Search results for "changepoint"
showing 8 items of 8 documents
Selecting the Kth nearest-neighbour for clutter removal in spatial point processes through segmented regression models
2023
We consider the problem of feature detection, in the presence of clutter in spatial point processes. A previous study addresses the issue of the selection of the best nearest neighbour for clutter removal. We outline a simple workflow to automatically estimate the number of nearest neighbours by means of segmented regression models applied to an entropy measure of cluster separation. The method is suitable for a feature with clutter as two superimposed Poisson processes on any twodimensional space, including linear networks. We present simulations to illustrate the method and an application to the problem of seismic fault detection.
Estimating the Number of Changepoints in Segmented Regression Models: Comparative Study and Application
2020
This paper deals with the problem of selecting the number of changepoints in segmented regression models. The aim is to review selection criteria, namely information criteria and hypothesis testing, and to propose a novel application in the context of students' careers in higher education. The performance of the selection criteria is assessed through simulation studies. Furthermore, we investigate the relationship between University students' performance and one of its main determinants, finding out that this relationship is actually broken-line.
A novel sequential testing procedure for selecting the number of changepoints in segmented regression models
2023
In this work, we address the problem of selecting the number of changepoints in segmented regression models. We propose a novel stepwise procedure and assess its performance through simulation studies. We demonstrate that our proposal behaves well with the Gaussian and Binomial responses.
Interval estimation for the breakpoint in segmented regression: a smoothed score-based approach
2017
Summary This paper is concerned with interval estimation for the breakpoint parameter in segmented regression. We present score-type confidence intervals derived from the score statistic itself and from the recently proposed gradient statistic. Due to lack of regularity conditions of the score, non-smoothness and non-monotonicity, naive application of the score-based statistics is unfeasible and we propose to exploit the smoothed score obtained via induced smoothing. We compare our proposals with the traditional methods based on the Wald and the likelihood ratio statistics via simulations and an analysis of a real dataset: results show that the smoothed score-like statistics perform in prac…
Segmented mixed models with random changepoints: a maximum likelihood approach with application to treatment for depression study
2014
We present a simple and effective iterative procedure to estimate segmented mixed models in a likelihood based framework. Random effects and covariates are allowed for each model parameter, including the changepoint. The method is practical and avoids the computational burdens related to estimation of nonlinear mixed effects models. A conventional linear mixed model with proper covariates that account for the changepoints is the key to our estimating algorithm. We illustrate the method via simulations and using data from a randomized clinical trial focused on change in depressive symptoms over time which characteristically show two separate phases of change.
Efficient change point detection in genomic sequences of continuous measurements
2010
Abstract Motivation: Knowing the exact locations of multiple change points in genomic sequences serves several biological needs, for instance when data represent aCGH profiles and it is of interest to identify possibly damaged genes involved in cancer and other diseases. Only a few of the currently available methods deal explicitly with estimation of the number and location of change points, and moreover these methods may be somewhat vulnerable to deviations of model assumptions usually employed. Results: We present a computationally efficient method to obtain estimates of the number and location of the change points. The method is based on a simple transformation of data and it provides re…
A segmented regression model for event history data: an application to the fertility patterns in Italy
2009
We propose a segmented discrete-time model for the analysis of event history data in demographic research. Through a unified regression framework, the model provides estimates of the effects of explanatory variables and jointly accommodates flexibly non-proportional differences via segmented relationships. The main appeal relies on ready availability of parameters, changepoints, and slopes, which may provide meaningful and intuitive information on the topic. Furthermore, specific linear constraints on the slopes may also be set to investigate particular patterns. We investigate the intervals between cohabitation and first childbirth and from first to second childbirth using individual data …
segmented: An R package to Fit Regression Models with Broken-Line Relationships
2008
Segmented or broken-line models are regression models where the relationships between the response and one or more explanatory variables are piecewise linear, namely represented by two or more straight lines connected at unknown values: these values are usually referred as breakpoints, changepoints or even joinpoints.