Results 51 to 60 of about 6,937 (202)
JTAM (Jurnal Teori dan Aplikasi Matematika)Regression analysis is one of the statistical methods used to model the relationship between response variables and predictor variables. Semiparametric regression is a combination of parametric and nonparametric regression.
Tiani Wahyu Utami +2 more
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A More Accurate Estimation of Semiparametric Logistic Regression
Mathematics, 2021 Growing interest in genomics research has called for new semiparametric models based on kernel machine regression for modeling health outcomes. Models containing redundant predictors often show unsatisfactory prediction performance.
Xia Zheng +3 more
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Local Eviction Moratoria and the Spread of COVID‐19
Southern Economic Journal, EarlyView.ABSTRACT At different stages during the initial onset of the COVID‐19 pandemic, various US states and local municipalities enacted eviction moratoria. One of the main aims of these moratoria was to slow the spread of COVID‐19 infections. We deploy a semiparametric difference‐in‐differences approach with an event study specification to examine whether ...
Julia Hatamyar, Christopher F. Parmeter
wiley +1 more source
SEMIPARAMETRIC REGRESSION AND GRAPHICAL MODELS
Australian & New Zealand Journal of Statistics, 2009 SummarySemiparametric regression models that use spline basis functions with penalization have graphical model representations. This link is more powerful than previously established mixed model representations of semiparametric regression, as a larger class of models can be accommodated. Complications such as missingness and measurement error are more
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Generalized Semiparametrically Structured Ordinal Models [PDF]
Biometrics, 2003 SummarySemiparametrically structured models are defined as a class of models for which the predictors may contain parametric parts, additive parts of covariates with an unspecified functional form, and interactions which are described as varying coefficients.
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International Journal for Re-Views in Empirical Economics, 2019 This paper aims to replicate the semiparametric Value-At-Risk model by Dias (2014) and to test its legitimacy. The study confirms the superiority of semiparametric estimation over classical methods such as mixture normal and Student-t approximations in ...
Jiahua Xu
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Teaching Statistics, EarlyView.Abstract Statistical hypothesis testing (SHT) is widely employed across numerous scientific disciplines, and a clear understanding of its underlying logic is essential for the broader scientific community. Here, drawing upon both epistemological and statistical perspectives, we aim to clarify—primarily for educational purposes—the logical relationship ...
Maria Cristina Amoretti +1 more
wiley +1 more source
Regulation, Taxation, and Resources: Unpacking Greenhouse Gas Emission Drivers Across G7 Economies
Thunderbird International Business Review, EarlyView.ABSTRACT Advanced economies are under growing pressure to downscale greenhouse gas (GHG) emissions without undermining growth, yet G7 (Group of Seven) nations, representing almost 10% of the world's population, still generate one quarter of global GHGs.
Mohammad Imtiaz Hossain +5 more
wiley +1 more source
Journal of Agricultural and Resource Economics, 2013 This study estimates off-farm labor supply from farm operators and their spouses using two different estimation procedures and data from the 2006 Agricultural Resource Management Survey.
Mahesh Pandit +2 more
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Mitigating policy uncertainty: What financial markets reveal about firm‐level lobbying
American Journal of Political Science, EarlyView.Abstract Elections can lead to substantial policy changes and, thus, are a significant source of risk. Firms can respond to such policy uncertainty by lobbying, but it is hard to quantify whether they do so and, if so, how much lobbying benefits them. We construct a new dataset and leverage investors’ expectations of variability in stock returns in the
Kristy Buzard +2 more
wiley +1 more source