Change Point Estimation Using Nonparametric Regression
نویسنده
چکیده
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use.
منابع مشابه
Nonparametric Regression Estimation under Kernel Polynomial Model for Unstructured Data
The nonparametric estimation(NE) of kernel polynomial regression (KPR) model is a powerful tool to visually depict the effect of covariates on response variable, when there exist unstructured and heterogeneous data. In this paper we introduce KPR model that is the mixture of nonparametric regression models with bootstrap algorithm, which is considered in a heterogeneous and unstructured framewo...
متن کاملA MODIFICATION ON RIDGE ESTIMATION FOR FUZZY NONPARAMETRIC REGRESSION
This paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. This estimation method is obtained by implementing ridge regression learning algorithm in the La- grangian dual space. The distance measure for fuzzy numbers that suggested by Diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...
متن کاملEstimating the Time of a Step Change in Gamma Regression Profiles Using MLE Approach
Sometimes the quality of a process or product is described by a functional relationship between a response variable and one or more explanatory variables referred to as profile. In most researches in this area the response variable is assumed to be normally distributed; however, occasionally in certain applications, the normality assumption is violated. In these cases the Generalized Linear Mod...
متن کاملNonparametric Threshold Regression: Estimation and Inference∗
The present work describes a simple approach to estimating the location of a threshold/change point in a nonparametric regression. This model has connections both to the time-series and regression discontinuity literatures. The estimator leverages a simple decomposition, giving it the form of a semiparametric smooth coefficient model. Optimal bandwidth selection and a suite of testing facilitie...
متن کاملVariance Estimation in Ranked Set Sampling Using a Concomitant Variable
We propose a nonparametric variance estimator when ranked set sampling (RSS) and judgment post stratification (JPS) are applied by measuring a concomitant variable. Our proposed estimator is obtained by conditioning on observed concomitant values and using nonparametric kernel regression.
متن کاملFeasible Multivariate Nonparametric Regression Estimation Using Weak Separability
One of the main practical problems of nonparametric regression estimation is the curse of dimensionality. The curse of dimensionality arises because nonparametric regression estimates are dependent variable averages local to the point at which the regression function is to be estimated. The number of observations ‘local’ to the point of estimation decreases exponentially with the number of dime...
متن کامل