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Analysing Mark-Recapture-Recovery Data in the Presence of Missing Covariate Data Via Multiple Imputation

JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2015年第1期20卷 28-46页

作者： Worthington, Hannah King, Ruth Buckland, stephen T. Univ St Andrews Sch Math & Stat St Andrews KY16 9LZ Fife Scotland Univ St Andrews Ctr Res Ecol & Environm Modelling St Andrews KY16 9LZ Fife Scotland

We consider mark-recapture-recovery data with additional individual time-varying continuous covariate data. For such data it is common to specify the model parameters, and in particular the survival probabilities, as a function of these covariates to incorporate individual heterogeneity. However, an issue arises in relation to missing covariate values, for (at least) the times when an individual is not observed, leading to an analytically intractable likelihood. We propose a two-step multiple imputation approach to obtain estimates of the demographic parameters. Firstly, a model is fitted to only the observed covariate values. Conditional on the fitted covariate model, multiple "complete" datasets are generated (i.e. all missing covariate values are imputed). Secondly, for each complete dataset, a closed form complete data likelihood can be maximised to obtain estimates of the model parameters which are subsequently combined to obtain an overall estimate of the parameters. Associated standard errors and 95 % confidence intervals are obtained using a non-parametric bootstrap. A simulation study is undertaken to assess the performance of the proposed two-step approach. We apply the method to data collected on a well-studied population of Soay sheep and compare the results with a Bayesian data augmentation approach. Supplementary materials accompanying this paper appear on-line.

关键词： Individual time-varying continuous covariates Mark-recapture-recovery data Missing values Multiple imputation two-step algorithm

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Information enhanced model selection for Gaussian graphical model with application to metabolomic data

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BIOSTATISTICS 2021年第3期23卷 926-948页

作者： Zhou, Jie Hoen, Anne G. Mcritchie, Susan Pathmasiri, Wimal Viles, Weston D. Nguyen, Quang P. Madan, Juliette C. Dade, Erika Karagas, Margaret R. Gui, Jiang Dartmouth Coll Geisel Sch Med Dept Biomed Data Sci 3 Rope Ferry Rd Hanover NH 03755 USA Dartmouth Coll Geisel Sch Med Dept Epidemiol 3 Rope Ferry Rd Hanover NH 03755 USA Univ North Carolina Chapel Hill Nutr Res Inst Dept Nutr Sch Publ Hlth 500 Laureate Way Kannapolis NC 28081 USA Univ Southern Maine Dept Math & Stat 96 Falmouth St Portland ME 04103 USA

In light of the low signal-to-noise nature of many large biological data sets, we propose a novel method to learn the structure of association networks using Gaussian graphical models combined with prior knowledge. Our strategy includes two parts. In the first part, we propose a model selection criterion called structural Bayesian information criterion, in which the prior structure is modeled and incorporated into Bayesian information criterion. It is shown that the popular extended Bayesian information criterion is a special case of structural Bayesian information criterion. In the second part, we propose a two-step algorithm to construct the candidate model pool. The algorithm is data-driven and the prior structure is embedded into the candidate model automatically. Theoretical investigation shows that under some mild conditions structural Bayesian information criterion is a consistent model selection criterion for high-dimensional Gaussian graphical model. Simulation studies validate the superiority of the proposed algorithm over the existing ones and show the robustness to the model misspecification. Application to relative concentration data from infant feces collected from subjects enrolled in a large molecular epidemiological cohort study validates that metabolic pathway involvement is a statistically significant factor for the conditional dependence between metabolites. Furthermore, new relationships among metabolites are discovered which can not be identified by the conventional methods of pathway analysis. Some of them have been widely recognized in biological literature.

关键词： Chow-Liu algorithm Metabolite pathway analysis Model pool Prior structure Structural BIC Structure learning algorithm two-step algorithm Undirected Gaussian graphical model

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Modification of two-step Monte Carlo algorithms based on the symmetry of the first step

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COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS 2009年第11期49卷 1921-1929页

作者： Mikhailov, G. A. Rozhenko, S. A. Russian Acad Sci Inst Computat Math & Math Geophys Siberian Branch Novosibirsk 630090 Russia Novosibirsk State Univ Novosibirsk 630090 Russia

two-step Monte Carlo algorithms are modified taking into account the symmetry (i.e., invariance) of the first step about some initial vector parameter of the modeled trajectory. In the modification, the modeling of this parameter is formally transferred to the second step of the algorithm. In the "splitting method," this means the randomization of the initial points of auxiliary trajectories. It is shown that the randomization can be improved by applying the Bellman principle.

关键词： Monte Carlo method two-step algorithm splitting method complexity estimation for algorithms

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Parsimonious HMMs for Offline Handwritten Chinese Text Recognition 16

Parsimonious HMMs for Offline Handwritten Chinese Text Recog...

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16th International Conference on Frontiers in Handwriting Recognition (ICFHR)

作者： Wang, Wenchao Du, Jun Wang, Zi-Rui Univ Sci & Technol China Hefei Anhui Peoples R China

ISBN: (纸本)9781538658758

Recently, hidden Markov models (HMMs) have achieved promising results for offline handwritten Chinese text recognition. However, due to the large vocabulary of Chinese characters with each modeled by a uniform and fixed number of hidden states, a high demand of memory and computation is required. In this study, to address this issue, we present parsimonious HMMs via the state tying which can fully utilize the similarities among different Chinese characters. two-step algorithm with the data-driven question-set is adopted to generate the tied-state pool using the likelihood measure. The proposed parsimonious HMMs with both Gaussian mixture models (GMMs) and deep neural networks (DNNs) as the emission distributions not only lead to a compact model but also improve the recognition accuracy via the data sharing for the tied states and the confusion decreasing among state classes. Tested on ICDAR-2013 competition database, in the best configured case, the new parsimonious DNN-HMM can yield a relative character error rate (CER) reduction of 6.2%, 25% reduction of model size and 60% reduction of decoding time over the conventional DNN-HMM. In the compact setting case of average 1-state HMM, our parsimonious DNN-HMM significantly outperforms the conventional DNN-HMM with a relative CER reduction of 35.5%.

关键词： Parsimonious HMM character similarity state tying two-step algorithm handwritten Chinese text recognition

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Cloud Service and Service Selection algorithm Research 09

Cloud Service and Service Selection Algorithm Research

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World Summit on Genetic and Evolutionary Computation (GEC 09)

作者： Zeng, Wenying Zhao, Yuelong Zeng, Junwei S China Univ Technol Sch Comp Sci & Engn Guangdong Inst Sci & Technol Guangzhou 510640 Guangdong Peoples R China

ISBN: (纸本)9781605583266

This paper describes the cloud service architecture and key technologies for service selection algorithm. Cloud computing is a hot topic on software and distributed computing based on Internet, which means users can access storages and applications from remote servers by web browsers or other fixed or mobile terminals. Because the constrained resources of fixed or mobile terminals, cloud computing will provide terminals with powerful complementation resources to acquire complicated services. The paper discusses the cloud service architecture and key algorithms about service selection with adaptive performances and minimum cost. The cloud service architecture is reasonable and the proposed service selection algorithms are available, scalable, and adaptive to different types of environments of services and clients.

关键词： Cloud Service Cloud Computing Architecture Service Selection two-step algorithm

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A new non-linear algorithm for complete pre-flight calibration of magnetometers in the geomagnetic field domain

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING 2009年第G6期223卷 729-739页

作者： Asl, H. Ghanbarpour Pourtakdoust, S. H. Samani, M. Sharif Univ Technol Ctr Res & Dev Space Sci & Technol Dept Aerosp Engn Tehran 113658639 Iran Islamic Azad Univ Sci & Res Branch Tehran Iran

A new algorithm for complete pre-flight calibration of triple magnetometers is developed. The traditional approach for calibrating these sensors are based on a cumbersome procedure called 'swing' that involves levelling and rotating the vehicle containing the magnetometers through a series of known headings. Application of such a procedure is difficult and costly. Recently, new approaches have been developed to calibrate magnetometers without the need of attitude information. Such methods are used mostly for the calibration of biases and scale factors. Additionally in situations where misalignment errors are also to be estimated, they are usually modelled as errors of a non-orthogonal frame relative to an orthogonal frame creating six additional unknown parameters to be estimated. The presented approach in this article utilizes a three-step algorithm to fully calibrate triple magnetometers without the need of attitude information through a batch least-square non-linear estimator. Since misalignment parameters are not all identifiable through attitude-independent techniques, the measurement equation is initially factorized such that the non-observable parameters are removed. This would allow identification of three parameters through attitude-independent techniques, while identification of the other three that require horizon information is carried out using a secondary procedure. In step one of the proposed scheme, the non-linear observation equation is transformed, via two non-linear functions, to a linear space with respect to the unknown parameters and the new unknown parameters are estimated with batch least-square estimator. In the second step, the first non-linear function is solved for nine parameters that have non-linear relationships with respect to the desired biases, scale factors, and misalignments. Subsequently, the second non-linear function is solved giving the main unknown calibration parameters in a non-physical frame. Finally, in the third step, to

关键词： magnetometer calibration non-linear estimator two-step algorithm three-step algorithm

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A High-Resolution SAR Focusing Experiment Based on GF-3 Staring Data

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SENSORS 2018年第4期18卷 943-943页

作者： Shang, Mingyang Han, Bing Ding, Chibiao Sun, Jili Zhang, Tao Huang, Lijia Meng, Dadi Chinese Acad Sci Inst Elect Key Lab Technol Geospatial Informat Proc & Appl S Beijing 100190 Peoples R China Chinese Acad Sci Inst Elect Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Elect Elect & Commun Engn Beijing 100049 Peoples R China Chinese Acad Sci Inst Elect Natl Key Lab Microwave Imaging Technol Beijing 100190 Peoples R China

Spotlight synthetic aperture radar (SAR) is a proven technique, which can provide high-resolution images as compared to those produced by traditional stripmap SAR. This paper addresses a high-resolution SAR focusing experiment based on Gaofen-3 satellite (GF-3) staring data with about 55 cm azimuth resolution and 240 MHz range bandwidth. In staring spotlight (ST) mode, the antenna always illuminates the same scene on the ground, which can extend the synthetic aperture. Based on a two-step processing algorithm, some special aspects such as curved-orbit model error correction, stop-and-go correction, and antenna pattern demodulation must be considered in image focusing. We provide detailed descriptions of all these aspects and put forward corresponding solutions. Using these suggested methods directly in an imaging module without any modification for other data processing software can make the most of the existing ground data processor. Finally, actual data acquired in GF-3 ST mode is used to validate these methodologies, and a well-focused, high-resolution image is obtained as a result of this focusing experiment.

关键词： SAR GF-3 staring spotlight two-step algorithm curved orbit stop-and-go antenna pattern high-resolution

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Power Supply Meshes based Line Routing for Urban MV Distribution Network Planning

Power Supply Meshes based Line Routing for Urban MV Distribu...

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作者： Ning Luo Hua Gao Zhuding Wang Molin He Power grid planning research centre of Guizhou Power Grid Co. Ltd State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University

Considering that it is difficult to determine the load points or the locations of user access facilities in urban areas for the planning years, an optimization method for the routing planning of urban medium-voltage(MV) trunk lines is proposed based on power supply meshes. Firstly, based on the results of load forecasting and high voltage substation planning, power supply meshes are generated in the entire planning area according to the principle of selecting standby substations close to loads. Then, based on the thinking line of "trunk firstly, branch then", a shortest path based two-step algorithm is proposed to find the shortest trunk lines for the load centres of power supply meshes and the shortest trunk tie-line be-tween the load centres of each mesh. A numerical example shows that the method is practical and feasible, which can provide a reference for the reasonable routing scheme of medium voltage trunk lines.

关键词： MV line routing planning power supply mesh shortest path algorithm two-step algorithm trunk line

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