Estimating the Locations of Multiple Change Points in the Mean

2002 ◽  
Vol 17 (2) ◽  
pp. 289-296 ◽  
Author(s):  
Joe H. Sullivan
Keyword(s):  
Change Points ◽  
The Mean

scholarly journals Analyses of Monthly Discharges in Slovakia Using Hydrological Exploratory Methods

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 18
Author(s):  
Mária Ďurigová ◽  
Dominika Ballová ◽  
Kamila Hlavčová
Keyword(s):  
Change Points ◽  
Hydrological Data ◽  
Pettitt Test ◽  
The Mean ◽  
Monthly Discharge ◽  
Meteorological Elements ◽  
The Relationship ◽  
Annual Discharge ◽  
Hydrological Regimes

Detailed analyses of hydrological data are necessary in order to prove changes in their character. This article focuses on an analysis of the average monthly discharges of 14 stage-discharge gauging stations in Slovakia. The measured period is from 1931 to 2016. The approaches used are hydrological exploration methods, which were created by hydrologists to describe the behavior of hydrological time series. The methods are used to identify a change-point using an analysis of any residuals, the Pettitt test, and an analysis of the relationship between the mean annual discharge deviations from the long-term annual discharge and the deviations of the average monthly discharge from the long-term average monthly discharge. A considerable number of change-points were identified in the 1970s and 1980s. The results of the analyses show changes in the hydrological regimes, but to confirm the accuracy of the outcomes, it is also necessary to examine other hydrological and meteorological elements such as, e.g., precipitation and the air temperature.

scholarly journals Homogeneity tests and non-parametric analyses of tendencies in precipitation time series in Keszthely, Western Hungary

2019 ◽  
Vol 139 (3-4) ◽  
pp. 849-859 ◽  
Author(s):  
Tímea Kocsis ◽  
Ilona Kovács-Székely ◽  
Angéla Anda
Keyword(s):  
Time Series ◽  
Change Points ◽  
Annual Precipitation ◽  
Trend Test ◽  
Climate Data ◽  
Homogeneity Tests ◽  
Break Points ◽  
The Mean ◽  
Parametric Analyses ◽  
Precipitation Records

Abstract This study aims to investigate the precipitation trends in Keszthely (Western Hungary, Central Europe) through an examination of historical climate data covering the past almost one and a half centuries. Pettitt’s test for homogeneity was employed to detect change points in the time series of monthly, seasonal and annual precipitation records. Change points and monotonic trends were analysed separately in annual, seasonal and monthly time series of precipitation. While no break points could be detected in the annual precipitation series, a significant decreasing trend of 0.2–0.7 mm/year was highlighted statistically using the autocorrelated Mann-Kendall trend test. Significant change points were found in those time series in which significant tendencies had been detected in previous studies. These points fell in spring and winter for the seasonal series, and October for the monthly series. The question therefore arises of whether these trends are the result of a shift in the mean. The downward and upward shift in the mean in the case of spring and winter seasonal amounts, respectively, leads to a suspicion that changes in precipitation are also in progress in these seasons. The study concludes that homogeneity tests are of great importance in such analyses, because they may help to avoid false trend detections.

scholarly journals A robust approach for estimating change-points in the mean of an $\operatorname{AR}(1)$ process

Bernoulli ◽  
2017 ◽  
Vol 23 (2) ◽  
pp. 1408-1447 ◽  
Author(s):  
S. Chakar ◽  
E. Lebarbier ◽  
C. Lévy-Leduc ◽  
S. Robin
Keyword(s):  
Change Points ◽  
Robust Approach ◽  
The Mean

scholarly journals Detection of multiple changes in mean by sparse parameter estimation

2013 ◽  
Vol 18 (2) ◽  
pp. 177-190 ◽  
Author(s):  
Jirí Neubauer ◽  
Vítezslav Veselý
Keyword(s):  
Stochastic Process ◽  
Parameter Estimation ◽  
Standard Deviation ◽  
White Noise ◽  
Change Point ◽  
Change Point Detection ◽  
Change Points ◽  
Empirical Probability ◽  
The Mean ◽  
Point Detection

The contribution is focused on detection of multiple changes in the mean in a onedimensional stochastic process by sparse parameter estimation from an overparametrized model. The authors’ approach to change point detection differs entirely from standard statistical techniques. A stochastic process residing in a bounded interval with changes in the mean is estimated using dictionary (a family of functions, the so-called atoms, which are overcomplete in the sense of being nearly linearly dependent) and consisting of Heaviside functions. Among all possible representations of the process we want to find a sparse one utilizing a significantly reduced number of atoms. This problem can be solved by ℓ1-minimization. The basis pursuit algorithm is used to get sparse parameter estimates. In this contribution the authors calculate empirical probability of successful change point detection as a function depending on the number of change points and the level of standard deviation of additive white noise of the stochastic process. The empirical probability was computed by simulations where locations of change points were chosen randomly from uniform distribution. The authors’ approach is compared with LASSO algorithm, ℓ1 trend filtering and selected statistical methods. Such probability decreases with increasing number of change points and/or standard deviation of white noise. The proposed method was applied on the time series of nuclear magnetic response during the drilling of a well.

scholarly journals How did governmental interventions affect the spread of COVID-19 in European countries?

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Richard A. J. Post ◽  
Marta Regis ◽  
Zhuozhao Zhan ◽  
Edwin R. van den Heuvel
Keyword(s):  
Time Window ◽  
A Priori ◽  
Change Points ◽  
Delayed Effect ◽  
Infectious Individual ◽  
Effective Contact ◽  
The Mean ◽  
Priori Information ◽  
The Uk ◽  
Daily Total

Abstract Background To reduce the transmission of the severe acute respiratory syndrome coronavirus 2 in its first wave, European governments have implemented successive measures to encourage social distancing. However, it remained unclear how effectively measures reduced the spread of the virus. We examined how the effective-contact rate (ECR), the mean number of daily contacts for an infectious individual to transmit the virus, among European citizens evolved during this wave over the period with implemented measures, disregarding a priori information on governmental measures. Methods We developed a data-oriented approach that is based on an extended Susceptible-Exposed-Infectious-Removed (SEIR) model. Using the available data on the confirmed numbers of infections and hospitalizations, we first estimated the daily total number of infectious-, exposed- and susceptible individuals and subsequently estimated the ECR with an iterative Poisson regression model. We then compared change points in the daily ECRs to the moments of the governmental measures. Results The change points in the daily ECRs were found to align with the implementation of governmental interventions. At the end of the considered time-window, we found similar ECRs for Italy (0.29), Spain (0.24), and Germany (0.27), while the ECR in the Netherlands (0.34), Belgium (0.35) and the UK (0.37) were somewhat higher. The highest ECR was found for Sweden (0.45). Conclusions There seemed to be an immediate effect of banning events and closing schools, typically among the first measures taken by the governments. The effect of additionally closing bars and restaurants seemed limited. For most countries a somewhat delayed effect of the full lockdown was observed, and the ECR after a full lockdown was not necessarily lower than an ECR after (only) a gathering ban.

scholarly journals Analyses of Monthly Discharges in Slovakia Using Hydrological Exploratory Methods and Statistical Methods

2019 ◽  
Vol 27 (2) ◽  
pp. 36-43 ◽  
Author(s):  
Mária Ďurigová ◽  
Dominika Ballová ◽  
Kamila Hlavčová
Keyword(s):  
Change Point ◽  
Change Points ◽  
Hydrological Data ◽  
The Mean ◽  
Monthly Discharge ◽  
Meteorological Elements ◽  
The Relationship ◽  
Annual Discharge ◽  
Hydrological Regimes

AbstractDetailed analyses of hydrological data are necessary in order to examine changes in their character. This article focuses on an analysis of the average monthly discharges of 14 stage-discharge gauging stations in Slovakia. The measured period is from 1931 to 2016. The approaches used are hydrological exploration methods, which were created by hydrologists to describe the behaviour of hydrological time series. The methods are used to identify a change-point through an analysis of any residuals, Pettitt´s test, and an analysis of the relationship between the mean annual discharge deviations from the long-term annual discharge and the deviations of the average monthly discharge from the long-term average monthly discharge. A considerable number of change-points were identified in the 1970s and 1980s. The results of the analyses show changes in the hydrological regimes, but to confirm the accuracy of the outcomes, it is also necessary to examine other hydrological and meteorological elements such as, e.g., precipitation and the air temperature.

Sign in / Sign up

Export Citation Format

Share Document