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Asymptotic properties of estimators in a semi-parametric regression model with infinite rth moments

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2025年

作者： Wu, Yi Yao, Mei Wang, Xuejun Chizhou Univ Sch Big Data & Artificial Intelligence Chizhou Peoples R China Hefei Univ Technol Sch Math Hefei Peoples R China Anhui Univ Sch Big Data & Stat Hefei 230601 Peoples R China

This work investigates the asymptotic properties for the least squares estimator and nonparametric estimator in a semi-parametric regression model. The mean consistency and strong consistency are established under infinite rth (1 < r < 2) moments. The results obtained in the paper improve and extend some existing ones in the literature. Some numerical studies are also presented to verify the performance of the consistency of the estimators with finite sample.

关键词： Infinite moment Mean consistency semi-parametric regression model Strong consistency

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The Variable Weight Combination Load Forecasting Based on Grey model and semi-parametric regression model

The Variable Weight Combination Load Forecasting Based on Gr...

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IEEE International Conference of Region 10 (TENCON)

作者： Ma Shushu Chen Xingying Liao Yingchen Wang Gang Ding Xiaohua Chen Kai Hohai Univ Nanjing 211100 Jiangsu Peoples R China China Elect Power Res Inst Nanjing 211100 Peoples R China Nanjing Power Supply Co Nanjing 210019 Peoples R China

ISBN: (纸本)9781479928255;9781479928279

Grey model using dimensional information update technology always contains the latest information from sample data, it guarantees the accuracy of mid-long term load forecasting. semi-parametric regression model which combines the advantages of parametric model and nonparametric model, it can fully reflect the complexity and uncertainties of the load change. This paper put forward an improved method which combines grey model with semi-parametric regression model by time-varying weight for load forecasting, the proposed method would make full use of data information and consider its inherent regularity completely, which makes prediction more realistic. At last, a comparison of the error has been made between the single model and the combination model. The test example results show that this method has higher precision.

关键词： Grey model semi-parametric regression model Variable weight combination

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Assessing Neuron Response to External Stimuli with a Data-Driven Procedure for Spike Train Extraction and GAMLSS regressions

Assessing Neuron Response to External Stimuli with a Data-Dr...

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2022 Data Research Camp

作者： Barile, Francesco Dallari, Silvia Pacifici, Carlotta Gruen, Bettina Univ Milano Bicocca I-20126 Milan Italy Univ Bologna I-40126 Bologna Italy Vienna Univ Econ & Business Adm A-1020 Vienna Austria

ISBN: (纸本)9783031706400;9783031706387;9783031706370

Gaining a better understanding of the brain is an important aspect in biological research. To this end, new measurement tools are employed to collect data on calcium traces for mice to analyze the neuron response to external stimuli. Suitable statistical analysis methods for the challenging data sets emerging from these measurements are essential to eventually learn more about the functioning of the brain. We use the calcium traces collected for one mouse across three sessions to showcase a statistical analysis focusing on extracting potential effects of external stimuli on the neuron response based in particular on advanced regression modeling approaches. This statistical analysis consists of: (1) a heuristic algorithm for spike train extraction, (2) an exploratory analysis in combination with suitable pre-processing to highlight features of the data and (3) a regression analysis based on zero-adjusted generalized additive linear models for location, scale and shape to relate the spike trains to stimuli and sessions as well as inspect their evolvement over time. Results indicate how the flexibility of advanced regression modeling approaches allows to account for specific data structures as well as easily compare different modeling approaches.

关键词： Exploratory analysis GAMLSS semi-parametric regression model Spike train extraction Zero-adjusted distribution

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Nonlinear regression on Growth Curves for Placental Parameters in R 3rd

Nonlinear Regression on Growth Curves for Placental Paramete...

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3rd International Conference on Optimization, Learning Algorithms and Applications (OL2A)

作者： Lemos, Daniela Braga, Ana Cristina Nogueira, Rosete Univ Minho Sch Engn P-4710057 Braga Portugal Univ Minho ALGORITMI Res Ctr LASI Campus Gualtar P-4710057 Braga Portugal Life & Hlth Sci Res Inst ICVS ICVS 3Bs PT Govt Associate Lab Campus Gualtar P-4710057 Braga Portugal Embryofetal Pathol Lab Unilabs CGC Genet R Sa da Bandeira 7061o P-4000431 Porto Portugal

ISBN: (纸本)9783031530241;9783031530258

Growth charts play a crucial role in the evaluation and surveillance of paediatric populations, serving as indispensable tools for paediatricians and public health researchers. The development of these growth charts for fetal parameters has been extensively used in recent decades. However, investigation of placental parameters and their relationship with obstetric outcome has been relatively neglected, resulting in a significant gap in understanding their biological significance. This study presents an alternative approach for constructing reference growth curves specific to the placental parameter, Diameter 2. Our methodology uses the generalized additive models for location, scale, and shape (GAMLSS), offering distinct advantages over traditional quantile regression methods. One of the key advantages of GAMLSS is its flexibility to accommodate any statistical distribution, allowing for the modelling of various parameters that characterize the distribution of the response variable. Through the application of our proposed methodology, we demonstrated that by using P-splines as a smoothing function and Box-Cox t (BCT) as a distribution, we can achieve a representative growth curve for the Diameter 2 of the placenta throughout gestational age (GA). The resulting models demonstrated high representativeness, with R-2 values of 0.7608 and 0.7673 and AIC scores of 7953 and 7946 for the best two models, respectively. Moreover, our approach has the ultimate goal to facilitate early diagnosis of fetal complications, thereby providing valuable assistance to healthcare professionals.

关键词： Placenta Growth curves Non-linear semi-parametric regression model Smoothing functions Distributions GAMLSS LMS

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Exploring the effective way of reducing carbon intensity in the heavy industry using a semiparametric econometric approach

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ENERGY 2022年第0期243卷 123066-123066页

作者： Xu, Renjing Xu, Bin Nanchang Inst Technol Sch Foreign Language Nanchang 330013 Jiangxi Peoples R China Xiamen Univ China Inst Studies Energy Policy Collaborat Innovat Ctr Energy Econ & Energy Policy Sch Management Xiamen 361005 Fujian Peoples R China Xiamen Univ China Inst Studies Energy Policy Sch Management Xiamen 361005 Fujian Peoples R China

China has promised that by 2030, its carbon intensity will be cut down by about 60%. The purpose of this article is to investigate the main influencing factors of the heavy industry's carbon intensity. Different from the existing related literature, this article uses a semiparametric model to empirically analyze the carbon intensity of China's heavy industry. The main results are as follows: (1) the relationship between spatial agglomeration and carbon intensity shows a non-linear pattern, mainly caused by the cross regional flow of production factors. (2) The impact of technological progress on carbon intensity also displays significant non-linear characteristics, mainly due to the staged differences in research and development investment. The following three factors are linearly related to carbon intensity. (1) Energy consumption structure has a more significant linear impact on the carbon intensity in the central and eastern regions, due to the heavy coal consumption of the heavy industry in these two regions. (2) The linear impact of environmental regulations on the carbon intensity in the eastern region is more significant, owing to the region's considerable investments in environmental governance. (3) The industrial structure has the most significant linear impact on the carbon intensity in the eastern region, since the scale of the tertiary industry in this region is larger. The conclusions can provide empirical support for local government managers to formulate differentiated energy policies.(c) 2022 Elsevier Ltd. All rights reserved.

关键词： Driving factors Carbon intensity The heavy industry semi-parametric regression model

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Cattle reference growth curves based on centile estimation: A GAMLSS approach

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2022年 192卷 106572-106572页

作者： Nakamura, Luiz R. Ramires, Thiago G. Righetto, Ana J. Pescim, Rodrigo R. Roquim, Fernanda, V Savian, Taciana, V Stasinopoulos, Dimitrios M. Univ Fed Santa Catarina Dept Informat & Estat 274 Roberto Sampaio Gonzaga St BR-88040380 Florianopolis SC Brazil Univ Tecnol Fed Parana Dept Matemat 635 Marcilio Dias St BR-86812460 Apucarana Parana Brazil Alvaz Agritech 20 Jose Giroldo St BR-86050268 Londrina Parana Brazil Univ Estadual Londrina Dept Estat 380 Celso Garcia Cid RdCampus Univ BR-86057970 Londrina Parana Brazil Univ Fed Lavras Programa Posgrad Estat & Expt Agr BR-37200900 Lavras MG Brazil Univ Sao Paulo Escola Super Agr Luiz de Queiroz Dept Ciencias Exatas 235 Padua Dias Av BR-13418900 Piracicaba SP Brazil London Metropolitan Univ STORM Sch Comp 166-220 Holloway Rd London N7 8DB England

In this paper we provide an alternative to create reference growth curves for female Hereford cattle breed based on the generalized additive models for location, scale and shape (GAMLSS) framework. The proposed methodology avoids some known problems present in the quantile regression, such as crossing quantiles and unsuitability in extreme centiles. Since GAMLSS are semi-parametric regression-type models, any statistical distribution can be considered to explain the behaviour of a given response variable (e.g., body weight) and we are able to model any and all of the parameters of the response variable distribution, it can easily deal with highly complex growth curves (e.g., presenting multiple cycles), heteroskedasticity and skewed data issues, commonly present in this field. We apply the abovementioned methodology, showing that the animal age directly affects median, variability and skewness characteristics of its growth curve. Finally, this approach may be applied in any other animal or plant growth, and it can be used as a powerful decision-making tool by producers.

关键词： Animal breeding Hereford cattle Multiphasic growth curve semi-parametric regression model Statistical learning

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Advanced topics in Sliced Inverse regression

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JOURNAL OF MULTIVARIATE ANALYSIS 2022年 188卷

作者： Girard, Stephane Lorenzo, Hadrien Saracco, Jerome Univ Grenoble Alpes INRIA CNRS Grenoble INPLJK F-38000 Grenoble France Univ Bordeaux CNRS Bordeaux INP IMBUMR 5251 F-33400 Talence France INRIA IMB UMR 5251 F-33400 Talence France

Since its introduction in the early 90s, the Sliced Inverse regression (SIR) methodology has evolved adapting to increasingly complex data sets in contexts combining linear dimension reduction with non linear regression. The assumption of dependence of the response variable with respect to only a few linear combinations of the covariates makes it appealing for many computational and real data application aspects. This work proposes an overview of the most active research directions in SIR modeling from multivariate regression models to regularization and variable selection. (C) 2021 Elsevier Inc. All rights reserved.

关键词： Curse of dimensionality Multivariate response Regularization semi-parametric regression model Sufficient dimension reduction Variable selection

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Wavelet Estimation in a semi-parametric regression model With ρ-mixing Errors

Wavelet Estimation in a Semi-parametric Regression Model Wit...

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2012 IEEE International Conference on Engineering Technology and Economic Management（ICETEM2012）

作者： CHANG Zhenhai and LIU Wei School of Mathematics and Statistics Tianshui Normal University Tianshui China

This paper considers a semi-par ametric regression model with fixed design points,whose errors are a stationary r-mixing *** estimators of unknown parameter and non-parameter are derived by the wavelet *** proper cond... 详细信息

关键词： semi-parametric regression model wavelet estimation ρ-mixing convergence rate consistency

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Research on Influence Factors ofIP Movie Box Office Based on semi-parametric model 9

Research on Influence Factors ofIP Movie Box Office Based on...

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9th IEEE International Conference on Software Engineering and Service Science (ICSESS)

作者： Hua, Yao Li, Bo Ren, Jinluan Yan, Haoyue Commun Univ China Fac Sci & Technol Beijing Peoples R China Commun Univ China Beijing Peoples R China

ISBN: (纸本)9781538665657

Through the establishment of a semi-parametric regression model, an empirical analysis of the influencing factors of the IP movie box office was conducted. The results of the study showed that: the fitting result of the semi-parametric regression model is better than that of the general linear regression model;the film type, attention degree, IP influence and the box office of the movie show a significant positive linear relationship, among which the degree of attention and influence of the IP influence most;the influence of the main creative team, IP scores and the movie box office are nonlinear, and the nonlinear part is visualized.

关键词： semi-parametric regression model Nonlinear IP movie box office

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INFERENCE IN semi-parametric DYNAMIC modelS FOR REPEATED COUNT DATA

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AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS 2016年第3期58卷 397-434页

作者： Sutradhar, Brajendra C. Warriyar, K. V. Vineetha Zheng, Nan Mem Univ Dept Math & Stat St John NF A1C 5S7 Canada

This paper deals with a longitudinal semi-parametric regression model in a generalised linear model setup for repeated count data collected from a large number of independent individuals. To accommodate the longitudinal correlations, we consider a dynamic model for repeated counts which has decaying auto-correlations as the time lag increases between the repeated responses. The semi-parametric regression function involved in the model contains a specified regression function in some suitable time-dependent covariates and a non-parametric function in some other time-dependent covariates. As far as the inference is concerned, because the non-parametric function is of secondary interest, we estimate this function consistently using the independence assumption-based well-known quasilikelihood approach. Next, the proposed longitudinal correlation structure and the estimate of the non-parametric function are used to develop a semi-parametric generalised quasilikelihood approach for consistent and efficient estimation of the regression effects in the parametric regression function. The finite sample performance of the proposed estimation approach is examined through an intensive simulation study based on both large and small samples. Both balanced and unbalanced cluster sizes are incorporated in the simulation study. The asymptotic performances of the estimators are given. The estimation methodology is illustrated by reanalysing the well-known health care utilisation data consisting of counts of yearly visits to a physician by 180 individuals for four years and several important primary and secondary covariates.

关键词： consistency of the estimators dynamic model for repeated counts improved efficiency mean squared error consistency and efficiency non-parametric function non-stationary correlations semi-parametric generalised quasi-likelihood estimation semi-parametric regression model

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