Abstract. In the classical time series analysis, a process is often modeled as three additive components: long-time trend, seasonal eect and background noise. Then the trend superimposed with the seasonal eect constitute the mean part of the process. The issue of mean stationarity, which is generically called change-point problem, is usually the rst step for further statistical inference. In this paper we develop testing theory for the existence of a long-time trend. Applications to the global temperature data and the Darwin sea level pressure data are discussed. Our results extend and generalize previous ones by allowing dependence and general patterns of trends. 1. Introduction. Man
[1] Hydroclimatological time series often exhibit trends. While trend magnitude can be determined wi...
textabstractWe propose tests for hypotheses on the parameter for deterministic trends. The model fra...
We analyze a time series of global temperature anomaly distributions to identify and estimate persis...
Climate time series often have artificial shifts induced by instrumentation changes, station relocat...
<p>This article develops a test for a single changepoint in a general setting that allows for correl...
[1] The detection of a trend in a time series and the evaluation of its magnitude and statistical si...
This paper proposes a test for the correct specification of a dynamic time-series model that is take...
This paper studies how to detect structural change characterized by a shift in persistence of a time...
The detection of climate change and its attribution to the corresponding underlying processes is cha...
Statistical tests for trend in recurrent event data not following a Poisson process are generally co...
Statistical tests for trend in recurrent event data not following a Poisson process are generally co...
This is an Accepted Manuscript of an article published by Taylor & Francis in Technometrics on April...
The identification of systematic small- and intermediate-scale temperature changes (trends) in a tim...
Several time series investigations of global climate change have been published, but the time series...
This paper presents a statistical analysis of structural changes in the Central England temperature ...
[1] Hydroclimatological time series often exhibit trends. While trend magnitude can be determined wi...
textabstractWe propose tests for hypotheses on the parameter for deterministic trends. The model fra...
We analyze a time series of global temperature anomaly distributions to identify and estimate persis...
Climate time series often have artificial shifts induced by instrumentation changes, station relocat...
<p>This article develops a test for a single changepoint in a general setting that allows for correl...
[1] The detection of a trend in a time series and the evaluation of its magnitude and statistical si...
This paper proposes a test for the correct specification of a dynamic time-series model that is take...
This paper studies how to detect structural change characterized by a shift in persistence of a time...
The detection of climate change and its attribution to the corresponding underlying processes is cha...
Statistical tests for trend in recurrent event data not following a Poisson process are generally co...
Statistical tests for trend in recurrent event data not following a Poisson process are generally co...
This is an Accepted Manuscript of an article published by Taylor & Francis in Technometrics on April...
The identification of systematic small- and intermediate-scale temperature changes (trends) in a tim...
Several time series investigations of global climate change have been published, but the time series...
This paper presents a statistical analysis of structural changes in the Central England temperature ...
[1] Hydroclimatological time series often exhibit trends. While trend magnitude can be determined wi...
textabstractWe propose tests for hypotheses on the parameter for deterministic trends. The model fra...
We analyze a time series of global temperature anomaly distributions to identify and estimate persis...