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Bayesian analysis for partially observed network data, missing ties, attributes and actors

SOCIAL NETWORKS 2013年第4期35卷 514-527页

作者： Koskinen, Johan H. Robins, Garry L. Wang, Peng Pattison, Philippa E. Univ Manchester Social Stat Discipline Area Manchester M13 9PL Lancs England Univ Melbourne Melbourne Sch Psychol Sci Melbourne Vic 3010 Australia

We consider partially observed network data as defined in Handcock and Gile (2010). More specifically we introduce an elaboration of the Bayesian data augmentation scheme of Koskinen et al. (2010) that uses the exchange algorithm (Caimo and Friel, 2011) for inference for the exponential random graph model (ERGM) where tie variables are partly observed. We illustrate the generating of posteriors and unobserved tie-variables with empirical network data where 74% of the tie variables are unobserved under the assumption that some standard assumptions hold true. One of these assumptions is that covariates are fixed and completely observed. A likely scenario is that also covariates might only be partially observed and we propose a further extension of the data augmentation algorithm for missing attributes. We provide an illustrative example of parameter inference with nearly 30% of dyads affected by missing attributes (e.g. homophily effects). The assumption that all actors are known is another assumption that is liable to be violated so that there are "covert actors". We briefly discuss various aspects of this problem with reference to the Sageman (2004) data set on suspected terrorists. We conclude by identifying some areas in need of further research. (C) 2013 Elsevier B.V. All rights reserved.

关键词： Missing data ERGM (p-star) exchange algorithm Snowball sampling Network boundary Non-response Markov graph Imputation

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A Nonlinear Adaptive Observer with Excitation-based Switching

A Nonlinear Adaptive Observer with Excitation-based Switchin...

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52nd IEEE Annual Conference on Decision and Control (CDC)

作者： Pin, Gilberto Chen, Boli Parisini, Thomas Electrolux Profess SpA Pordenone PN Italy Univ London Imperial Coll Sci Technol & Med London SW7 2AZ England Univ Trieste I-34127 Trieste Italy

ISBN: (纸本)9781467357173

This paper presents a MIMO nonlinear adaptive observer, which is characterized by a robust excitation-based switching strategy. The proposed switching algorithm allows to address the scenario of poor excitation, while a conservative minimum duration of excitation interval for ensuring a progressive improvement is determined. The robustness of the devised method with respect to the bounded unstructured perturbation is studied by a input-to-state stability analysis. Simple simulation results show the effectiveness of the proposed technique.

关键词： Excitation Stability analysis Self tuning switching nonlinearity exchange algorithm Simulation results Robustness

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Unfalsified Adaptive Control for Resettable Systems

Unfalsified Adaptive Control for Resettable Systems

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American Control Conference

作者： Seunggyun Cheong Department of Mechanical and Aerospace Engineering University of California San Diego La Jolla CA 92093 USA

ISBN: (纸本)9781479901777

A switching algorithm in the framework of unfalsified adaptive control is formulated for an uncertain system whose state can be reset in a certain set repeatedly. The behavior of the system with its state in or around the set is of interest and the reset process is performed when a switching occurs. The traditional meaning of a feasible controller is modified and, hence, a candidate controller that locally stabilizes the uncertain system with its state in or around the set for small reference signals, becomes a feasible controller. In addition to a cost function in a switching algorithm for unfalsified adaptive control, a secondary cost function is constructed and is utilized in the switching algorithm. At each switching moment, this secondary cost function supports the selection process of the switching algorithm by providing an additional selecting criterion for candidate controllers with small primary cost values. Even with the introduction of the secondary cost function, the number of switchings is still guaranteed to be finite, provided that the primary cost function satisfies assumptions.

关键词： Cost functions exchange algorithm adaptive control Process selection Controllers relocatable uncertain systems Reference signals algorithms switching system behavior

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Unfalsified Adaptive Control: Finding the Best Controller among Candidate Controllers

Unfalsified Adaptive Control: Finding the Best Controller am...

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IEEE Annual Conference on Decision and Control

作者： Seunggyun Cheong Australian Centre for Field Robotics (ACFR) and School of the Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW 2006 Australia

ISBN: (纸本)9781467357159

A new switching algorithm for unfalsified adaptive control is developed to accommodate a pair of cost functions, called a primary and a secondary cost functions. In this switching algorithm, the primary cost function is designed to satisfy certain conditions to ensure the unfalsified stability of the adaptive switching control system. On the other hand, the secondary cost function can be designed based on a performance measure of interests without any condition to satisfy. Thus, both prediction-based and data-based cost functions are allowed for the secondary cost function. When there are multiple stabilizing controllers in the candidate controller set, this secondary cost function is a tool to find the best controller among the stabilizing controllers.

关键词： Cost functions Controllers Performance metrics adaptive control exchange algorithm control systems candidate species

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SENSOR SELECTION FOR RANDOM FIELD ESTIMATION IN WIRELESS SENSOR NETWORKS

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Journal of Systems Science & Complexity 2012年第1期25卷 46-59页

作者： Yang WENG Lihua XIE Wendong XIAO College of Mathematics Sichuan University School of Electrical and Electronic Engineering Nanyang Technological University School of Automation and Electrical Engineering University of Science and Technology Beijing

This paper studies the sensor selection problem for random field estimation in wireless sensor networks. The authors first prove that selecting a set of I sensors that minimize the estimation error under the D-optimal criterion is NP-complete. The authors propose an iterative algorithm to pursue a suboptimal solution. Furthermore, in order to improve the bandwidth and energy efficiency of the wireless sensor networks, the authors propose a best linear unbiased estimator for a Gaussian random field with quantized measurements and study the corresponding sensor selection problem. In the case of unknown covariance matrix, the authors propose an estimator for the covariance matrix using measurements and also analyze the sensitivity of this estimator. Simulation results show the good performance of the proposed algorithms.

关键词： BLUE covarianee matrix exchange algorithm NP-completeness quantization random field sensor selection.

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Optimum design of experiments for statistical inference

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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS 2012年第3期61卷 345-369页

作者： Gilmour, Steven G. Trinca, Luzia A. Univ Southampton Sch Math Southampton SO17 1BJ Hants England Univ Estadual Paulista Botucatu SP Brazil

. One attractive feature of optimum design criteria, such as D- and A-optimality, is that they are directly related to statistically interpretable properties of the designs that are obtained, such as minimizing the volume of a joint confidence region for the parameters. However, the assumed relationships with inferential procedures are valid only if the variance of experimental units is assumed to be known. If the variance is estimated, then the properties of the inferences depend also on the number of degrees of freedom that are available for estimating the error variance. Modified optimality criteria are defined, which correctly reflect the utility of designs with respect to some common types of inference. For fractional factorial and response surface experiments, the designs that are obtained are quite different from those which are optimal under the standard criteria, with many more replicate points required to estimate error. The optimality of these designs assumes that inference is the only purpose of running the experiment, but in practice interpretation of the point estimates of parameters and checking for lack of fit of the treatment model assumed are also usually important. Thus, a compromise between the new criteria and others is likely to be more relevant to many practical situations. Compound criteria are developed, which take account of multiple objectives, and are applied to fractional factorial and response surface experiments. The resulting designs are more similar to standard designs but still have sufficient residual degrees of freedom to allow effective inferences to be carried out. The new procedures developed are applied to three experiments from the food industry to see how the designs used could have been improved and to several illustrative examples. The design optimization is implemented through a simple exchange algorithm.

关键词： A-optimality Blocking Compound criterion D-optimality exchange algorithm Factorial design Lack of fit Pure error Response surface

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A re-coloring approach for graph b-coloring based clustering

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INTERNATIONAL JOURNAL OF KNOWLEDGE-BASED AND INTELLIGENT ENGINEERING SYSTEMS 2012年第2期16卷 117-128页

作者： Yoshida, Tetsuya Ogino, Hiroki Hokkaido Univ Grad Sch Informat Sci & Technol N-14W-9 Sapporo Hokkaido 0600814 Japan

This paper proposes a re-coloring approach for graph b-coloring based clustering. Based on the notion of graph b-coloring in graph theory, a b-coloring based clustering method was proposed. However, previous method did not explicitly consider the quality of clusters, and could not find out better clusters which satisfy the properties of b-coloring. Although a greedy re-coloring algorithm was proposed to reflect the quality of clusters, it was still restrictive in terms of the explored search space due to its greedy and sequential re-coloring process. We aim at overcoming the limitations by enlarging the search space for re-coloring, while guaranteeing the b-coloring properties. In our approach, the vertices in a graph are divided into two disjoint subsets based on the properties of b-coloring. A best first re-coloring algorithm is proposed to realize non-greedy search for the admissible colors of vertices. A color exchange algorithm is proposed to remedy the problem in sequential re-coloring. These algorithms are orthogonal to each other with respect to the re-colored vertices, and thus can be utilized in conjunction. The proposed approach was evaluated against several UCI benchmark datasets. The results are encouraging and indicate the effectiveness of the proposed method, especially with respect to the ground truth micro-averaged precision.

关键词： Graph theory Orthogonal exchange algorithm vertex head Line graph based greedy method

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RaSMaLai: A Randomized Switching algorithm for Maximizing Lifetime in Tree-based Wireless Sensor Networks

RaSMaLai: A Randomized Switching Algorithm for Maximizing Li...

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IEEE INFOCOM

作者： Sk Kajal Arefin Imon Adnan Khan Mario Di Francesco Sajal K. Das Center for Research in Wireless Mobility and Networking The University of Texas at Arlington USA Dept. of Computer Science and Engineering Aalto University School of Science Finland

ISBN: (纸本)9781467359443

In most wireless sensor network (WSN) applications, data are typically gathered by the sensor nodes and reported to a data collection point, called the sink. In order to support such data collection, a tree structure rooted at the sink is usually defined. Based on different aspects, including the actual WSN topology and the available energy budget, the energy consumption of nodes belonging to different paths in the data collection tree may vary significantly. This affects the overall network lifetime, defined in terms of when the first node in the network runs out of energy. In this paper, we address the problem of lifetime maximization of WSNs in the context of data collection trees. In particular, we propose a novel and efficient algorithm, called Randomized Switching for Maximizing Lifetime (RaSMaLai) that aims at maximizing the lifetime of WSNs through load balancing with a low time complexity. We further design a distributed version of our algorithm, called D-RaSMaLai. Simulation results show that both the proposed algorithms outperform several existing approaches in terms of network lifetime. Moreover, RaSMaLai offers lower time complexity while the distributed version, D-RaSMaLai, is very efficient in terms of energy expenditure.

关键词： Wireless sensor networks complexity classes Data Collection Methods energy consumption exchange algorithm available energy TREE STRUCTURES Ganglia algorithms efficient algorithm Load balancing RANDOMISING network node Energy Expenditure

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Switching Control design based on multi-observer for nonlinear systems

Switching Control design based on multi-observer for nonline...

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IEEE Mediterranean Electrotechnical Conference

作者： Lamjed LAMLOUMI Adel YAICH Abdelkader CHAARI R.U. Control Supervision and Operating Safety of Systems Higher School of Sciences and Techniques of Tunis

ISBN: (纸本)9781467307826

The purpose of the work presented in this paper is to design a multi-control scheme for nonlinear systems based on multi-observers and a switching procedure. The concept of the multi-control approach is to design N local linear controllers, each is designed to control the system in a specific operating area. The switcher selects one local controller. This selection is performed by a supervisor consists of a set of local observers. The switching algorithm is then based on the minimization of a quadratic criterion: the correction associated with the observer corresponding to the smallest value of the criterion is selected by the switcher and provides the control signal to the process. This control approach is applied to a Two Wheels inverted Pendulum Mobile Robot and the simulation results showed the effectiveness and the robustness of the control strategy in term of tracking and regulation.

关键词： control strategy Nonlinear systems design control Supervisors Standing Orders Simulation results switching local controller linear controllers exchange algorithm

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SALSA - a spatially adaptive local smoothing algorithm

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2011年第2期81卷 179-191页

作者： Walker, C. G. Mackenzie, M. L. Donovan, C. R. O'Sullivan, M. J. Univ Auckland Dept Engn Sci Auckland 1142 New Zealand Univ St Andrews Sch Math & Stat St Andrews KY16 9AJ Fife Scotland

We present a nonlinear integer programming formulation for fitting a spline-based regression to two-dimensional data using an adaptive knot-selection approach, with the number and location of the knots being determined in the solution process. However, the nonlinear nature of this formulation makes its solution impractical, so we also outline a knot selection heuristic inspired by the Remes exchange algorithm, to produce good solutions to our formulation. This algorithm is intuitive and naturally accommodates local changes in smoothness. Results are presented for the algorithm demonstrating performance that is as good as, or better than, other current methods on established benchmark functions.

关键词： regression spline knot location exchange algorithm nonlinear integer program

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