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Non parametric regression models with additive distortions [PDF]
, 2023 In this article, we study the non parametric estimation of some regression curves when the data are observed with additive distortions, and these distortions for unobservable response variables and covariates are connected with a common observed ...
Jun Zhang (48506) +2 more
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Testing the Equality of Two Parametric Quantile Regression Curves : The Application for Comparing Two Data Sets [PDF]
, 2016 This study aims to compare the different between two data sets that having the relationship between the dependent and independent variables at each quantile using testing the equality of two parametric quantile regression functions, the conditional ...
Tonggumnead, Unchalee; Faculty of Science and Technology, Rajamangala University of Technology Thanyaburi, 39 Moo1, Rangsit-Nakhonnayok Rd. Klong6, Thanyaburi, Pathum Thani 12110Thailand
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Adaptive Robust Efficient Methods for Periodic Signal Processing Observed with Colours Noises
Advances in Electrical and Electronic Engineering, 2019 In this paper, we consider the problem of robust adaptive efficient estimating a periodic signal observed in the transmission channel with the dependent noise defined by non-Gaussian Ornstein-Uhlenbeck processes with unknown correlation properties ...
Evgeny Pchelintsev +2 more
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Agricultural Economics (AGRICECON), 2023 Sustainable intensification (SI) is a widely discussed concept that aims to increase agricultural production without harming the environment. This study assessed the process of SI that took place in the EU regions from 2004 to 2018 and the impact of ...
Jakub Staniszewski, Anika Muder
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Non-parametric regression for binary dependent variables [PDF]
, 2006 Finite-sample properties of non-parametric regression for binary dependent variables are analyzed. Non parametric regression is generally considered as highly variable in small samples when the number of regressors is large.
Frölich, Markus, Markus Fr�lich
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On the pitfalls of Gaussian likelihood scoring for causal discovery
Journal of Causal Inference, 2023 We consider likelihood score-based methods for causal discovery in structural causal models. In particular, we focus on Gaussian scoring and analyze the effect of model misspecification in terms of non-Gaussian error distribution. We present a surprising
Schultheiss Christoph, Bühlmann Peter
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Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Japan has one of the highest dialysis prevalence rates worldwide and a shrinking, aging population. Whether dialysis burden has entered a sustained post‐peak phase or whether recent declines partly reflect pandemic‐related disruptions remains uncertain.
Hatice Şahin +2 more
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JOIV: International Journal on Informatics VisualizationResearchers need to understand the differences between parametric and nonparametric regression models and how they work with available information about the relationship between response and explanatory variables and the distribution of random errors ...
Amjed Mohammed Sadek, Lekaa Ali Mohammed
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Plants, 2023 Lentil yield is a complicated quantitative trait; it is significantly influenced by the environment. It is crucial for improving human health and nutritional security in the country as well as for a sustainable agricultural system. The study was laid out
Md. Amir Hossain +8 more
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FEBS Letters, EarlyView.The Ile181Asn variant of human UDP‐xylose synthase (hUXS1), associated with a short‐stature genetic syndrome, has previously been reported as inactive. Our findings demonstrate that Ile181Asn‐hUXS1 retains catalytic activity similar to the wild‐type but exhibits reduced stability, a looser oligomeric state, and an increased tendency to precipitate ...
Tuo Li +2 more
wiley +1 more source