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Strong Convergence and Its Rate of Modified Partitioning Estimation for Nonparametric Regression Function under Dependence Samples 认领 引用 被引量：5
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作者 凌能祥 《Northeastern Mathematical Journal》 2004年第3期349-354,共6页
In this paper, we study the strong consistency and convergence rate for modified partitioning estimation of regression function under samples that are ψ-mixing with identically distribution.
关键词 partitioning esfimation strong convergence convergence rate nonpara-metric regression function ψ-mixing
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On the L_p Convergence Rate of Kernel Estimates for the Nonparametric Regression Function 认领 引用
2
作者 薛留根 《Chinese Quarterly Journal of Mathematics》 1992年第1期37-43,共7页
Let (X,Y) be an R^d×R^1 valued random vector (X_1,Y_1),…, (X_n,Y_n) be a random sample drawn from (X,Y), and let E|Y|<∞. The regression function m(x)=E(Y|X=x) for x∈R^d is estimated by where, and h_n is a p... Let (X,Y) be an R^d×R^1 valued random vector (X_1,Y_1),…, (X_n,Y_n) be a random sample drawn from (X,Y), and let E|Y|<∞. The regression function m(x)=E(Y|X=x) for x∈R^d is estimated by where, and h_n is a positive number depending upon n only, nad K is a given nonnegative function on R^d. In the paper, we study the L_p convergence rate of kernel estimate m_n(x) of m(x) in suitable condition, and improve and extend the results of Wei Lansheng. 展开更多
关键词 regression function L convergence rate kernel estimate
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Strong Convergence of Partitioning Estimation for Nonparametric Regression Function under Dependence Samples 认领 引用 被引量：7
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作者 LING Neng-xiang DU Xue-qiao 《Chinese Quarterly Journal of Mathematics》 北大核心 2005年第1期28-33,共6页
In this paper, we study the strong consistency for partitioning estimation of regression function under samples that axe φ-mixing sequences with identically distribution.Key words: nonparametric regression function; ... In this paper, we study the strong consistency for partitioning estimation of regression function under samples that axe φ-mixing sequences with identically distribution.Key words: nonparametric regression function; partitioning estimation; strong convergence;φ-mixing sequences. 展开更多
关键词 nonparametric regression function partitioning estimation strong convergence φ-mixing sequences
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THE WAVELET DETECTION OF THE JUMP AND CUSP POINTS OF A REGRESSION FUNCTION 认领 引用 被引量：6
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作者 李元 谢衷洁 《Acta Mathematicae Applicatae Sinica》 2000年第3期283-291,共9页
Wavelets are applied to a regression model with an additive stationary noise. By checking the empirical wavelet coefficients with significantly large absolute values across fine scale levels, the jump points are detec... Wavelets are applied to a regression model with an additive stationary noise. By checking the empirical wavelet coefficients with significantly large absolute values across fine scale levels, the jump points are detected first. Then the cusp points are identified by checking the wavelet coefficients with significantly large absolute values which are secondly large only to the previous wavelet coefficient across fine scale levels. All estimators are shown to be consistent. 展开更多
关键词 Jump and cusp points regression function stationary noises wavelets
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DISTRIBUTION FREE LAWS OF THEITERATED LOGARITHM FOR KERNELESTIMATOR OF REGRESSION FUNCTIONBASED ON DIRECTIONAL DATADISTRIBUTION FREE LAWS OF THEITERATED LOGARITHM FOR KERNELESTIMATOR OF REGRESSION FUNCTIONBASED ON DIRECTIONAL DATA 认领 引用 被引量：2
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作者 WANGXIAOMING ZHAOLINCHENG WUYAOHUA 《Chinese Annals of Mathematics,Series B》 SCIE 2000年第4期489-498,共10页
The authors derive laws of the iterated logarithm for kernel estimator of regression function based on directional data. The results are distribution free in the sense that they are true for all distributions of desig... The authors derive laws of the iterated logarithm for kernel estimator of regression function based on directional data. The results are distribution free in the sense that they are true for all distributions of design variable. 展开更多
关键词 Directional data Laws of the iterated logrithm Regression function kernel estimator Strong convergence rates
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Regression Function Comparison for Paired Data 认领 引用
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作者 GUO Xu ZHANG Jun FANG Yun 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2020年第5期1558-1570,共13页
In this paper,the regression function comparison for paired data is studied.The proposed test statistic is based on the weighted integral of characteristic function marked by the difference of responses.There are seve... In this paper,the regression function comparison for paired data is studied.The proposed test statistic is based on the weighted integral of characteristic function marked by the difference of responses.There are several merits of the proposed statistic.For instance,it takes a simple V-statistic form.No bandwidth is needed.No moment conditions are required for covariates.It can be applied to covariates of any fixed dimension.The asymptotic results are also developed.It is proven that n times the proposed test statistic converges to a finite limit under the null hypothesis and the test is consistent against any fixed alternatives.Local alternative hypotheses which converge to the null hypothesis at the rate of n-1/2 are also detected.A suitable Bootstrap algorithm is also proposed for the implementation of the proposed test statistic.Simulation studies are carried out to illustrate the merits of the proposed method.A real data example is also used to illustrate the proposed testing procedures. 展开更多
关键词 Bootstrap characteristic function paired data regression function comparison V-statistic
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Strong Consistency and Convergence Rate of Modified Partitioning Estimate of Non.p.arametric Regression Function under α-Mixing Sample 认领 引用
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作者 YAO Mei DU Xue Qiao 《Journal of Mathematical Research and Exposition》 北大核心 2008年第3期637-644,共8页
In this paper, we study the strong consistency and convergence partitioning estimate of nonparametric regression function under the sample that is α sequence taking values in R^d × R^1 with identical distributio... In this paper, we study the strong consistency and convergence partitioning estimate of nonparametric regression function under the sample that is α sequence taking values in R^d × R^1 with identical distribution. rate of modified （（Xi,Yi）,i 〉 1} . 展开更多
关键词 nonparametric regression function modified partitioning estimate strong consistency convergence rate α-mixing.
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ASYMPTOTIC NORMALITY OF WAVELET ESTIMATOR IN HETEROSCEDASTIC REGRESSION MODEL 认领 引用 被引量：2
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作者 Liang Hanying Lu Yi 《Applied Mathematics(A Journal of Chinese Universities)》 2007年第4期453-459,共7页
The following heteroscedastic regression model Yi = g（xi） ＋σiei （1 ≤i ≤ n） is 2 considered, where it is assumed that σi^2 = f（ui）, the design points （xi,ui） are known and nonrandom, g and f are unknown fu... The following heteroscedastic regression model Yi = g（xi） ＋σiei （1 ≤i ≤ n） is 2 considered, where it is assumed that σi^2 = f（ui）, the design points （xi,ui） are known and nonrandom, g and f are unknown functions. Under the unobservable disturbance ei form martingale differences, the asymptotic normality of wavelet estimators of g with f being known or unknown function is studied. 展开更多
关键词 regression function martingale difference error wavelet estimator asymptotic normality.
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Functional data analysis-based yield modeling in year-round crop cultivation 认领 引用 被引量：2
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作者 Hidetoshi Matsui Keiichi Mochida 《Horticulture Research》 SCIE CSCD 2024年第7期200-206,共7页
Crop yield prediction is essential for effective agricultural management.We introduce a methodology for modeling the relationship between environmental parameters and crop yield in longitudinal crop cultivation,exempl... Crop yield prediction is essential for effective agricultural management.We introduce a methodology for modeling the relationship between environmental parameters and crop yield in longitudinal crop cultivation,exemplified by strawberry and tomato production based on year-round cultivation.Employing functional data analysis(FDA),we developed a model to assess the impact of these factors on crop yield,particularly in the face of environmental fluctuation.Specifically,we demonstrated that a varying-coefficient functional regression model(VCFRM)is utilized to analyze time-series data,enabling to visualize seasonal shifts and the dynamic interplay between environmental conditions such as solar radiation and temperature and crop yield.The interpretability of our FDA-based model yields insights for optimizing growth parameters,thereby augmenting resource efficiency and sustainability.Our results demonstrate the feasibility of VCFRM-based yield modeling,offering strategies for stable,efficient crop production,pivotal in addressing the challenges of climate adaptability in plant factory-based horticulture. 展开更多
关键词 assess impact factors modeling relationship environmental parameters effective agricultural managementwe varying coefficient functional regression model environmental parameters functional data analysis crop yield prediction functional data analysis fda we
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Real-time and wearable functional electrical stimulation system for volitional hand motor function control using the electromyography bridge method 认领 引用 被引量：6
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作者 Hai-peng Wang Zheng-yang Bi +3 位作者 Yang Zhou Yu-xuan Zhou Zhi-gong Wang Xiao-ying Lv 《Neural Regeneration Research》 SCIE CAS CSCD 2017年第1期133-142,共10页
Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor functio... Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy.A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method.Through a series of novel design concepts,including the integration of a detecting circuit and an analog-to-digital converter,a miniaturized functional electrical stimulation circuit technique,a low-power super-regeneration chip for wireless receiving,and two wearable armbands,a prototype system has been established with reduced size,power,and overall cost.Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects,the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy.Test results showed that wrist flexion/extension,hand grasp,and finger extension could be reproduced with high accuracy and low latency.This system can build a bridge of information transmission between healthy limbs and paralyzed limbs,effectively improve voluntary participation of hemiplegic patients,and elevate efficiency of rehabilitation training. 展开更多
关键词 nerve regeneration functional electrical stimulation logistic regression rehabilitation of upper-limb hemiplegia electromyography control wearable device stroke frequency-modulation stimulation hand motion circuit and system real-time neural regeneration
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Model-Assisted Estimators with Auxiliary Functional Data 认领 引用
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作者 Chao Liu Huiming Zhang Jing Yan 《Communications in Mathematical Research》 CSCD 2022年第1期81-98,共18页
Few studies focus on the application of functional data to the field of design-based survey sampling.In this paper,the scalar-onunction regression model-assisted method is proposed to estimate the finite population me... Few studies focus on the application of functional data to the field of design-based survey sampling.In this paper,the scalar-onunction regression model-assisted method is proposed to estimate the finite population means with auxiliary functional data information.The functional principal component method is used for the estimation of functional linear regression model.Our proposed functional linear regression model-assisted(FLR-assisted)estimator is asymptotically design-unbiased,consistent under mild conditions.Simulation experiments and real data analysis show that the FLR-assisted estimators are more efficient than the Horvitz-Thompson estimators under different sampling designs. 展开更多
关键词 Survey sampling semi-supervised inference model-assisted estimator Horvitz-Thompson estimator functional linear regression
Projective Resampling Functional Sliced Inverse Regression 认领 引用 被引量：2
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作者 QU Wenxin LIANG Beiting WANG Guochang 《Journal of Systems Science & Complexity》 SCIE EI CSCD 2025年第5期2185-2203,共19页
For functional data,the most popular dimension reduction methods are functional sliced inverse regression(FSIR)and functional sliced average variance estimation(FSAVE).Both FSIR and FSAVE methods are based on the slic... For functional data,the most popular dimension reduction methods are functional sliced inverse regression(FSIR)and functional sliced average variance estimation(FSAVE).Both FSIR and FSAVE methods are based on the slice approach to estimate the conditional expectation E[x(t)|y].While sliced-based methods are effective for scalar responses,they often perform poorly or even lead to failure for multivariate responses and small sample sizes as the so-called“curse of dimensionality”.To avoid this problem,this study proposes a projective resampling method that first projects the multivariate response into a scalar-response and then uses SDR method for the univariate response to estimate the effective dimension reduction space(e.d.r space).The proposed projective resampling method is insensitive to the number of slices and the dimensionality of the response variable.In theory,the proposed resampling method can fully recover the effective dimension reduction space.Furthermore,this study investigates the performance of the proposed method through simulation studies and one real data analysis and compares the proposed method with other methods. 展开更多
关键词 Effectivedimension reduction functional sliced inverse regression(FSIR) functional data multivariate response projective resampling
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Estimation of Regression Coefficient in General Regression Model 认领 引用
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作者 Song Lixin 《Northeastern Mathematical Journal》 1995年第3期315-318,共4页
In this poper,we proope a new method for estimating the regression coefficient in a general regression duel based on characteristic functions,which is easier to calcutate than those methods based on Prohorov metric.
关键词 General Regresion Model Regression Coefficient.Chatacteristic Function Prohorov Metric Characteristic Direction
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Research on YOLO algorithm for lightweight PCB defect detection based on MobileViT 认领 引用 被引量：2
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作者 LIU Yuchen LIU Fuzheng JIANG Mingshun 《Optoelectronics Letters》 EI 2025年第8期483-490,共8页
Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order t... Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order to solve this problem,we propose a new method,which combined the lightweight network mobile vision transformer(Mobile Vi T)with the convolutional block attention module(CBAM)mechanism and the new regression loss function.This method needed less computation resources,making it more suitable for embedded edge detection devices.Meanwhile,the new loss function improved the positioning accuracy of the bounding box and enhanced the robustness of the model.In addition,experiments on public datasets demonstrate that the improved model achieves an average accuracy of 87.9%across six typical defect detection tasks,while reducing computational costs by nearly 90%.It significantly reduces the model's computational requirements while maintaining accuracy,ensuring reliable performance for edge deployment. 展开更多
关键词 YOLO lightweight network mobile vision transformer mobile Lightweight Network convolutional block attention module cbam mechanism MobileViT CBAM PCB Defect Detection Regression Loss Function
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Partial functional linear quantile regression 认领 引用 被引量：6
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作者 TANG QingGuo CHENG LongSheng 《Science China Mathematics》 SCIE 2014年第12期2589-2608,共20页
This paper studies estimation in partial functional linear quantile regression in which the dependent variable is related to both a vector of finite length and a function-valued random variable as predictor variables.... This paper studies estimation in partial functional linear quantile regression in which the dependent variable is related to both a vector of finite length and a function-valued random variable as predictor variables. The slope function is estimated by the functional principal component basis. The asymptotic distribution of the estimator of the vector of slope parameters is derived and the global convergence rate of the quantile estimator of unknown slope function is established under suitable norm. It is showed that this rate is optirnal in a minimax sense under some smoothness assumptions on the covariance kernel of the covariate and the slope function. The convergence rate of the mean squared prediction error for the proposed estimators is also established. Finite sample properties of our procedures are studied through Monte Carlo simulations. A real data example about Berkeley growth data is used to illustrate our proposed methodology. 展开更多
关键词 partial functional linear quantile regression quantile estimator functional principal coraponent analysis convergence rate
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平衡损失下回归系数的线性容许估计 认领 引用 被引量：30
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作者 徐兴忠 吴启光 《数学物理学报（A辑）》 北大核心 2000年第4期468-473,共6页
该文在平衡损失函数下 ,研究线性模型中回归系数的线性容许估计 ,得到了充要条件 .结果表明 。
关键词 线性模型 回归系数 平衡损失函数 线性容许估计
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Real-Time Hand Motion Parameter Estimation with Feature Point Detection Using Kinect 认领 引用
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作者 Chun-Ming Chang Che-Hao Chang Chung-Lin Huang 《Journal of Electronic Science and Technology》 CAS 2014年第4期429-433,共5页
This paper presents a real-time Kinect- based hand pose estimation method. Different from model-based and appearance-based approaches, our approach retrieves continuous hand motion parameters in real time. First, the ... This paper presents a real-time Kinect- based hand pose estimation method. Different from model-based and appearance-based approaches, our approach retrieves continuous hand motion parameters in real time. First, the hand region is segmented from the depth image. Then, some specific feature points on the hand are located by the random forest classifier, and the relative displacements of these feature points are transformed to a rotation invariant feature vector. Finally, the system retrieves the hand joint parameters by applying the regression functions on the feature vectors. Experimental results are compared with the ground truth dataset obtained by a data glove to show the effectiveness of our approach. The effects of different distances and different rotation angles for the estimation accuracy are also evaluated. 展开更多
关键词 Hand motion Kinect parameterestimation random forest regression function.
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Developing Weibull-based diameter distributions for the major coniferous species in Heilongjiang Province,China 认领 引用 被引量：6
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作者 Qila Sa Xingji Jin +1 位作者 Timo Pukkala Fengri Li 《Journal of Forestry Research》 SCIE CAS CSCD 2023年第6期1803-1815,共13页
Diameter distribution models play an important role in forest inventories,growth prediction,and management.The Weibull probability density function is widely used in forestry.Although a number of methods have been pro... Diameter distribution models play an important role in forest inventories,growth prediction,and management.The Weibull probability density function is widely used in forestry.Although a number of methods have been proposed to predict or recover the Weibull distribution,their applicability and predictive performance for the major tree species of China remain to be determined.Trees in sample plots of three even-aged coniferous species(Larix olgensis,Pinus sylvestris and Pinus koraiensis)were measured both in un-thinned and thinned stands to develop parameter prediction models for the Weibull probability density function.Ordinary least squares(OLS)and maximum likelihood regression(MLER),as well as cumulative distribution function regression(CDFR)were used,and their performance compared.The results show that MLER and CDFR were better than OLS in predicting diameter distributions of tree plantations.CDFR produced the best results in terms of fitting statistics.Based on the error statistics calculated for different age groups,CDFR was considered the most suitable method for developing prediction models for Weibull parameters in coniferous plantations. 展开更多
关键词 Parameter prediction Maximum likelihood regression Cumulative distribution function regression
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A Gradient Iteration Method for Functional Linear Regression in Reproducing Kernel Hilbert Spaces 认领 引用
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作者 Hongzhi Tong Michael Ng 《Annals of Applied Mathematics》 2022年第3期280-295,共16页
We consider a gradient iteration algorithm for prediction of functional linear regression under the framework of reproducing kernel Hilbert spaces.In the algorithm,we use an early stopping technique,instead of the cla... We consider a gradient iteration algorithm for prediction of functional linear regression under the framework of reproducing kernel Hilbert spaces.In the algorithm,we use an early stopping technique,instead of the classical Tikhonov regularization,to prevent the iteration from an overfitting function.Under mild conditions,we obtain upper bounds,essentially matching the known minimax lower bounds,for excess prediction risk.An almost sure convergence is also established for the proposed algorithm. 展开更多
关键词 Gradient iteration algorithm functional linear regression reproducing kernel Hilbert space early stopping convergence rates
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Nonparametric Regression with Interval-Censored Data 认领 引用 被引量：2
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作者 Wen Li DENG Zu Kang ZHENG Ri Quan ZHANG 《Acta Mathematica Sinica,English Series》 SCIE CSCD 2014年第8期1422-1434,共13页
In many medical studies,the prevalence of interval censored data is increasing due to periodic monitoring of the progression status of a disease.In nonparametric regression model,when the response variable is subjecte... In many medical studies,the prevalence of interval censored data is increasing due to periodic monitoring of the progression status of a disease.In nonparametric regression model,when the response variable is subjected to interval-censoring,the regression function could not be estimated by traditional methods directly.With the censored data,we construct a new response variable which has the same conditional expectation as the original one.Based on the new variable,we get a nearest neighbor estimator of the regression function.It is established that the estimator has strong consistency and asymptotic normality.The relevant simulation reports are given. 展开更多
关键词 Interval-censored data regression function nearest neighbor estimator
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