Off-line statistical analysis of change-point models using non parametric and likelihood methods

2005 ◽  
pp. 103-168 ◽  
Author(s):  
Jean Deshayes ◽  
Dominique Picard
Keyword(s):  
Statistical Analysis ◽  
Change Point ◽  
Likelihood Methods ◽  
Analysis Of Change ◽  
Change Point Models ◽  
Non Parametric

Estimation and comparison of multiple change-point models

1998 ◽  
Vol 86 (2) ◽  
pp. 221-241 ◽  
Author(s):  
Siddhartha Chib
Keyword(s):  
Change Point ◽  
Change Point Models

scholarly journals Consistency of an Estimator for Change Point in Volatility of Financial Returns

2021 ◽  
Vol 13 (1) ◽  
pp. 56
Author(s):  
Josephine Njeri Ngure ◽  
Anthony Gichuhi Waititu
Keyword(s):  
Exchange Rate ◽  
Change Point ◽  
Point Estimation ◽  
Fourth Moment ◽  
Financial Returns ◽  
Test Statistic ◽  
Data Set ◽  
United States Dollar ◽  
Binary Segmentation ◽  
Non Parametric

A non parametric Auto-Regressive Conditional Heteroscedastic model for financial returns series is considered in which the conditional mean and volatility functions are estimated non-parametrically using Nadaraya Watson kernel. A test statistic for unknown abrupt change point in volatility which takes into consideration conditional heteroskedasticity, dependence, heterogeneity and the fourth moment of financial returns, since kurtosis is a function of the fourth moment is considered. The test is based on L2norm of the conditional variance functions of the squared residuals. A non-parametric change point estimator in volatility of financial returns is further obtained. The consistency of the estimator is shown theoretically and through simulation. An application of the estimator in change point estimation in volatility of United States Dollar/Kenya Shilling exchange rate returns data set is made. Through binary segmentation procedure, three change points in volatility of the exchange rate returns are estimated and further accounted for.

scholarly journals Closed-Form Estimation of Multiple Change-Point Models

2013 ◽  
Author(s):  
Greg Jensen
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Change Point ◽  
Marginal Likelihood ◽  
Stationary Time Series ◽  
Change Points ◽  
Model Complexity ◽  
Marginal Model ◽  
General Strategy ◽  
Change Point Models

Identifying discontinuities (or change-points) in otherwise stationary time series is a powerful analytic tool. This paper outlines a general strategy for identifying an unknown number of change-points using elementary principles of Bayesian statistics. Using a strategy of binary partitioning by marginal likelihood, a time series is recursively subdivided on the basis of whether adding divisions (and thus increasing model complexity) yields a justified improvement in the marginal model likelihood. When this approach is combined with the use of conjugate priors, it yields the Conjugate Partitioned Recursion (CPR) algorithm, which identifies change-points without computationally intensive numerical integration. Using the CPR algorithm, methods are described for specifying change-point models drawn from a host of familiar distributions, both discrete (binomial, geometric, Poisson) and continuous (exponential, Gaussian, uniform, and multiple linear regression), as well as multivariate distribution (multinomial, multivariate normal, and multivariate linear regression). Methods by which the CPR algorithm could be extended or modified are discussed, and several detailed applications to data published in psychology and biomedical engineering are described.

scholarly journals Grammatical taboos

2019 ◽  
Vol 38 (1) ◽  
pp. 37-79 ◽  
Author(s):  
Ralf Vogel
Keyword(s):  
Statistical Analysis ◽  
Rating Scales ◽  
Experimental Testing ◽  
Questionnaire Study ◽  
Parametric Methods ◽  
Aesthetic Judgement ◽  
Explorative Study ◽  
The Aesthetic ◽  
Non Parametric

Abstract This explorative study focuses on grammatical taboos in German, morphosyntactic constructions which are subject to stigmatisation, as they regularly occur in standard languages. They are subjected to systematic experimental testing in a questionnaire study with gradient rating scales on two salient and two non-salient grammatical taboo phenomena of German. The study is divided into three subexperiments with different judgement types, an aesthetic judgement, a norm-oriented judgement and the sort of possibility judgement that comes closest to linguists’ understanding of grammar. Included in the investigated material are also examples of ordinary gradient grammaticality: unmarked, marked and ungrammatical sentences. The empirical characteristics of grammatical taboos are compared to those ordinary cases with the finding that they are rated at the level of markedness, but differ from ordinary markedness in that they produce a different pattern of between-subject variance. In addition, we find that grammatical taboos have a particular disadvantage under the aesthetic judgement type. The paper also introduces the concept of empirical grammaticality as a necessary theoretical cornerstone for empirical linguistics. Methodically, the study applies a mix of parametric and non-parametric methods of statistical analysis.

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