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Implied distributions in multiple change point problems
2011
Statistics and computing
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It is shown that, in contrast to sampling methods, very little computation is needed. The method provides probabilities associated with change points within an interval, as well as at specific points. ...
A method for efficiently calculating exact marginal, conditional and joint distributions for change points defined by general finite state Hidden Markov Models is proposed. ...
The methods are ways of detecting and evaluating change points that are implied by a model. In addition, formulas are given to facilitate evaluation of joint and marginal change point distributions. ...
doi:10.1007/s11222-011-9268-6
fatcat:dv4ky67x6vcannoml4fqwaois4
Testing exchangeability with martingale for change-point detection
[article]
2020
arXiv
pre-print
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An online algorithm based on Beta distribution parametrization for constructing this betting function is discussed in detail as well. ...
By choosing the underlying probability density function of p-values as a betting function, it can be shown that, when a change-point appears, a satisfying trade-off between the smoothness and expected ...
Given the fact that both ( ) and ρ( ) integrate to 1 in [0,1], we get = 1, and it implies that the optimum to the optimization problem in eq. (13) is ρ( ). ...
arXiv:1810.04022v2
fatcat:xw7wwdgfpjh5xl22xgsxgo6m2i
Multiple change-point detection via a screening and ranking algorithm
2013
Statistica sinica
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In particular, we develop a false discovery rate approach to the multiple change-point problem and show a strong sure coverage property for the SaRa. ...
The detection of the change points, namely the positions where the mean changes, is an important problem in such fields as engineering, economics, climatology and bioscience. ...
For multiple-change-point problem, the number of change points and their locations are to be estimated. ...
doi:10.5705/ss.2012.018s
pmid:24489450
pmcid:PMC3902887
fatcat:freng7ec4zfqdnyql7k65wdbum
Consistent multiple testing for change points
2011
Journal of Multivariate Analysis
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The change point problem for independent normal means is considered as a multiple testing problem. Two stepwise methods are considered. ...
Various approaches to this multiple testing problem, called a change point problem, have been considered, see Chen and Gupta [4] . ...
The methodology called MRD is developed in Cohen et al. [5] . The MRD methodology can be applied in a variety of multiple testing settings other than change point. ...
doi:10.1016/j.jmva.2011.04.012
fatcat:wulzhme5abdfrmonux5mk3ejpa
To threshold or not to threshold? That's the question
2012
Ecological Indicators
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The paper focuses on the question of whether a threshold model is appropriate, and demonstrates the importance of evaluating multiple alternative models in the detection of ecological thresholds, and illustrates ...
Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. ...
In a threshold modeling problem, the multiple model approach is especially important because the three alternative threshold models can often produce a change point even when a threshold does not exist ...
doi:10.1016/j.ecolind.2011.08.019
fatcat:jdyeekmcprcw7lrqhlw7a7t4ni
Barankin-Type Lower Bound on Multiple Change-Point Estimation
2010
IEEE Transactions on Signal Processing
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We compute lower bounds on the mean-square error of multiple change-point estimation. In this context, the parameters are discrete and the Cramér-Rao bound is not applicable. ...
Several closed-form expressions of the elements of BIM are given for changes in the parameters of Gaussian and Poisson distributions. ...
parameters in addition to the multiple change-point localizations. ...
doi:10.1109/tsp.2010.2064771
fatcat:ugys6hl73bettcii426kp2z624
Nonparametric Bayesian approach to the detection of change point in statistical process control
2017
Hacettepe Journal of Mathematics and Statistics
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This approach can be further extended in the multivariate change point detection which will be studied in the near future. ...
This paper gives an intensive overview of nonparametric Bayesian model relevant to the determination of change point in a process control. ...
In this article we use the nonparametric Bayesian approach to detect change point by not restricting the distributions to be just priori distributed and also we develop that into the multiple change point ...
doi:10.15672/hjms.2017.419
fatcat:ko2nre74wneuxdrwyvkyq2wr2u
Prior Influence on Weiss-Weinstein Bounds for Multiple Change- Point Estimation
2018
2018 26th European Signal Processing Conference (EUSIPCO)
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In this paper, we study the influence of the prior distribution on the Weiss-Weinstein bound (WWB) in the ubiquitous multiple change-point estimation problem. ...
WWBs for the multiple change-point problem In this section, we derive expressions of the WWBs for the multiple change-point estimation problem presented in Section II-A. ...
An important example of discrete parameter estimation problem is the change-point problem, in which the distribution of the observations abruptly changes at an unknown time instant, named "change-point ...
doi:10.23919/eusipco.2018.8553250
dblp:conf/eusipco/BacharachRK18
fatcat:mb3ajgoyevd5noefssh42qieny
The geometry of III-conditioning
1987
Journal of Complexity
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Numerous problems in numerical analysis, including matrix inversion, eigenvalue calculations, and polynomial zero finding, share the following property: the difficulty of solving a given problem is large ...
From this probability distribution we derive, for example, the distribution of the condition number of a random matrix. ...
This permits us to normalize all our problems to have unit norm (lie on the unit sphere in either RN or C~), and implies that any results on the distribution of the condition number will hold for any distribution ...
doi:10.1016/0885-064x(87)90027-6
fatcat:jxq6stotzjhhzcpo2b4feubsrq
Posterior Convergence and Model Estimation in Bayesian Change-point Problems
[article]
2008
arXiv
pre-print
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We study the posterior distribution of the Bayesian multiple change-point regression problem when the number and the locations of the change-points are unknown. ...
Finally, we argue that the point-wise posterior convergence property as demonstrated might have bad finite sample performance in that consistent posterior for model selection necessarily implies the maximal ...
In our context, similar conclusion can be drawn for the Bayesian multiple change-point problem. ...
arXiv:0808.2700v1
fatcat:t5zd2rqjozc6vinhcjl7fzgaii
Ruling Out Multiplicity and Indeterminacy: The Role of Heterogeneity
2000
The Review of Economic Studies
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We illustrate this point in a version of Matsuyama' s (1991) two-sector model with increasing returns to scale. Two main results are shown. ...
We argue that the importance of this source of multiplicity and indeterminacy is overstated in representative agent models, as they ignore the potential stabilizing effect of heterogeneity. ...
In general, a distribution and its spread can have more than one crossing point. ...
doi:10.1111/1467-937x.00132
fatcat:7pmmlrmhqneftpddttxn2af4gq
Structural change and income distribution: An inverted-U relationship
2013
Journal of Economic Dynamics and Control
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We show that, in an economy where preferences and technology adapt over time, multiple long-term outcomes are mainly brought about by different distributive rules governing the assignment of innovative ...
Instead, when innovative rents are too concentrated in favor of either workers or entrepreneurs, the system does not fully accomplish the transition and unemployment might emerge, in contrast, with the ...
From a methodological point of view, considering multiple outcomes as emerging from disequilibrium coordination problems (Howitt, 1994; Amendola et al., 2001) implies rethinking the stark dichotomy between ...
doi:10.1016/j.jedc.2013.02.002
fatcat:3toedgx64nc3pccum3jecvicdq
Calibrating probability distributions with convex-concave-convex functions: application to CDO pricing
2013
Computational Management Science
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Distribution generalizations with multiple humps and their applications in credit risk are also discussed. ...
In discrete case, this class of functions can be expressed by a system of linear constraints and incorporated into an optimization problem. ...
The probability distribution constraint (20) is defined in lines 6,7 with keyword linearmulti and the matrix of unit coefficients, located in the file matrix_aeq.txt. ...
doi:10.1007/s10287-013-0176-4
fatcat:x6c3bg24fja4bj5zmfxl3326je
A finite mixture of multiple discrete distributions for modelling heaped count data
2017
Computational Statistics & Data Analysis
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A new modelling approach, based on finite mixtures of multiple discrete distributions of different multiplicities, is proposed to fit data with a lot of periodic spikes in certain values. ...
An EM algorithm is provided in order to ensure the models' ease-of-fit and then a simulation study is presented to show its efficiency. ...
We do not allow the λ to be zero since this implies a points mass at zero regardless the multiplicity and hence leads to identifiability problems. ...
doi:10.1016/j.csda.2017.02.013
fatcat:c6znmkhyvrf5fi4laua4ohaxqy
Distribution networks as complex dynamic systems new perspective for monitoring them
2017
2017 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
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with multiple and distributed production points whose productions are unpredictable. ...
Anyway, the voltage regulation is made against one or multiple previously selected points. A great improvement would have been the possibility to change these points. ...
doi:10.1109/uic-atc.2017.8397398
dblp:conf/uic/PerlesC17
fatcat:wdoog2dopvhidmx6wi57g5aezm
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