178,933 Hits in 8.4 sec

Extension to the product partition model: computing the probability of a change

R.H. Loschi, F.R.B. Cruz
2005 Computational Statistics & Data Analysis  
The well-known product partition model (PPM) is considered for the identiÿcation of multiple change points in the means and variances of normal data sequences.  ...  The PPM is extended to generate the posterior distribution of p and the posterior probability that each instant of time is a change point.  ...  Acknowledgements The authors would like to thank professor Luiz Raul Pericchi (University of Puerto Rico) for his important suggestions and comments in earlier version of this paper. Rosangela H.  ... 
doi:10.1016/j.csda.2004.03.003 fatcat:57wllxsqmrervccj7tncbpzg6i

Product Partition Dynamic Generalized Linear Models [article]

Victor S. Comitti, Fábio N. Demarqui, Thiago R. dos Santos, Jéssica da Assunção Almeida
2021 arXiv   pre-print
A simulation study shows that the proposed model provides reasonable estimates of the dynamic parameters and also assigns high change-point probabilities to the breaks introduced in the artificial data  ...  In this paper we approach this problem by incorporating the class of Dynamic Generalized Linear Models (DGLM) into the well know class of Product Partition Models (PPM).  ...  Another Bayesian approach to the change-point problem that has drawn considerable attention over the last decades is the class of Product Partition Models (PPM) proposed by Hartigan (1990) [13] and  ... 
arXiv:2103.02470v1 fatcat:naeyt2n6rbe7vgybkcpxujgrvi

Lumpable hidden Markov models-model reduction and reduced complexity filtering

L.B. White, R. Mahony, G.D. Brushe
2000 IEEE Transactions on Automatic Control  
In essence, the property of lumpability means that there is a partition of the (atomic) states of the Markov chain into aggregated sets which act in a similar manner as far as the state dynamics and observation  ...  For a particular class of hidden Markov models (HMMs), namely finite output alphabet models, conditions for lumpability of all HMPs representable by a specified HMM are given.  ...  ACKNOWLEDGMENT The authors thanks B. D. O. Anderson for helpful comments. They also thank the associate editor and anonymous referees for helpful suggestions.  ... 
doi:10.1109/9.895565 fatcat:wujmxrrdtjcmvn2puelqp5e7rq

Discrete Rayleigh fading channel modeling

Julio Aráuz, Prashant Krishnamurthy, Miguel A. Labrador
2004 Wireless Communications and Mobile Computing  
The Markovian validity of the model is described along with the adequate conditions under which such validity holds.  ...  The first model presented is the finite state Markov channel model which is based on the side information given by the received signal to noise ratio.  ...  The details of how this model should be Current literature does not elaborate extensively on how to select a partitioning scheme.  ... 
doi:10.1002/wcm.185 fatcat:lvfpabtq5bgkhifolm3z6kaug4

Latent Dependency Forest Models [article]

Shanbo Chu, Yong Jiang, Kewei Tu
2016 arXiv   pre-print
A LDFM models the dependencies between random variables with a forest structure that can change dynamically based on the variable values.  ...  Probabilistic modeling is one of the foundations of modern machine learning and artificial intelligence.  ...  Acknowledgments This work was supported by the National Natural Science Foundation of China (61503248).  ... 
arXiv:1609.02236v2 fatcat:qyox6oyiubap5irkhitx37zuhu

Bayesian Analysis of Value-at-Risk with Product Partition Models [article]

Giacomo Bormetti, Maria Elena De Giuli, Danilo Delpini, Claudia Tarantola
2009 arXiv   pre-print
The use of Product Partition Models allows us to remain in a Normal setting even in presence of outlying points, and to obtain a closed-form expression for Value-at-Risk computation.  ...  In this paper we propose a novel Bayesian methodology for Value-at-Risk computation based on parametric Product Partition Models.  ...  Maria Elena De Giuli and Claudia Tarantola acknowledge the University of Pavia for partial support.  ... 
arXiv:0809.0241v2 fatcat:abxtlizonfdsxg2xk2lo5gbqwy

Universal Decision Models [article]

Sridhar Mahadevan
2021 arXiv   pre-print
We describe universal functorial representations of UDMs, and propose an algorithm for computing the minimal object in a UDM using algebraic topology.  ...  Decision objects in a UDM correspond to instances of decision tasks, ranging from causal models and dynamical systems such as Markov decision processes and predictive state representations, to network  ...  In other words, to compute the join of two partition fields, we compute the intersection of every component of F α with that of F β .  ... 
arXiv:2110.15431v1 fatcat:2fwnguplrnfxxgtvh5uryc5q4a

Implicit Generation and Modeling with Energy Based Models

Yilun Du, Igor Mordatch
2019 Neural Information Processing Systems  
Finally, we show that EBMs are useful models across a wide variety of tasks, achieving state-of-the-art out-of-distribution classification, adversarially robust classification, state-of-the-art continual  ...  Energy based models (EBMs) are appealing due to their generality and simplicity in likelihood modeling, but have been traditionally difficult to train.  ...  Acknowledgements We would like to thank Ilya Sutskever, Alec Radford, Prafulla Dhariwal, Dan Hendrycks, Johannes Otterbach, Rewon Child and everyone at OpenAI for helpful discussions.  ... 
dblp:conf/nips/DuM19 fatcat:4hhqfykybzaszd7w4at3ye5u6y

Model-Based Hierarchical Clustering [article]

Shivakumar Vaithyanathan, Byron E Dom
2013 arXiv   pre-print
This model organizes the data into a cluster hierarchy while specifying a complex feature-set partitioning that is a key component of our model.  ...  The regularization induced by using the marginal likelihood automatically determines the optimal model structure including number of clusters, the depth of the tree and the subset of features to be modeled  ...  Acknowledgement: The authors would like to thank Yael Ravin and Roy Byrd for free use of Textract and all the timely help provided.  ... 
arXiv:1301.3899v1 fatcat:2weuuv4c75clza6upzfohtmeba

Approximate Solution of Queueing Models

Sauer, Chandy
1980 Computer  
A queueing network is often represented as a set of queues, corresponding to resources in the computer system, and a set of jobs which, depending on the system, correspond to processes in the computer  ...  Queueing networks are important as performance models of computer systems because the performance of these systems is usually principally affected by contention for resources.  ...  Acknowledgments Portions of this paper are based on or excerpted from a previous paper.' 8 We are grateful to John Spragins and the referees for helpful comments on a draft of this paper.  ... 
doi:10.1109/mc.1980.1653573 fatcat:q56xbir3mna2bbunzgkthjjm5u

Vacation Model [chapter]

2013 Encyclopedia of Operations Research and Management Science  
A vector n-space is a set of vectors or points, each with n components, and rules for vector addition and multiplication by real numbers. Euclidean 3-space is a vector space.  ...  Then the effort of an estimator may be defined to be the product of its variance and its computing time: EFFORT ¼ Var  TMð' N Þ.  ...  specification with the elements and actual functionality of corresponding partition implementation, (3) deriving test data to extensively test the functional behavior of each partition, and (4) testing  ... 
doi:10.1007/978-1-4419-1153-7_200894 fatcat:zm5qf6pzmzbepkc55xmzunolhq

A Dynamic Changepoint Model for New Product Sales Forecasting

Peter S. Fader, Bruce G. S. Hardie, Chun-Yao Huang
2004 Marketing science (Providence, R.I.)  
A t the heart of a new product sales-forecasting model for consumer packaged goods is a multiple-event timing process.  ...  In this paper, we develop a dynamic changepoint model that captures the underlying evolution of the buying behavior associated with the new product.  ...  Acknowledgments The second author acknowledges the support of the London Business School Centre for Marketing.  ... 
doi:10.1287/mksc.1030.0046 fatcat:5mabbey3czhnrp5h2bhm7mjuna

Model Uncertainty

Edward I. George, Merlise Clyde
2004 Statistical Science  
The evolution of Bayesian approaches for model uncertainty over the past decade has been remarkable.  ...  To illustrate key aspects of this evolution, the highlights of some of these developments are described.  ...  Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.  ... 
doi:10.1214/088342304000000035 fatcat:3sjueiia4bh7fher2wqhksiwxy

Spatial Product Partition Models [article]

Garritt L. Page, Fernando A. Quintana
2015 arXiv   pre-print
To this end, we extend product partition models to a spatial setting so that the partitioning of locations into spatially dependent clusters is explicitly modeled.  ...  We explore the spatial structures that result from employing a spatial product partition model and demonstrate its flexibility in accommodating many types of spatial dependencies.  ...  The authors thank Carolina Flores for granting access to the Chilean education data whose collection was partially funded by the ANILLO Project SOC 1107 Statistics for Public Policy in Education from the  ... 
arXiv:1504.04489v1 fatcat:2ft5rz7jonf6zcykqjdcinnsja

Detecting Time-dependent Structure in Network Data via a New Class of Latent Process Models [article]

Lucy F. Robinson, Carey E. Priebe
2013 arXiv   pre-print
A random dot product model is used to describe the dependency structure of the graph. As an application we analyze the Enron email corpus.  ...  Such changes may take the form of a change in the overall probability of connection within or between subgroups, or a change in the distribution of edge attributes.  ...  Several extensions of the model are possible.  ... 
arXiv:1212.3587v2 fatcat:lglw26sbdrdexmn7tm72l72ioy
« Previous Showing results 1 — 15 out of 178,933 results