A loss-based approach to change point analysis is proposed. In particular, the problem is looked from two perspectives. The first focuses on the definition of a prior when the number of change points is known a priori. The second contribution aims to estimate the number of change points by using a loss-based approach recently introduced in the literature. The latter considers change point estimation as a model selection exercise. The performance of the proposed approach is shown on simulated data and real data sets
In this work we consider time series with a finite number of discrete point changes. We assume that ...
Change-point models are useful for modeling time series subject to structural breaks. For interpreta...
Many regression problems can be modelled as independent linear regressions on disjoint segments. The...
A loss-based approach to change point analysis is proposed. In particular, the problem is looked fro...
A Bayesian approach is considered to study the change point problems. A hypothesis for testing chang...
This article discusses Bayesian inference in change-point models. The main existing approaches treat...
Change point problems are referred to detect heterogeneity in temporal or spatial data. They have a...
This article presents a new approach for obtaining the change point in the hazard function. The prop...
summary:A change-point problem is examined from a Bayesian viewpoint, under nonparametric hypotheses...
Recently there has been a keen interest in the statistical analysis of change point detection and es...
Changepoint regression models have originally been developed in connection with applications in qual...
This paper discusses Bayesian inference in change-point models. Existing approaches involve placing ...
A Bayesian approach is considered to the problem of making inferences about the point in a sequence ...
The change point estimation problem of a common change in sequence means for a very general sequence...
This work is an in-depth study of the change point problem from a general point of view and a furthe...
In this work we consider time series with a finite number of discrete point changes. We assume that ...
Change-point models are useful for modeling time series subject to structural breaks. For interpreta...
Many regression problems can be modelled as independent linear regressions on disjoint segments. The...
A loss-based approach to change point analysis is proposed. In particular, the problem is looked fro...
A Bayesian approach is considered to study the change point problems. A hypothesis for testing chang...
This article discusses Bayesian inference in change-point models. The main existing approaches treat...
Change point problems are referred to detect heterogeneity in temporal or spatial data. They have a...
This article presents a new approach for obtaining the change point in the hazard function. The prop...
summary:A change-point problem is examined from a Bayesian viewpoint, under nonparametric hypotheses...
Recently there has been a keen interest in the statistical analysis of change point detection and es...
Changepoint regression models have originally been developed in connection with applications in qual...
This paper discusses Bayesian inference in change-point models. Existing approaches involve placing ...
A Bayesian approach is considered to the problem of making inferences about the point in a sequence ...
The change point estimation problem of a common change in sequence means for a very general sequence...
This work is an in-depth study of the change point problem from a general point of view and a furthe...
In this work we consider time series with a finite number of discrete point changes. We assume that ...
Change-point models are useful for modeling time series subject to structural breaks. For interpreta...
Many regression problems can be modelled as independent linear regressions on disjoint segments. The...