<b>bcp</b>: An<i>R</i>Package for Performing a Bayesian Analysis of Change Point Problems

Erdman, Chandra; Emerson, John W.

doi:10.18637/jss.v023.i03

Cited by 276 publications

(229 citation statements)

References 15 publications

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“…The presence and timing of change points in the macroalgal cover time series, indicative of a regime shift, were calculated via Bayesian change-point analysis (48). The analysis provides estimates of posterior probabilities for the presence of a change point at any given date and of posterior mean algal cover.…”

Section: Methodsmentioning

confidence: 99%

Climate-driven regime shifts in Arctic marine benthos

Kortsch

Primicerio

Beuchel

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

222

183

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Climate warming can trigger abrupt ecosystem changes in the Arctic. Despite the considerable interest in characterizing and understanding the ecological impact of rapid climate warming in the Arctic, few long time series exist that allow addressing these research goals. During a 30-y period of gradually increasing seawater temperature and decreasing sea ice cover in Svalbard, we document rapid and extensive structural changes in the rocky-bottom communities of two Arctic fjords. The most striking component of the benthic reorganization was an abrupt fivefold increase in macroalgal cover in 1995 in Kongsfjord and an eightfold increase in 2000 in Smeerenburgfjord. Simultaneous changes in the abundance of benthic invertebrates suggest that the macroalgae played a key structuring role in these communities. The abrupt, substantial, and persistent nature of the changes observed is indicative of a climate-driven ecological regime shift. The ecological processes thought to drive the observed regime shifts are likely to promote the borealization of these Arctic marine communities in the coming years.climate change | community structure | ecological dynamics | ecological interactions | tipping point C limate warming has accelerated over the past 30 y, causing increases in global surface temperatures of about 0.2°C per decade (1). The greatest changes have been recorded in the Arctic, where the temperatures have risen at twice the global average rate and sea ice cover, at the end of the Arctic summer, has declined by 30% (2). These changes modify Arctic marine habitats with respect to light and temperature regimes, which, in turn, impact local biological communities (3, 4). The increasing length of the ice-free season (5), extending the period of primary production, and the increasing seawater temperature, have strong impacts on abundances and distributions of species mediated by changes in demographic and interaction parameters.

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Section: Methodsmentioning

confidence: 99%

Climate-driven regime shifts in Arctic marine benthos

Kortsch

Primicerio

Beuchel

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

222

183

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“…The double mass curve, Pettitt's test and the BCP analysis were used to detect a change point in observed runoff time series in this study. Furthermore, the BCP package developed by Erdman and Emerson [48] on R was used.…”

Section: Detection Of a Change Pointmentioning

confidence: 99%

Quantification of Hydrological Responses Due to Climate Change and Human Activities over Various Time Scales in South Korea

Lee

Kim

2017

Water

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Hydrological responses are being impacted by both climate change and human activities. In particular, climate change and regional human activities have accelerated significantly during the last three decades in South Korea. The variation in runoff due to the two types of factors should be quantitatively investigated to aid effective water resources' planning and management. In water resources' planning, analysis using various time scales is useful where rainfall is unevenly distributed. However, few studies analyzed the impacts of these two factors over different time scales. In this study, hydrologic model-based approach and hydrologic sensitivity were used to separate the relative impacts of these two factors at monthly, seasonal and annual time scales in the Soyang Dam upper basin and the Seom River basin in South Korea. After trend analysis using the Mann-Kendall nonparametric test to identify the causes of gradual change, three techniques, such as the double mass curve method, Pettitt's test and the BCP (Bayesian change point) analysis, were used to detect change points caused by abrupt changes in the collected observed runoff. Soil and Water Assessment Tool (SWAT) models calibrated from the natural periods were used to calculate the impacts of human activities. Additionally, six Budyko-based methods were used to verify the results obtained from the hydrological-based approach. The results show that impacts of climate change have been stronger than those of human activities in the Soyang Dam upper basin, while the impacts of human activities have been stronger than those of climate change in the Seom River basin. Additionally, the quantitative characteristics of relative impacts due to these two factors were identified at the monthly, seasonal and annual time scales. Finally, we suggest that the procedure used in this study can be used as a reference for regional water resources' planning and management.

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“…The prior distribution of µ ij (the mean of the block beginning at position i + 1 and ending at position j) is chosen as N (µ 0 , σ 2 0 /(j − i)). The algorithm uses a partition ρ = (U 1 , U 2 , ..., U n ), where U i = 1 indicates a change point at position i + 1; Erdman and Emerson (2007) initialize U i to 0 for all i < n, with U n ≡ 1. In each step of the Markov chain, at each position i, a value of Ui is drawn from the conditional distribution of Ui given the data and the current partition.…”

Section: Methodological Approachmentioning

confidence: 99%

Comparative analysis of Bayesian and maximum likelihood estimators in change point problems with Poisson process

Kitabo¹,

Kim

2015

Journal of the Korean Data and Information Science Society

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Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum likelihood estimator and remains good choice specially in confidence interval statistical inference.

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bcp: AnRPackage for Performing a Bayesian Analysis of Change Point Problems

Cited by 276 publications

References 15 publications

Climate-driven regime shifts in Arctic marine benthos

Climate-driven regime shifts in Arctic marine benthos

Quantification of Hydrological Responses Due to Climate Change and Human Activities over Various Time Scales in South Korea

Comparative analysis of Bayesian and maximum likelihood estimators in change point problems with Poisson process

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