期刊文献+
共找到556篇文章
< 1 2 28 >
每页显示 20 50 100
Remaining useful life prediction based on nonlinear random coefficient regression model with fusing failure time data 被引量:1
1
作者 WANG Fengfei TANG Shengjin +3 位作者 SUN Xiaoyan LI Liang YU Chuanqiang SI Xiaosheng 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2023年第1期247-258,共12页
Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a n... Remaining useful life(RUL) prediction is one of the most crucial elements in prognostics and health management(PHM). Aiming at the imperfect prior information, this paper proposes an RUL prediction method based on a nonlinear random coefficient regression(RCR) model with fusing failure time data.Firstly, some interesting natures of parameters estimation based on the nonlinear RCR model are given. Based on these natures,the failure time data can be fused as the prior information reasonably. Specifically, the fixed parameters are calculated by the field degradation data of the evaluated equipment and the prior information of random coefficient is estimated with fusing the failure time data of congeneric equipment. Then, the prior information of the random coefficient is updated online under the Bayesian framework, the probability density function(PDF) of the RUL with considering the limitation of the failure threshold is performed. Finally, two case studies are used for experimental verification. Compared with the traditional Bayesian method, the proposed method can effectively reduce the influence of imperfect prior information and improve the accuracy of RUL prediction. 展开更多
关键词 remaining useful life(RUL)prediction imperfect prior information failure time data nonlinear random coefficient regression(RCR)model
下载PDF
Smoothed Empirical Likelihood Inference for Nonlinear Quantile Regression Models with Missing Response
2
作者 Honghua Dong Xiuli Wang 《Open Journal of Applied Sciences》 2023年第6期921-933,共13页
In this paper, three smoothed empirical log-likelihood ratio functions for the parameters of nonlinear models with missing response are suggested. Under some regular conditions, the corresponding Wilks phenomena are o... In this paper, three smoothed empirical log-likelihood ratio functions for the parameters of nonlinear models with missing response are suggested. Under some regular conditions, the corresponding Wilks phenomena are obtained and the confidence regions for the parameter can be constructed easily. 展开更多
关键词 nonlinear model Quantile regression Smoothed Empirical Likelihood Missing at Random
下载PDF
ON CONFIDENCE REGIONS OF SEMIPARAMETRIC NONLINEAR REGRESSION MODELS(A GEOMETRIC APPROACH) 被引量:3
3
作者 朱仲义 唐年胜 韦博成 《Acta Mathematica Scientia》 SCIE CSCD 2000年第1期68-75,共8页
A geometric framework is proposed for semiparametric nonlinear regression models based on the concept of least favorable curve, introduced by Severini and Wong (1992). The authors use this framework to drive three kin... A geometric framework is proposed for semiparametric nonlinear regression models based on the concept of least favorable curve, introduced by Severini and Wong (1992). The authors use this framework to drive three kinds of improved approximate confidence regions for the parameter and parameter subset in terms of curvatures. The results obtained by Hamilton et al. (1982), Hamilton (1986) and Wei (1994) are extended to semiparametric nonlinear regression models. 展开更多
关键词 confidence regions CURVATURES nonlinear regression models score statistic semiparametric models
下载PDF
CONSERVATIVE ESTIMATING FUNCTION IN THE NONLINEAR REGRESSION MODEL WITH AGGREGATED DATA 被引量:1
4
作者 林路 《Acta Mathematica Scientia》 SCIE CSCD 2000年第3期335-340,共6页
The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When thi... The purpose of this paper is to study the theory of conservative estimating functions in nonlinear regression model with aggregated data. In this model, a quasi-score function with aggregated data is defined. When this function happens to be conservative, it is projection of the true score function onto a class of estimation functions. By constructing, the potential function for the projected score with aggregated data is obtained, which have some properties of log-likelihood function. 展开更多
关键词 nonlinear regression model with aggregated data quasi-score function conservative vector field potential function
下载PDF
CBPS-Based Inference in Nonlinear Regression Models with Missing Data 被引量:1
5
作者 Donglin Guo Liugen Xue Haiqing Chen 《Open Journal of Statistics》 2016年第4期675-684,共11页
In this article, to improve the doubly robust estimator, the nonlinear regression models with missing responses are studied. Based on the covariate balancing propensity score (CBPS), estimators for the regression coef... In this article, to improve the doubly robust estimator, the nonlinear regression models with missing responses are studied. Based on the covariate balancing propensity score (CBPS), estimators for the regression coefficients and the population mean are obtained. It is proved that the proposed estimators are asymptotically normal. In simulation studies, the proposed estimators show improved performance relative to usual augmented inverse probability weighted estimators. 展开更多
关键词 nonlinear regression model Missing at Random Covariate Balancing Propensity Score GMM Augmented Inverse Probability Weighted
下载PDF
TESTING OF CORRELATION AND HETEROSCEDASTICITY IN NONLINEAR REGRESSION MODELS WITH DBL(p,q,1) RANDOM ERRORS
6
作者 刘应安 韦博成 《Acta Mathematica Scientia》 SCIE CSCD 2008年第3期613-632,共20页
Chaos theory has taught us that a system which has both nonlinearity and random input will most likely produce irregular data. If random errors are irregular data, then random error process will raise nonlinearity (K... Chaos theory has taught us that a system which has both nonlinearity and random input will most likely produce irregular data. If random errors are irregular data, then random error process will raise nonlinearity (Kantz and Schreiber (1997)). Tsai (1986) introduced a composite test for autocorrelation and heteroscedasticity in linear models with AR(1) errors. Liu (2003) introduced a composite test for correlation and heteroscedasticity in nonlinear models with DBL(p, 0, 1) errors. Therefore, the important problems in regression model axe detections of bilinearity, correlation and heteroscedasticity. In this article, the authors discuss more general case of nonlinear models with DBL(p, q, 1) random errors by score test. Several statistics for the test of bilinearity, correlation, and heteroscedasticity are obtained, and expressed in simple matrix formulas. The results of regression models with linear errors are extended to those with bilinear errors. The simulation study is carried out to investigate the powers of the test statistics. All results of this article extend and develop results of Tsai (1986), Wei, et al (1995), and Liu, et al (2003). 展开更多
关键词 DBL(p Q 1) random errors nonlinear regression models score test HETEROSCEDASTICITY CORRELATION
下载PDF
Responses of River Runoff to Climate Change Based on Nonlinear Mixed Regression Model in Chaohe River Basin of Hebei Province, China
7
作者 JIANG Yan LIU Changming +2 位作者 ZHENG Hongxing LI Xuyong WU Xianing 《Chinese Geographical Science》 SCIE CSCD 2010年第2期152-158,共7页
Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature ... Taking the nonlinear nature of runoff system into account,and combining auto-regression method and multi-regression method,a Nonlinear Mixed Regression Model (NMR) was established to analyze the impact of temperature and precipitation changes on annual river runoff process. The model was calibrated and verified by using BP neural network with observed meteorological and runoff data from Daiying Hydrological Station in the Chaohe River of Hebei Province in 1956–2000. Compared with auto-regression model,linear multi-regression model and linear mixed regression model,NMR can improve forecasting precision remarkably. Therefore,the simulation of climate change scenarios was carried out by NMR. The results show that the nonlinear mixed regression model can simulate annual river runoff well. 展开更多
关键词 river runoff runoff forecast nonlinear mixed regression model linear multi-regression model linear mixed regression model BP neural network
下载PDF
Geometric Properties of AR(q) Nonlinear Regression Models
8
作者 LIUYing-ar WEIBo-cheng 《Chinese Quarterly Journal of Mathematics》 CSCD 2004年第2期146-154,共9页
This paper is devoted to a study of geometric properties of AR(q) nonlinear regression models. We present geometric frameworks for regression parameter space and autoregression parameter space respectively based on th... This paper is devoted to a study of geometric properties of AR(q) nonlinear regression models. We present geometric frameworks for regression parameter space and autoregression parameter space respectively based on the weighted inner product by fisher information matrix. Several geometric properties related to statistical curvatures are given for the models. The results of this paper extended the work of Bates & Watts(1980,1988)[1.2] and Seber & Wild (1989)[3]. 展开更多
关键词 nonlinear regression model AR(q) errors geometric framework statistical curvature Fisher information matrix
下载PDF
Local Curvature and Centering Effects in Nonlinear Regression Models
9
作者 Michael Brimacombe 《Open Journal of Statistics》 2016年第1期76-84,共9页
The effects of centering response and explanatory variables as a way of simplifying fitted linear models in the presence of correlation are reviewed and extended to include nonlinear models, common in many biological ... The effects of centering response and explanatory variables as a way of simplifying fitted linear models in the presence of correlation are reviewed and extended to include nonlinear models, common in many biological and economic applications. In a nonlinear model, the use of a local approximation can modify the effect of centering. Even in the presence of uncorrelated explanatory variables, centering may affect linear approximations and related test statistics. An approach to assessing this effect in relation to intrinsic curvature is developed and applied. Mis-specification bias of linear versus nonlinear models also reflects this centering effect. 展开更多
关键词 nonlinear regression Centering Data model Mis-Specification BIAS CURVATURE
下载PDF
Small-time scale network traffic prediction based on a local support vector machine regression model 被引量:10
10
作者 孟庆芳 陈月辉 彭玉华 《Chinese Physics B》 SCIE EI CAS CSCD 2009年第6期2194-2199,共6页
In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the... In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements. 展开更多
关键词 network traffic small-time scale nonlinear time series analysis support vector machine regression model
下载PDF
Regression Modeling of Individual-Patient Correlated Discrete Outcomes with Applications to Cancer Pain Ratings 被引量:1
11
作者 George J. Knafl Salimah H. Meghani 《Open Journal of Statistics》 2022年第4期456-485,共30页
Purpose: To formulate and demonstrate methods for regression modeling of probabilities and dispersions for individual-patient longitudinal outcomes taking on discrete numeric values. Methods: Three alternatives for mo... Purpose: To formulate and demonstrate methods for regression modeling of probabilities and dispersions for individual-patient longitudinal outcomes taking on discrete numeric values. Methods: Three alternatives for modeling of outcome probabilities are considered. Multinomial probabilities are based on different intercepts and slopes for probabilities of different outcome values. Ordinal probabilities are based on different intercepts and the same slope for probabilities of different outcome values. Censored Poisson probabilities are based on the same intercept and slope for probabilities of different outcome values. Parameters are estimated with extended linear mixed modeling maximizing a likelihood-like function based on the multivariate normal density that accounts for within-patient correlation. Formulas are provided for gradient vectors and Hessian matrices for estimating model parameters. The likelihood-like function is also used to compute cross-validation scores for alternative models and to control an adaptive modeling process for identifying possibly nonlinear functional relationships in predictors for probabilities and dispersions. Example analyses are provided of daily pain ratings for a cancer patient over a period of 97 days. Results: The censored Poisson approach is preferable for modeling these data, and presumably other data sets of this kind, because it generates a competitive model with fewer parameters in less time than the other two approaches. The generated probabilities for this model are distinctly nonlinear in time while the dispersions are distinctly nonconstant over time, demonstrating the need for adaptive modeling of such data. The analyses also address the dependence of these daily pain ratings on time and the daily numbers of pain flares. Probabilities and dispersions change differently over time for different numbers of pain flares. Conclusions: Adaptive modeling of daily pain ratings for individual cancer patients is an effective way to identify nonlinear relationships in time as well as in other predictors such as the number of pain flares. 展开更多
关键词 Cancer Pain Ratings Discrete regression Extended Linear Mixed modeling Likelihood-Like Cross-Validation nonlinear Moderation
下载PDF
GEOMETRY OF EXPONENTIAL TYPE REGRESSION MODELS AND ITS ASYMPTOTIC INFERENCE
12
作者 韦博成 马阳明 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 1993年第2期182-197,共16页
In this paper, exponential type regression models are considered from geometric point of view. The stochastic expansions relating to the estimate are derived and are used to study several asymptotic inference problems... In this paper, exponential type regression models are considered from geometric point of view. The stochastic expansions relating to the estimate are derived and are used to study several asymptotic inference problems. The biases and the covariances relating to the estimate may be calculated based on the expansions. The information loss of the estimate and a limit theorem connected with the observed and expected Fisher informations are obtained in terms of the curvatures. 展开更多
关键词 Exponential Type regression Exponential Family nonlinear models Stochastic Expansion CURVATURE Information.
下载PDF
Simulation Program to Determine Sample Size and Power for a Multiple Logistic Regression Model with Unspecified Covariate Distributions
13
作者 Naoko Kumagai Kohei Akazawa +2 位作者 Hiromi Kataoka Yutaka Hatakeyama Yoshiyasu Okuhara 《Health》 2014年第21期2973-2998,共26页
Binary logistic regression models are commonly used to assess the association between outcomes and covariates. Many covariates are inherently continuous, and have a variety of distributions, including those that are h... Binary logistic regression models are commonly used to assess the association between outcomes and covariates. Many covariates are inherently continuous, and have a variety of distributions, including those that are heavily skewed to the left or right. Existing theoretical formulas, criteria, and simulation programs cannot accurately estimate the sample size and power of non-standard distributions. Therefore, we have developed a simulation program that uses Monte Carlo methods to estimate the exact power of a binary logistic regression model. This power calculation can be used for distributions of any shape and covariates of any type (continuous, ordinal, and nominal), and can account for nonlinear relationships between covariates and outcomes. For illustrative purposes, this simulation program is applied to real data obtained from a study on the influence of smoking on 90-day outcomes after acute atherothrombotic stroke. Our program is applicable to all effect sizes and makes it possible to apply various statistical methods, logistic regression and related simulations such as Bayesian inference with some modifications. 展开更多
关键词 LOGISTIC regression model MONTE Carlo Simulation Non-Standard DISTRIBUTIONS nonlinear POWER SAMPLE Size Skewed Distribution
下载PDF
Diagnostics in generalized nonlinear models based on maximum L_q-likelihood estimation 被引量:1
14
作者 徐伟娟 林金官 《Journal of Southeast University(English Edition)》 EI CAS 2013年第1期106-110,共5页
In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood e... In order to detect whether the data conforms to the given model, it is necessary to diagnose the data in the statistical way. The diagnostic problem in generalized nonlinear models based on the maximum Lq-likelihood estimation is considered. Three diagnostic statistics are used to detect whether the outliers exist in the data set. Simulation results show that when the sample size is small, the values of diagnostic statistics based on the maximum Lq-likelihood estimation are greater than the values based on the maximum likelihood estimation. As the sample size increases, the difference between the values of the diagnostic statistics based on two estimation methods diminishes gradually. It means that the outliers can be distinguished easier through the maximum Lq-likelihood method than those through the maximum likelihood estimation method. 展开更多
关键词 maximum Lq-likelihood estimation generalized nonlinear regression model case-deletion model generalized Cook distance likelihood distance difference of deviance
下载PDF
TESTING FOR VARYING DISPERSION OF LONGITUDINAL BINOMIAL DATA IN NONLINEAR LOGISTIC MODELS WITH RANDOM EFFECTS 被引量:2
15
作者 林金官 韦博成 《Acta Mathematica Scientia》 SCIE CSCD 2004年第4期559-568,共10页
In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. O... In this paper, it is discussed that two tests for varying dispersion of binomial data in the framework of nonlinear logistic models with random effects, which are widely used in analyzing longitudinal binomial data. One is the individual test and power calculation for varying dispersion through testing the randomness of cluster effects, which is extensions of Dean(1992) and Commenges et al (1994). The second test is the composite test for varying dispersion through simultaneously testing the randomness of cluster effects and the equality of random-effect means. The score test statistics are constructed and expressed in simple, easy to use, matrix formulas. The authors illustrate their test methods using the insecticide data (Giltinan, Capizzi & Malani (1988)). 展开更多
关键词 Longitudinal binomial data logistic regression nonlinear models power calculation random effects score test varying dispersion
下载PDF
Mathematical modelling of nonlinear behaviour of seismicity
16
作者 杨立明 石特临 郭大庆 《Acta Seismologica Sinica(English Edition)》 CSCD 1995年第2期223-232,共10页
In this paper,the nonlinear behaviour of seismic activities has been studied by means of the threshold autoregressive model and the exponential autoregressive model. The contents are as follows: ① The theories and m... In this paper,the nonlinear behaviour of seismic activities has been studied by means of the threshold autoregressive model and the exponential autoregressive model. The contents are as follows: ① The theories and modelling methods of this two models have been studied.② One kind of explanation for the seismic cycle and order structure are given by means of the threshold autoregressive model.③ According to the exponential autoregressive model,an inherent structure of the magnitude series are discussed,the different relations between magnitude and frequency in active period and quiet period are also explained in this paper. 展开更多
关键词 threshold regression model SEISMICITY nonlinear evolution
下载PDF
Heteroscedasticity check in nonlinear semiparametric models based on nonparametric variance function
17
作者 QU Xiao-yi LIN Jin-guan 《Applied Mathematics(A Journal of Chinese Universities)》 SCIE CSCD 2008年第4期401-409,共9页
The assumption of homoscedasticity has received much attention in classical analysis of regression. Heteroscedasticity tests have been well studied in parametric and nonparametric regressions. The aim of this paper is... The assumption of homoscedasticity has received much attention in classical analysis of regression. Heteroscedasticity tests have been well studied in parametric and nonparametric regressions. The aim of this paper is to present a test of heteroscedasticity for nonlinear semiparametric regression models with nonparametric variance function. The validity of the proposed test is illustrated by two simulated examples and a real data example. 展开更多
关键词 heteroscedasticity check nonlinear semiparametric regression model asymptotic normality nonparametric variance function
下载PDF
老年人对信号交叉口行人服务水平评价建模与分析
18
作者 张惠玲 王瑞浩 张睿 《郑州大学学报(工学版)》 CAS 北大核心 2024年第6期9-17,共9页
为分析老年人在信号交叉口人行横道的过街需求,对老年行人在通行时的服务水平进行评估,建立了基于主观评价和交叉口交通特征的老年行人服务水平评价模型。首先,通过现场观测和视频分析获取了33条信号控制人行横道的交通特征参数,并采用... 为分析老年人在信号交叉口人行横道的过街需求,对老年行人在通行时的服务水平进行评估,建立了基于主观评价和交叉口交通特征的老年行人服务水平评价模型。首先,通过现场观测和视频分析获取了33条信号控制人行横道的交通特征参数,并采用截断式问卷调查得到同步情况下过街老年人对行人服务水平评价主观值,初步选用基于非线性、线性和模糊线性回归模型。其次,通过基于30条人行横道的数据分析,采用皮尔逊相关系数和斯皮尔曼相关系数识别出了影响老年人过街服务水平的关键因素。最后,以关键因素为输入,对比分析非线性、线性和模糊线性3种回归模型,结果表明:多元非线性回归的老年行人服务水平评价模型在拟合度和误差方面表现更优,且验证组的3条人行横道数据进一步证实了该模型的适用性。 展开更多
关键词 信号交叉口 老年行人 多元非线性回归模型 行人服务水平 建模与分析
下载PDF
基于“灰色+非线性回归”的煤矿死亡人数预测
19
作者 景国勋 卢一瑾 +2 位作者 王远声 郭绍帅 彭乐 《安全与环境学报》 CAS CSCD 北大核心 2024年第5期1922-1929,共8页
为探究我国煤矿现阶段安全管理水平,从煤矿近年死亡人数为切入点,分析灰色模型[Gray Model, GM(1,1)]、回归模型在煤矿事故的预测效果,进而建立“灰色+回归”模型。首先,建立灰色模型,利用后残差比值、小概率误差验证灰色模型的预测等... 为探究我国煤矿现阶段安全管理水平,从煤矿近年死亡人数为切入点,分析灰色模型[Gray Model, GM(1,1)]、回归模型在煤矿事故的预测效果,进而建立“灰色+回归”模型。首先,建立灰色模型,利用后残差比值、小概率误差验证灰色模型的预测等级为“好”,满足改进要求;其次,对回归模型进行线性拟合,建立“灰色+回归”预测模型,并对3类模型的预测准确性进行评估;最后,利用“灰色+非线性回归”模型预测2023年煤矿死亡人数。结果显示:以2021—2022年数据为基准,“灰色+非线性回归”预测相对误差依次为4.5%和1.3%,预测结果接近实际值,适用于短中期预测;经分析,“灰色+非线性回归”对煤矿死亡人数预测具有较高的研究价值。2023年煤矿死亡人数控制在123~136人,煤矿死亡人数呈下降趋势。 展开更多
关键词 安全工程 死亡人数 灰色模型 “灰色+非线性回归”模型 事故预测
下载PDF
基于混合效应模型的相容性削度-材积方程研究
20
作者 李春明 《西北林学院学报》 CSCD 北大核心 2024年第2期210-216,共7页
为构建一个能够准确估计树干从地面到任意部位高度的直径和材积的相容性削度-材积方程,以吉林省汪清林业局金沟岭林场的冷杉解析木数据为例,选择基于材积比方程和基于积分方法这2种方法来构建相容性削度-材积方程系统。在模拟时,采用3... 为构建一个能够准确估计树干从地面到任意部位高度的直径和材积的相容性削度-材积方程,以吉林省汪清林业局金沟岭林场的冷杉解析木数据为例,选择基于材积比方程和基于积分方法这2种方法来构建相容性削度-材积方程系统。在模拟时,采用3种参数估计方法来估计2个系统中的削度方程、全树干材积和商品材材积方程的参数,并考虑样木间的随机效应。选择均方根误差和平均绝对残差等指标,对精度进行比较。最后发展出一个能够准确预测树干任意高度的直径、全树干材积和商品材材积的相容性削度-材积方程系统。结果表明,在2个相容性削度-材积系统中,采用削度方程参数估计方法提供了商品材材积和全树干材积的最差预测,似乎不相关参数方法在材积比方程方法构建的相容性削度-材积方程系统中的精度最高,商品材材积参数方法在积分方法构建的相容性削度-材积方程系统中的精度最高。2个相容性削度-材积系统中无论采用商品材材积参数估计方法还是削度方程参数估计方法,在考虑单木的随机效应后,模型的模拟和验证效果都得到很大的提高。基于积分方法的相容性削度-材积方程系统的模拟和验证精度要高于基于材积比方程方法的相容性削度-材积方程系统的模拟和验证精度。总体来说,相容性削度-材积方程系统可以保证削度方程、商品材材积方程和全树干材积方程在形式和算法上相容。 展开更多
关键词 削度方程 相容性削度-材积方程 非线性似乎不相关回归 混合效应模型 商品材材积
下载PDF
上一页 1 2 28 下一页 到第
使用帮助 返回顶部