Bent line quantile regression via a smoothing technique
- MathematicsStat. Anal. Data Min.
A bent line quantile regression model can describe the conditional quantile function of the response variable with two different straight lines, which intersect at an unknown change point. This paper…
Robust continuous piecewise linear regression model with multiple change points
- MathematicsThe Journal of Supercomputing
This paper uses the LARS algorithm via generalized BIC to refine the candidate threshold estimates and obtain the ultimate estimators, which are less sensitive to outliers and heavy-tailed data, and therefore achieves robustness.
Real-time detection of a change-point in a linear expectile model
- MathematicsStatistical Papers
In the present paper we address the real-time detection problem of a change-point in the coefficients of a linear model with the possibility that the model errors are asymmetrical and that the…
Robust Algorithms for Change-Point Regressions Using the t-Distribution
- Computer ScienceMathematics
A modified version of the proposed EMT and FCT, which fits the t change-point regression model to the data after moderately pruning high leverage points, is introduced, and the preference of the t-based approach over normal-based methods for better robustness and computational efficiency is demonstrated.
Estimation and inference for multikink expectile regression with longitudinal data
- MathematicsStatistics in medicine
In this article, parameter estimation, kink points testing and statistical inference for a longitudinal multikink expectile regression model is investigated and the number selection consistency of kinks points and the asymptotic normality of all estimators are demonstrated.
SUGGESTING MULTIPHASE REGRESSION MODEL ESTIMATION WITH SOME THRESHOLD POINT
- Mathematics, Computer ScienceJOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES
The main goal of this paper is to suggest a new hybrid estimator obtained by an ad-hoc algorithm which relies on data driven strategy that overcomes outliers and introduces a new employment of an unweighted estimation method named "winsorization" which is a good method to get robustness in regression estimation via special technique to reduce the effect of the outliers.
Robust algorithms for multiphase regression models
- Computer Science
NEW ROBUST ESTIMATOR OF CHANGE POINT IN SEGMENTED REGRESSION MODEL FOR BED-LOAD OF RIVERS
- MathematicsJOURNAL OF MECHANICS OF CONTINUA AND MATHEMATICAL SCIENCES
Segmentation has vital employment in regression analysis where data have some change point. Traditional estimation methods such as Hudson, D.J.;(1966) and Muggeo, V. M., (2003)have been reviewed .…
SHOWING 1-10 OF 41 REFERENCES
A Lack-of-Fit Test for Quantile Regression
We propose an omnibus lack-of-fit test for linear or nonlinear quantile regression based on a cusum process of the gradient vector. The test does not involve nonparametric smoothing but is consistent…
Testing for Threshold Effects in Regression Models
In this article, we develop a general method for testing threshold effects in regression models, using sup-likelihood-ratio (LR)-type statistics. Although the sup-LR-type test statistic has been…
FURTHER DETAILS ON INFERENCE UNDER RIGHT CENSORING FOR TRANSFORMATION MODELS WITH A CHANGE-POINT BASED ON A COVARIATE THRESHOLD
We consider linear transformation models applied to right censored survival data with a change-point based on a covariate threshold. We establish consistency and weak convergence of the nonparametric…
SELECTING THE NUMBER OF CHANGE-POINTS IN SEGMENTED LINE REGRESSION.
- Mathematics, Computer ScienceStatistica Sinica
It is shown that, under some conditions, the number of change-points selected by the permutation procedure is consistent and compared with such information-based criterior as the Bayesian Information Criteria, the Akaike Information Criterion, and Generalized Cross Validation.
Model selection by LASSO methods in a change-point model
- Mathematics, Computer Science
A linear regression model with multiple change-points occurring at unknown times and the LASSO technique, which allows simultaneously the parametric estimation, including the change- points estimation, and the automatic variable selection is considered.
Testing for change points due to a covariate threshold in quantile regression
We develop a new procedure for testing change points due to a covariate threshold in regression quantiles. The proposed test is based on the CUSUM of the subgradient of the quantile objective…
The Estimation of the Parameters of a Linear Regression System Obeying Two Separate Regimes
Abstract In attempting to estimate the parameters of a linear regression system obeying two separate regimes, it is necessary first to estimate the position of the point in time at which the switch…
Fitting bent lines to data, with applications to allometry.
- MathematicsJournal of theoretical biology
Estimating regression models with unknown break‐points
- MathematicsStatistics in medicine
This paper deals with fitting piecewise terms in regression models where one or more break‐points are true parameters of the model. For estimation, a simple linearization technique is called for,…
Testing for Structural Change in Regression Quantiles
Most studies in the structural change literature focus solely on the conditional mean, while under various circumstances, structural change in the conditional distribution or in conditional quantiles…