accounting and Finance in Emerging Economies 6, no. 4 (2020): 1133–38. http://dx.doi.org/10.26710/jafee.v6i4.1477.

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The paper analyzed the long-term and short-term impact of interest rate, exchange rate and inflation on the private sector credit of Pakistan during the period from 1975 to 2018. To test the stationarity of data Augmented Dick Fuller (ADF) Test was applied. While the main model to explore the long-term and short-term dependence was based on Auto Regressive Distribution Lag (ARDL) Model. The results suggested no effect of exchange rate on private sector credit, while inflation has significant as well as positive impact on Private Sector Credit (PSC) in long as well as short run. Lastly, the mos
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Prishchenko, Olga, and Tetyana Chernogor. "USING OF METHODS OF CROSS-CORRELATION AND REGRESSIVE ANALYSIS FOR DETERMINATION OF FUNCTIONAL DEPENDENCE BETWEEN SIZES." Bulletin of the National Technical University "KhPI". Series: Innovation researches in students’ scientific work, no. 15 (August 5, 2019): 36–41. http://dx.doi.org/10.20998/2220-4784.2019.15.07.

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Dissertations / Theses on the topic "Regressive dependence"

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Шовкопляс, Н. Р. "Програмні середовища для проведення парного лінійного регресійного аналізу". Thesis, Сумський державний університет, 2018. http://essuir.sumdu.edu.ua/handle/123456789/66833.

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У роботі наведені результати порівняльного аналізу використання табличного процесора MS Excel та програмного середовища NI LabVIEW для побудови формули лінійної регресійної залежності між двома змінними. Регресійний аналіз фактичних даних проведений у безрозмірній формі.
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Xie, Bo. "Requirement based regression test suite reduction using dependence analysis." Thesis, University of Ottawa (Canada), 2006. http://hdl.handle.net/10393/27200.

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In this research, we present an extension to an existing requirement-based regression test suite reduction approach that uses EFSM model dependence analysis to reduce a given regression test suite [19]. The approach is based on the difference between the original model and the modified model expressed as a set of elementary model modifications: elementary addition of a transition and elementary deletion of a transition. For each elementary modification, the data and control dependencies are used to capture potential interactions between EFSM transitions. The potential interactions are used to
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Sim, Nicholas. "Modeling Quantile Dependence." Thesis, Boston College, 2009. http://hdl.handle.net/2345/2467.

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Thesis advisor: Zhijie Xiao<br>In recent years, quantile regression has achieved increasing prominence as a quantitative method of choice in applied econometric research. The methodology focuses on how the quantile of the dependent variable is influenced by the regressors, thus providing the researcher with much information about variations in the relationship between the covariates. In this dissertation, I consider two quantile regression models where the information set may contain quantiles of the regressors. Such frameworks thus capture the dependence between quantiles - the quantile of th
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COLUMBU, SILVIA. "Parametric modeling of dependence of bivariate quantile regression residuals' signs." Doctoral thesis, Università degli Studi di Cagliari, 2015. http://hdl.handle.net/11584/266587.

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In this thesis, we propose a non-parametric method to study the dependence of the quantiles of a multivariate response conditional on a set of covariates. We define a statistic that measures the conditional probability of concordance of the signs of the residuals of the conditional quantiles of each univariate response. The probability of concordance is bounded from below by the value of largest possible negative dependence and from above by that of largest possible positive dependence. The value corresponding to the case of independence is contained in the interior of that interval. We
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Park, Ju-Hyun Dunson David B. "Bayesian density regression and predictor-dependent clustering." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1821.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Dec. 11, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biostatistics, School of Public Health." Discipline: Biostatistics; Department/School: Public Health.
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Lumley, Thomas. "Marginal regression modelling of weakly dependent data /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/9555.

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Chen, Ke. "Latent dependency mining for solving regression problems in computer vision." Thesis, Queen Mary, University of London, 2013. http://qmro.qmul.ac.uk/xmlui/handle/123456789/8402.

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Regression-based frameworks, learning the direct mapping between low-level imagery features and vector/scalar-formed continuous labels, have been widely exploited in computer vision, e.g. in crowd counting, age estimation and human pose estimation. In the last decade, many efforts have been dedicated by researchers in computer vision for better regression fitting. Nevertheless, solving these computer vision problems with regression frameworks remained a formidable challenge due to 1) feature variation and 2) imbalance and sparse data. On one hand, large feature variation can be caused by the c
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Berrett, Candace. "Bayesian Probit Regression Models for Spatially-Dependent Categorical Data." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1285076512.

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Mok, Kit Ying. "Central limit theorem for nonparametric regression under dependent data /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?MATH%202003%20MOK.

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El, Ghouch Anouar. "Nonparametric statistical inference for dependent censored data." Université catholique de Louvain, 2007. http://edoc.bib.ucl.ac.be:81/ETD-db/collection/available/BelnUcetd-09262007-123927/.

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A frequent problem that appears in practical survival data analysis is censoring. A censored observation occurs when the observation of the event time (duration or survival time) may be prevented by the occurrence of an earlier competing event (censoring time). Censoring may be due to different causes. For example, the loss of some subjects under study, the end of the follow-up period, drop out or the termination of the study and the limitation in the sensitivity of a measurement instrument. The literature about censored data focuses on the i.i.d. case. However in many real applications the da
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Books on the topic "Regressive dependence"

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Robinson, P. M. Time series regression with long range dependence. Suntory and Toyota International Centres for Economics and Related Disciplines, 1997.

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Orme, John G. Multiple regression with discrete dependent variables. Oxford University Press, 2009.

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Jeremy, Freese, ed. Regression models for categorical dependent variables using Stata. Stata Press, 2001.

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Long, J. Scott. Regression models for categorical dependent variables using Stata. Stata Press, 2003.

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Jeremy, Freese, ed. Regression models for categorical dependent variables using Stata. Stata Corporation, 2003.

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Jeremy, Freese, ed. Regression models for categorical dependent variables using Stata. 2nd ed. StataCorp LP, 2006.

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Sweden, Robert C. Van. Regression to dependence: A second opportunity for ego integration and developmental progression. J. Aronson, 1995.

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Robinson, P. M. Large-sample inference for nonparametric regression with dependent errors. Suntory and Toyota International Centres for Economics and Related Disciplines, 1997.

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Kuan, Chung-Ming. Recursive M-estimation, nonlinear regression and neural network learning with dependent observations. College of Commerce and Business Administration, University of Illinois at Urbana-Champaign, 1990.

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Banowetz, G. M. A computer program for logit-log transformation and linear regression analysis of concentration-dependent biological and chemical responses. U.S. Dept. of Agriculture, Agricultural Research Service, 1987.

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Book chapters on the topic "Regressive dependence"

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Erdely, Arturo. "Copula-based piecewise regression." In Copulas and Dependence Models with Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-64221-5_5.

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Ward, Michael D., and Kristian Skrede Gleditsch. "Spatially Lagged Dependent Variables." In Spatial Regression Models. SAGE Publications, Inc., 2019. http://dx.doi.org/10.4135/9781071802588.n8.

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Rossello, Damiano. "Regression, Prediction and More Dependence." In A Cookbook with Probability One. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-54688-4_7.

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Vapnik, Vladimir. "Estimation of Regression Parameters." In Estimation of Dependences Based on Empirical Data. Springer New York, 2006. http://dx.doi.org/10.1007/0-387-34239-7_5.

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Kohn, Robert, Michael G. Schimek, and Michael Smith. "Spline and Kernel Regression for Dependent Data." In Smoothing and Regression. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118150658.ch6.

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Thrane, Christer. "An ordered (ordinal) dependent variableLogistic (logit) regression." In Applied Regression Analysis. Routledge, 2019. http://dx.doi.org/10.4324/9780429443756-11.

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Thrane, Christer. "A categorical dependent variableLogistic (logit) regression and related methods." In Applied Regression Analysis. Routledge, 2019. http://dx.doi.org/10.4324/9780429443756-10.

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Anselin, Luc. "Spatial Dependence in Regression Error Terms." In Spatial Econometrics: Methods and Models. Springer Netherlands, 1988. http://dx.doi.org/10.1007/978-94-015-7799-1_8.

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Lee, Myoung-jae. "Nonparametric Regression." In Methods of Moments and Semiparametric Econometrics for Limited Dependent Variable Models. Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4757-2550-6_8.

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Welc, Jacek, and Pedro J. Rodriguez Esquerdo. "Regression Analysis of Discrete Dependent Variables." In Applied Regression Analysis for Business. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-71156-0_7.

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Conference papers on the topic "Regressive dependence"

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Tanaka, Kenta, and Tomoyuki Sugimoto. "On the Use of Gaussian Process Regression and Multiple Imputation in Cox Regression Models with Time-Dependent Covariates." In 2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC). IEEE, 2024. http://dx.doi.org/10.1109/compsac61105.2024.00311.

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Tamas, Anca. "THE IMPACT OF DEMOGRAPHICS ON ECONOMIC DEVELOPMENT OF THE BRICS COUNTRIES." In 11th SWS International Scientific Conferences on SOCIAL SCIENCES - ISCSS 2024. SGEM WORLD SCIENCE, 2024. https://doi.org/10.35603/sws.iscss.2024/s03/24.

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The aim of this paper is to assess the impact of the demographics on the economic development on the BRICS countries during 2009-2021. The BRICS countries as Brazil, Russia, India, China and South Africa are known starting 2009 (and 2010 for South Africa respectively), they are fast growing economies, emerging markets in the second stage of demographic transition and highly heterogeneous countries in most social economic features. Due to the fact they are counting for more than 40% of the global population, the demographic impact on the economic development should be significant. EViews 8 was
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Grachev, Vladimir, Michael Shvarts, Alexander Grischenko, and Philipp Shvarts. "Increasing the statistical signification of regression dependence in the problems of processing experimental samples of small volume." In Fourth International Conference on Optics, Computer Applications, and Materials Science (CMSD-IV 2024), edited by Arthur Gibadullin and Ramazon Abdullozoda. SPIE, 2025. https://doi.org/10.1117/12.3060519.

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Kulynych, Roman. "Statistic methods of definition of the social standards selection of statistic methods for definition of the social standards." In The 8th International Conference "Management Strategies and Policies in the Contemporary Economy". Academy of Economic Studies of Moldova, 2023. http://dx.doi.org/10.53486/icspm2023.14.

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Methods of definition of social normd on the example of cumulative volume population’s monetary incomes and its separate parts (payment of labour, pensions, scholarships, assistance, subsidies; receipt from own subsidiary economy, other sources) and population’s expenses to the food products and nonfood-stuffs has been shown in this work. Great attention has been given to the comparative analysis of efficiency of regressive analysis and statistic equations of dependence on level’s definition of social norms
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Hasan, Mohammad H., and Fadi Alsaleem. "Nonlinear Time-Series Prediction Using a Single MEMS Reservoir." In ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/detc2020-22671.

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Abstract In this work, we show the computational potential of MEMS devices by predicting the dynamics of a 10th order nonlinear auto-regressive moving average (NARMA10) dynamical system. Modeling this system is considered complex due to its high nonlinearity and dependency on its previous values. To model the NARMA10 system, we used a reservoir computing scheme by utilizing one MEMS device as a reservoir, produced by the interaction of 100 virtual nodes. The virtual nodes are attained by sampling the input of the MEMS device and modulating this input using a random modulation mask. The interac
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Fewzee, Pouria, Ali-Akbar Samadani, Dana Kulic, and Fakhri Karray. "Max-dependence regression." In 2014 International Joint Conference on Neural Networks (IJCNN). IEEE, 2014. http://dx.doi.org/10.1109/ijcnn.2014.6889867.

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Vasiliev, Alexandr, and Svetlana Daškevič. "ASSESSMENT OF THE DEPTH AND RATE OF CORROSION IN STEEL REINFORCEMENT OF REINFORCED CONCRETE CULVERTS." In 11th International Conference “Environmental Engineering”. VGTU Technika, 2020. http://dx.doi.org/10.3846/enviro.2020.831.

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Based on the results of many research years on concrete carbonisation: both immediately after manufacture (using heat-moisture treatment) and in reinforced concrete elements operated for the periods of various length (in an open atmosphere); the effect of carbonisation on the change in the protective properties of concrete in relation to steel reinforcement; for determination of the dependence of the corrosion state of steel reinforcement on the degree of concrete carbonisation in the area of steel reinforcement; the obtained regression dependences of the change (by time in the cross section)
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Daskalakis, Constantinos, Nishanth Dikkala, and Ioannis Panageas. "Regression from dependent observations." In STOC '19: 51st Annual ACM SIGACT Symposium on the Theory of Computing. ACM, 2019. http://dx.doi.org/10.1145/3313276.3316362.

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Hans, Christopher. "Prior Dependence in L1-regularized Bayesian Regression." In 4th International Conference on Statistics: Theory and Applications (ICSTA'22). Avestia Publishing, 2022. http://dx.doi.org/10.11159/icsta22.007.

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Ivuawuogu, Henry, Steven Jiang, Lauren Davis, and Mikaya Hamilton. "Predictive Model for Partner Agencies Dependency on Food Banks." In 2024 AHFE International Conference on Human Factors in Design, Engineering, and Computing (AHFE 2024 Hawaii Edition). AHFE International, 2024. http://dx.doi.org/10.54941/ahfe1005573.

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In the quest for equitable resource distribution within food banks and their partner agencies, understanding the dependencies of these agencies on food banks emerges as a critical factor. This study investigates the intricate dynamics influencing agency dependency ratios, exploring the complex factors that shape the demand for food resources. Leveraging historical self-reported dependency ratio data, this preliminary study employs predictive modeling using Multiple Linear Regression to forecast agency dependencies on food banks. The primary objective is to discern the underlying factors that s
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Reports on the topic "Regressive dependence"

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Robinson, Peter, and Supachoke Thawornkaiwong. Statistical inference on regression with spatial dependence. Institute for Fiscal Studies, 2011. http://dx.doi.org/10.1920/wp.cem.2011.0811.

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Robinson, Peter. Nonparametric trending regression with cross-sectional dependence. Institute for Fiscal Studies, 2011. http://dx.doi.org/10.1920/wp.cem.2011.1011.

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Poupakis, Stavros, Peter Levell, and Thomas Crossley. Regression with an Imputed Dependent Variable. The IFS, 2019. http://dx.doi.org/10.1920/wp.ifs.2019.1619.

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Hausman, Jerry, Haoyang Liu, Ye Luo, and Christopher Palmer. Errors in the Dependent Variable of Quantile Regression Models. National Bureau of Economic Research, 2019. http://dx.doi.org/10.3386/w25819.

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Cabrera, Grant. Local Polynomial Regression with Semi-Long Range Dependent Errors. Iowa State University, 2024. http://dx.doi.org/10.31274/cc-20240624-966.

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Mathew, Sonu, Srinivas S. Pulugurtha, and Sarvani Duvvuri. Modeling and Predicting Geospatial Teen Crash Frequency. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2119.

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This research project 1) evaluates the effect of road network, demographic, and land use characteristics on road crashes involving teen drivers, and, 2) develops and compares the predictability of local and global regression models in estimating teen crash frequency. The team considered data for 201 spatially distributed road segments in Mecklenburg County, North Carolina, USA for the evaluation and obtained data related to teen crashes from the Highway Safety Information System (HSIS) database. The team extracted demographic and land use characteristics using two different buffer widths (0.25
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Almuzara, Martín, and Víctor Sancibrián. Micro Responses to Macro Shocks. Federal Reserve Bank of New York, 2024. http://dx.doi.org/10.59576/sr.1090.

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We study estimation and inference in panel data regression models when the regressors of interest are macro shocks, which speaks to a large empirical literature that targets impulse responses via local projections. Our results hold under general dynamics and are uniformly valid over the degree of signal-to-noise of aggregate shocks. We show that the regression scores feature strong cross-sectional dependence and a known autocorrelation structure induced only by leads of the regressor. In general, including lags as controls and then clustering over the cross-section leads to simple, robust infe
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Kott, Phillip S. The Role of Weights in Regression Modeling and Imputation. RTI Press, 2022. http://dx.doi.org/10.3768/rtipress.2022.mr.0047.2203.

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When fitting observations from a complex survey, the standard regression model assumes that the expected value of the difference between the dependent variable and its model-based prediction is zero, regardless of the values of the explanatory variables. A rarely failing extended regression model assumes only that the model error is uncorrelated with the model’s explanatory variables. When the standard model holds, it is possible to create alternative analysis weights that retain the consistency of the model-parameter estimates while increasing their efficiency by scaling the inverse-probabili
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Kotlikoff, Laurence J., Guillermo Lagarda, and Gabriel Marin. A Personalized VAT with Capital Transfers: A Reform to Protect Low-Income Households in Mexico. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005028.

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The Value-Added Tax (VAT) is the most prevalent consumption tax globally, yet it is frequently deemed highly regressive. To address this, we propose a Personalized VAT (PVAT) devised in conjunction with a distributional policy. We aim to achieve three objectives: increase revenue collection, achieve progressivity, and disrupt the intergenerational dependency of low-income households. We use Mexico as a case study, showing that eliminating all special VAT regimes and standardizing the rate at 16% could contribute an additional 2.2% of GDP to fiscal revenues. However, such a reform could have se
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Mullahy, John, and Edward Norton. Why Transform Y? A Critical Assessment of Dependent-Variable Transformations in Regression Models for Skewed and Sometimes-Zero Outcomes. National Bureau of Economic Research, 2022. http://dx.doi.org/10.3386/w30735.

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