Exact and efficient Bayesian inference for multiple changepoint problems

Fearnhead, Paul

doi:10.1007/s11222-006-8450-8

Cited by 396 publications

(481 citation statements)

References 38 publications

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“…Another interesting refinement would be to make the substitution rate in recombined regions nonconstant. One way to do this would be to have a different value of n for each recombined region, but this implies a nonconstant dimensionality of the parameter space, which requires the use of complex inferential methods, for example, reversible-jump MCMC (Green 1995) or exact sampling (Fearnhead 2006). Alternatives include having a different value of n for each branch or having several possible values of n representing different distances of the import source.…”

Section: Discussionmentioning

confidence: 99%

Inference of Bacterial Microevolution Using Multilocus Sequence Data

2007

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We describe a model-based method for using multilocus sequence data to infer the clonal relationships of bacteria and the chromosomal position of homologous recombination events that disrupt a clonal pattern of inheritance. The key assumption of our model is that recombination events introduce a constant rate of substitutions to a contiguous region of sequence. The method is applicable both to multilocus sequence typing (MLST) data from a few loci and to alignments of multiple bacterial genomes. It can be used to decide whether a subset of isolates share common ancestry, to estimate the age of the common ancestor, and hence to address a variety of epidemiological and ecological questions that hinge on the pattern of bacterial spread. It should also be useful in associating particular genetic events with the changes in phenotype that they cause. We show that the model outperforms existing methods of subdividing recombinogenic bacteria using MLST data and provide examples from Salmonella and Bacillus. The software used in this article, ClonalFrame, is available from http:/ /bacteria.stats.ox.ac.uk/.

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Section: Discussionmentioning

confidence: 99%

Inference of Bacterial Microevolution Using Multilocus Sequence Data

2007

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“…Temporal segmentation is related to numbers of different fields such as data mining [6] [7], behavior recognition [8] and so on. Researchers have proposed several techniques to segment motion capture data into distinct behaviors.…”

Section: Related Workmentioning

confidence: 99%

Efficient Unsupervised Behavioral Segmentation of Human Motion Capture Data

Liu¹,

Xing

2016

International Conferences on Distributed Multimedia Systems

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-With the development of human motion capture, realistic human motion capture data has been widely implemented to many fields. However, segmenting motion capture data sequences manually into distinct behavior is time-consuming and laborious. In this paper, we introduce an efficient unsupervised method based on graph partition for automatically segmenting motion capture data. For the N-Frame motion capture data sequence, we construct an undirected, weighted graph G=G(V,E), where the node set V represent frames of motion sequence and the weight of the edge set E describes similarity between frames. In this way, behavioral segmentation problem on motion capture data may be transformed into graph cut problem. However, the traditional graph cut problem is NP hard. By analyzing the relationship between graph cut and spectral clustering, we apply spectral clustering to the NP hard problem of graph cut. In this paper, two methods of spectral clustering, tnearest neighbors and the Nystrom method, are employed to cluster motion capture data for getting behavioral segmentation. In addition, we define an energy function to refine the results of behavioral segmentation. Extensive experiments are conducted on the dataset of multi-behavior motion capture data from CMU database. The experimental results prove that our novel method is robust and effective.

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“…There is a variety of efficient ways to analyze a time series if the parameters associated with each segment are independent (Fearnhead 2006;Hutter 2007, and references therein). Scargle (1998) proposed an algorithm for best data partitioning within an interval based on Bayesian statistics.…”

Section: Theory and Calculationmentioning

confidence: 99%

INTEGRAL/SPI data segmentation to retrieve source intensity variations

Bouchet

Amestoy

Buttari

et al. 2013

A&A

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Context. The INTEGRAL/SPI, X/γ-ray spectrometer (20 keV-8 MeV) is an instrument for which recovering source intensity variations is not straightforward and can constitute a difficulty for data analysis. In most cases, determining the source intensity changes between exposures is largely based on a priori information. Aims. We propose techniques that help to overcome the difficulty related to source intensity variations, which make this step more rational. In addition, the constructed "synthetic" light curves should permit us to obtain a sky model that describes the data better and optimizes the source signal-to-noise ratios. Methods. For this purpose, the time intensity variation of each source was modeled as a combination of piecewise segments of time during which a given source exhibits a constant intensity. To optimize the signal-to-noise ratios, the number of segments was minimized. We present a first method that takes advantage of previous time series that can be obtained from another instrument on-board the INTEGRAL observatory. A data segmentation algorithm was then used to synthesize the time series into segments. The second method no longer needs external light curves, but solely SPI raw data. For this, we developed a specific algorithm that involves the SPI transfer function. Results. The time segmentation algorithms that were developed solve a difficulty inherent to the SPI instrument, which is the intensity variations of sources between exposures, and it allows us to obtain more information about the sources' behavior.

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Exact and efficient Bayesian inference for multiple changepoint problems

Cited by 396 publications

References 38 publications

Inference of Bacterial Microevolution Using Multilocus Sequence Data

Inference of Bacterial Microevolution Using Multilocus Sequence Data

Efficient Unsupervised Behavioral Segmentation of Human Motion Capture Data

INTEGRAL/SPI data segmentation to retrieve source intensity variations

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