%0 Conference Proceedings %B JSM 2017 %T Estimation of Capture Probabilities by Accounting for Sample Designs %A Abernethy, J. %A Sartore, L. %A Benecha, H. %A Spiegelman, C. %K Agriculture %K CaptureRecapture %K Estimation %K government %K NASS %K Research %K SampleDesigns %K Weights %X

The United States Department of Agriculture’s (USDA’s) National Agricultural Statistics Service (NASS) conducts the Census of Agriculture every five years to estimate the number of U.S. farms, as well as other agriculturally related population totals. NASS applies a Dual-System Estimation (DSE) methodology on data collected from the Census and the June Area Survey (JAS) to estimate the number of farms in the U.S.. Traditional multinomial-based capture-recapture methodology requires a model to estimate the probability of capture for every captured operation on either survey. Of course, the selection probabilities associated with the JAS area frame design are different from those associated with the Census. Such a difference makes it difficult to compute the exact JAS selection probabilities for farm records captured only by the Census. For this reason, we propose and compare three methods for estimating the overall capture probability. The first two methods involve approximating the JAS selection probabilities and the third conditions them out. We compare these three techniques to investigate their precision through a simulation study.

%B JSM 2017 %G eng %U https://www.niss.org/sites/default/files/Abernethy_Capture_Probs_20170920.pdf %1

In Proceedings of the Government Statistics Section, JSM 2017. Download https://www.niss.org/sites/default/files/Abernethy_Capture_Probs_20170920.pdf

%0 Conference Proceedings %B JSM 2017 %T Evaluation of a New Approach for Estimating the Number of U.S. Farms %A Benecha, H. %A Abreu, D. %A Abernethy, J. %A Sartore, L. %A Young, L. Y. %K Agriculture %K Area-frame %K BigData %K Capture-Recapture %K List Frame %K Logistic Regression %K Misclassification Error %K NASS %X

USDA’s National Agricultural Statistics Service (NASS) employs the June Area Survey (JAS) to produce annual estimates of U.S. farm numbers. The JAS is an area-frame-based survey conducted every year during the first two weeks of June. NASS also publishes an independent estimate of the number of farms from the quinquennial Census of Agriculture. Studies conducted by NASS have shown that farm number estimates from the JAS can be biased, mainly due to misclassification of agricultural tracts during the pre-screening and data collection processes. To adjust for the bias, NASS has developed a capture-recapture model that uses NASS’s list frame as the second sample, where estimation is performed based on records in the JAS with matches in the list frame. In the current paper, we describe an alternative capture-recapture approach that uses all available data from the JAS and the Census of Agriculture to correct for biases due to misclassification and to produce more stable farm number estimates.

%B JSM 2017 %G eng %U https://www.niss.org/sites/default/files/Benecha_Estim_Farms_20170929.pdf %0 Conference Proceedings %B JSM 2017 %T Restricted Multinomial Regression for a Triple-System Estimation with List Dependence %A Sartore, L. %A Benecha, H. %A Toppin, K. %A Spiegelman, C. %K Agriculture %K BigData %K Capture %K DataScience %K Dependence %K Estimation %K NASS %K Probability %K Triple-System %K Weights %X

The National Agricultural Statistics Service (NASS) conducts the U.S. Census of Agriculture every five years. In 2012, NASS began using a capture-recapture approach to adjust the Census estimates for under-coverage, non-response, and misclassification. This requires two independent samples. NASS has kept its Census Mailing List (CML) independent from its area frame, which is used for the June Area Survey (JAS) every June. NASS is exploring the use of web-scraping to develop a third list-frame (TL) that would be independent of the CML and the area frame. In this paper, a Triple-System Estimation (TSE) methodology based on regularized multinomial regression is proposed to investigate for possible dependence between the CML and the TF. A simulation study is performed to compare the performance of the estimator based on the proposed methodology, which can take into account the frame dependence with others already presented in the literature.

%B JSM 2017 %G eng %U https://www.niss.org/sites/default/files/Sartore_RestMultiReg_TSE_20170901.pdf %0 Journal Article %J Survey Methodology %T Bayesian Benchmarking of the Fay-Herriot Model Using Random Deletion. %A Nandram B. %A Erciulescu A.L. %A Cruze N. %B Survey Methodology %0 Journal Article %J Environmental and Ecological Statistics %D 2018 %T Benchmarking a Triplet of Official Estimates. %A Erciulescu A.L. %A Cruze N. %A Nandram B. %B Environmental and Ecological Statistics %V 25 %P 523-547 %N 4 %0 Journal Article %J Journal of the Royal Statistical Society %D 2018 %T Model-Based County-Level Crop Estimates Incorporating Auxiliary Sources of Information %A Erciulescu A.L. %E Cruze N. %E Nandram B. %B Journal of the Royal Statistical Society %I Journal of the Royal Statistical Society %V Series A %N DOI 10.1111/rssa.12390 %0 Conference Proceedings %B JSM Proceedings. Survey Research Methods Section. Alexandria, VA: American Statistical Association. %D 2017 %T Developments in Model-Based County Level Estimation of Agricultural Cash Rental Rates %A Bellow, Michael E. %A Cruze, Nathan %A Erciulescu, Andreea L. %B JSM Proceedings. Survey Research Methods Section. Alexandria, VA: American Statistical Association. %G eng %U https://www.niss.org/sites/default/files/2017%20-%20Developments%20in%20Model-Based%20County-Level%20Estimation%20of%20Ag%20Cash%20Rental%20Rates.pdf %& 2773 - 2790 %0 Journal Article %J ICES V Proceedings. Alexandria, VA: American Statistical Association %D 2016 %T Developments in Model-Based Estimation of County-Level Agricultural Estimates %A Cruze N.B. %A Erciulescu A.L. %A Nandram B. %A Barboza W.J. %A Young L.J. %B ICES V Proceedings. Alexandria, VA: American Statistical Association %G eng %U http://ww2.amstat.org/meetings/ices/2016/proceedings/131_ices15Final00229.pdf %0 Journal Article %J JSM Proceedings. Survey Research Methods Section. Alexandria, VA: American Statistical Association. %D 2016 %T Model-based County-Level Crop Estimates Incorporating Auxiliary Sources of Information %A Erciulescu A.L. %A Cruze N.B. %A Nandram B. %B JSM Proceedings. Survey Research Methods Section. Alexandria, VA: American Statistical Association. %G eng %U https://ww2.amstat.org/MembersOnly/proceedings/2016/data/assets/pdf/389784.pdf %& 3591-3605 %0 Journal Article %J Molecular Cell Proteomics %D 2015 %T Large-Scale Interlaboratory Study to Develop, Analytically Validate and Apply Highly Multiplexed, Quantitative Peptide Assays to Measure Cancer-Relevant Proteins in Plasma. %A Susan Abbatiello %A Birgit Schilling %A D.R. Mani %A L.I. Shilling %A S.C. Hall %A B. McLean %A M. Albetolle %A S. Allen %A M. Burgess %A M.P. Cusack %A M Gosh %A V Hedrick %A J.M. Held %A H.D. Inerowicz %A A. Jackson %A H. Keshishian %A C.R. Kinsinger %A Lyssand, JS %A Makowski L %A Mesri M %A Rodriguez H %A Rudnick P %A Sadowski P %A Nell Sedransk %A Shaddox K %A Skates SJ %A Kuhn E %A Smith D %A Whiteaker, JR %A Whitwell C %A Zhang S %A Borchers CH %A Fisher SJ %A Gibson BW %A Liebler DC %A M.J. McCoss %A Neubert TA %A Paulovich AG %A Regnier FE %A Tempst, P %A Carr, SA %X

There is an increasing need in biology and clinical medicine to robustly and reliably measure tens to hundreds of peptides and proteins in clinical and biological samples with high sensitivity, specificity, reproducibility, and repeatability. Previously, we demonstrated that LC-MRM-MS with isotope dilution has suitable performance for quantitative measurements of small numbers of relatively abundant proteins in human plasma and that the resulting assays can be transferred across laboratories while maintaining high reproducibility and quantitative precision. Here, we significantly extend that earlier work, demonstrating that 11 laboratories using 14 LC-MS systems can develop, determine analytical figures of merit, and apply highly multiplexed MRM-MS assays targeting 125 peptides derived from 27 cancer-relevant proteins and seven control proteins to precisely and reproducibly measure the analytes in human plasma. To ensure consistent generation of high quality data, we incorporated a system suitability protocol (SSP) into our experimental design. The SSP enabled real-time monitoring of LC-MRM-MS performance during assay development and implementation, facilitating early detection and correction of chromatographic and instrumental problems. Low to subnanogram/ml sensitivity for proteins in plasma was achieved by one-step immunoaffinity depletion of 14 abundant plasma proteins prior to analysis. Median intra- and interlaboratory reproducibility was <20%, sufficient for most biological studies and candidate protein biomarker verification. Digestion recovery of peptides was assessed and quantitative accuracy improved using heavy-isotope-labeled versions of the proteins as internal standards. Using the highly multiplexed assay, participating laboratories were able to precisely and reproducibly determine the levels of a series of analytes in blinded samples used to simulate an interlaboratory clinical study of patient samples. Our study further establishes that LC-MRM-MS using stable isotope dilution, with appropriate attention to analytical validation and appropriate quality control measures, enables sensitive, specific, reproducible, and quantitative measurements of proteins and peptides in complex biological matrices such as plasma.

%B Molecular Cell Proteomics %V 14 %P 2357-74 %8 09/2015 %G eng %N 9 %R 10.1074/mcp.M114.047050 %0 Book Section %D 2014 %T Confidentiality and Data Access in the Use of Big Data: Theory and Practical Approaches %A A. F. Karr %A J. P. Reiter %E J. Lane %E V. Stodden %E H. Nissenbaum %E S. Bender %I Cambridge University Press %G eng %& Analytical frameworks for data release: A statistical view %0 Book Section %D 2014 %T The New Literacies of Online Research and Comprehension: Assessing and Preparing Students for the 21st Century with Common Core State Standards %A Sedransk, N. %A Leu, D. %A Forzani, E. %A Burlingame, C. %A Kulikowich, J. %A Coiro, J. %A Kennedy, C. %E Neuman, S. B. %E Gambrell, L.B. %I International Reading Association %P to appear %G eng %& to appear %0 Journal Article %J Analytical Chemistry %D 2014 %T QC Metrics from CPTAC Raw LC-MS/MS Data Interpreted through Multivariate Statistics %A X. Wang %A M. C. Chambers %A L. J. Vega-Montoto %A D. M. Bunk %A S. E. Stein %A D. Tabb %X
Shotgun proteomics experiments integrate a complex sequence of processes, any of which can introduce variability. Quality metrics computed from LC-MS/MS data have relied upon identifying MS/MS scans, but a new mode for the QuaMeter software produces metrics that are independent of identifications. Rather than evaluating each metric independently, we have created a robust multivariate statistical toolkit that accommodates the correlation structure of these metrics and allows for hierarchical relationships among data sets. The framework enables visualization and structural assessment of variability. Study 1 for the Clinical Proteomics Technology Assessment for Cancer (CPTAC), which analyzed three replicates of two common samples at each of two time points among 23 mass spectrometers in nine laboratories, provided the data to demonstrate this framework, and CPTAC Study 5 provided data from complex lysates under Standard Operating Procedures (SOPs) to complement these findings. Identification-independent quality metrics enabled the differentiation of sites and run-times through robust principalcomponents analysis and subsequent factor analysis. Dissimilarity metrics revealed outliers in performance, and a nested ANOVA model revealed the extent to which all metrics or individual metrics were impacted by mass spectrometer and run time. Study 5 data revealed that even when SOPs have been applied, instrument-dependent variability remains prominent, although it may bereduced, while within-site variability is reduced significantly. Finally, identification-independent quality metrics were shown to bepredictive of identification sensitivity in these data sets. QuaMeter and the associated multivariate framework are available from http://fenchurch.mc.vanderbilt.edu and http://homepages.uc.edu/~wang2x7/, respectively
%B Analytical Chemistry %V 86 %P 2497 − 2509 %G eng %U http://pubs.acs.org/doi/pdf/10.1021/ac4034455 %R dx.doi.org/10.1021 %0 Conference Paper %B JSM Proceedings, Section on Survey Research Methods 2013 %D 2013 %T Construction of replicate weights for Project TALENT %A A. F. Karr %A Z. He %A M. P. Cohen %A D. Battle %A D. L. Achorn %A A. D. McKay %B JSM Proceedings, Section on Survey Research Methods 2013 %G eng %0 Journal Article %J Molecular and Cellular Proteomics %D 2013 %T Design, Implementation and Multisite Evaluation of a System Suitability Protocol for the Quantitative Assessment of Instrument Performance in Liquid Chromatography-Multiple Reaction Monitoring-MS (LC-MRM-MS) %A Abbatiello, S. %A Feng, X. %A Sedransk, N. %A Mani, DR %A Schilling, B %A Maclean, B %A Zimmerman, LJ %A Cusack, MP %A Hall, SC %A Addona, T %A Allen, S %A Dodder, NG %A Ghosh, M %A Held, JM %A Hedrick, V %A Inerowicz, HD %A Jackson, A %A Keshishian, H %A Kim, JW %A Lyssand, JS %A Riley, CP %A Rudnick, P %A Sadowski, P %A Shaddox, K %A Smith, D %A Tomazela, D %A Wahlander, A %A Waldemarson, S %A Whitwell, CA %A You, J %A Zhang, S %A Kinsinger, CR %A Mesri, M %A Rodriguez, H %A Borchers, CH %A Buck, C %A Fisher, SJ %A Gibson, BW %A Liebler, D %A Maccoss, M %A Neubert, TA %A Paulovich, A %A Regnier, F %A Skates, SJ %A Tempst, P %A Wang, M %A Carr, SA %X

Multiple reaction monitoring (MRM) mass spectrometry coupled with stable isotope dilution (SID) and liquid chromatography (LC) is increasingly used in biological and clinical studies for precise and reproducible quantification of peptides and proteins in complex sample matrices. Robust LC-SID-MRM-MS-based assays that can be replicated across laboratories and ultimately in clinical laboratory settings require standardized protocols to demonstrate that the analysis platforms are performing adequately. We developed a system suitability protocol (SSP), which employs a predigested mixture of six proteins, to facilitate performance evaluation of LC-SID-MRM-MS instrument platforms, configured with nanoflow-LC systems interfaced to triple quadrupole mass spectrometers. The SSP was designed for use with low multiplex analyses as well as high multiplex approaches when software-driven scheduling of data acquisition is required. Performance was assessed by monitoring of a range of chromatographic and mass spectrometric metrics including peak width, chromatographic resolution, peak capacity, and the variability in peak area and analyte retention time (RT) stability. The SSP, which was evaluated in 11 laboratories on a total of 15 different instruments, enabled early diagnoses of LC and MS anomalies that indicated suboptimal LC-MRM-MS performance. The observed range in variation of each of the metrics scrutinized serves to define the criteria for optimized LC-SID-MRM-MS platforms for routine use, with pass/fail criteria for system suitability performance measures defined as peak area coefficient of variation <0.15, peak width coefficient of variation <0.15, standard deviation of RT <0.15 min (9 s), and the RT drift <0.5min (30 s). The deleterious effect of a marginally performing LC-SID-MRM-MS system on the limit of quantification (LOQ) in targeted quantitative assays illustrates the use and need for a SSP to establish robust and reliable system performance. Use of a SSP helps to ensure that analyte quantification measurements can be replicated with good precision within and across multiple laboratories and should facilitate more widespread use of MRM-MS technology by the basic biomedical and clinical laboratory research communities.

%B Molecular and Cellular Proteomics %V 12 %P 2623-2639 %G eng %R 10.1074/mcp.M112.027078 %0 Journal Article %J Information Fusion %D 2012 %T Bayesian CAR models for syndromic surveillance on multiple data streams: Theory and practice %A A. F. Karr %A D. L. Banks %A G. Datta %A J. Lynch %A J. Niemi %A F. Vera %K Bayes %K CAR models %K Gibbs distribution %K Markov random field %K Syndromic surveillance %X

Syndromic surveillance has, so far, considered only simple models for Bayesian inference. This paper details the methodology for a serious, scalable solution to the problem of combining symptom data from a network of US hospitals for early detection of disease outbreaks. The approach requires high-end Bayesian modeling and significant computation, but the strategy described in this paper appears to be feasible and offers attractive advantages over the methods that are currently used in this area. The method is illustrated by application to ten quarters worth of data on opioid drug abuse surveillance from 636 reporting centers, and then compared to two other syndromic surveillance methods using simulation to create known signal in the drug abuse database.

%B Information Fusion %V 13 %P 105–116 %G eng %U http://dx.doi.org/10.1016/j.inffus.2009.10.005 %0 Journal Article %J Statistical Analysis and Data Mining %D 2012 %T Bayesian methodology for the analysis of spatial temporal surveillance data %A Zou, Jian %A Alan F. Karr %A Banks, David %A Heaton, Matthew J. %A Datta, Gauri %A Lynch, James %A Vera, Francisco %K conditional autoregressive process %K Markov random field %K spatial statistics %K spatio-temporal %K Syndromic surveillance %X

Early and accurate detection of outbreaks is one of the most important objectives of syndromic surveillance systems. We propose a general Bayesian framework for syndromic surveillance systems. The methodology incorporates Gaussian Markov random field (GMRF) and spatio-temporal conditional autoregressive (CAR) modeling. By contrast, most previous approaches have been based on only spatial or time series models. The model has appealing probabilistic representations as well as attractive statistical properties. Based on extensive simulation studies, the model is capable of capturing outbreaks rapidly, while still limiting false positives. © 2012 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 5: 194–204, 2012

%B Statistical Analysis and Data Mining %I Wiley Subscription Services, Inc., A Wiley Company %V 5 %P 194–204 %G eng %U http://dx.doi.org/10.1002/sam.10142 %R 10.1002/sam.10142 %0 Journal Article %J Statistics in Medicine %D 2012 %T A spatio-temporal absorbing state model for disease and syndromic surveillance %A M. J. Heaton %A A. F. Karr %A J. Zou %A D. L. Banks %A G. Datta %A J. Lynch %A F. Vera %X

Reliable surveillance models are an important tool in public health because they aid in mitigating disease outbreaks, identify where and when disease outbreaks occur, and predict future occurrences. Although many statistical models have been devised for surveillance purposes, none are able to simultaneously achieve the important practical goals of good sensitivity and specificity, proper use of covariate information, inclusion of spatio-temporal dynamics, and transparent support to decision-makers. In an effort to achieve these goals, this paper proposes a spatio-temporal conditional autoregressive hidden Markov model with an absorbing state. The model performs well in both a large simulation study and in an application to influenza/pneumonia fatality data.

%B Statistics in Medicine %V 31 %P 2123-2136 %G eng %0 Journal Article %J Journal of Agricultural, Biological, and Environmental Statistics %D 2011 %T A Bayesian Approach to Estimating Agricultural Yield Based on Multiple Repeated Surveys %A Jianqiang C. Wang %A S. H. Holan %A Balgobin Nandram %A Wendy Barboza %A Criselda Toto %A Edwin Anderson %K Bayesian hierarchical model %K Composite estimation %K Dynamic model %K Forecasting Model comparison %K Prediction %B Journal of Agricultural, Biological, and Environmental Statistics %V 17 %P 84-106 %8 October 29, 2011 %G eng %R 10.1007/s13253-011-0067-5 %0 Journal Article %J Computer Math Organ Theory %D 2009 %T Special issue on dynamic models for social networks %A David Banks %B Computer Math Organ Theory %V 15 %P 259-260 %8 12/2009 %G eng %& 259 %R 10.1007/s10588-009-9062-6 %0 Book Section %D 2008 %T Citizen access to government statistical information %A Alan F. Karr %E H. Chen %E L. Brandt %E V. Gregg %E R. Traunmüller %E S. Dawes %E E. Hovy %E A. Macintosh %E C. A. Larson %X

Modern electronic technologies have dramatically increased the volume of information collected and assembled by government agencies at all levels. This chapter describes digital government research aimed at keeping government data warehouses from turning into data cemeteries. The products of the research exploit modern electronic technologies in order to allow “ordinary citizens” and researchers access to government-assembled information. The goal is to help ensure that more data also means better and more useful data. Underlying the chapter are three tensions. The first is between comprehensiveness and understandability of information available to non-technically oriented “private citizens.” The second is between ensuring usefulness of detailed statistical information and protecting confidentiality of data subjects. The third tension is between the need to analyze “global” data sets and the reality that government data are distributed among both levels of government and agencies (typically, by the “domain” of data, such as education, health, or transportation).

%I Springer US %P 503-529 %G eng %& 25 %0 Journal Article %J Q. Applied Mathematics %D 2008 %T Sensitivity to noise variance in a social network dynamics model %A H. T. Banks %A H. K. Nguyen %A J. R. Samuels, Jr. %A A. F. Karr %B Q. Applied Mathematics %V 66 %P 233-247 %G eng %0 Book Section %B Encyclopedia of Risk Assessment IV %D 2008 %T Social Networks %A D. L. Banks %A N. Hengartner %K block models %K counterterrorism %K exponential family %K latent space models %K p* models %X

Social networks models are a body of statistical procedures for describing relationships between agents. The term stems from initial applications that studied interactions within human communities, but the methodology is now used much more broadly and can analyze interactions among genes, proteins, nations, and websites. In the context of risk analysis, social network models have been used to describe the formation, persistence, and breakdown of terrorist cells. They also pertain to studies of organizational behavior.

%B Encyclopedia of Risk Assessment IV %I Wiley %G eng %R 10.1002/9780470061596.risk0667 %0 Journal Article %J Annals of Statistics %D 2007 %T Computer Model Validation with Functional Output %A M.J. Bayarri %A J. Berger %A Garcia-Donato, G. %A Liu, F. %A R. Paulo %A Jerome Sacks %A Palomo, J. %A Walsh, D. %A J. Cafeo %A Parthasarathy, R. %B Annals of Statistics %V 35 %P 1874-190 %G eng %N 5 %0 Journal Article %J Statistical Methodology %D 2006 %T Data quality: A statistical perspective %A Alan F. Karr %A Ashish P. Sanil %A David L. Banks %B Statistical Methodology %V 3 %P 137–173 %G eng %0 Journal Article %J Journal of Regional Science %D 2003 %T Validation of multiclass urban travel forecasting models combining origin-destination, mode, and route choices %A Bar-Gera, H. %A Boyce, D. E. %B Journal of Regional Science %V 43 %P 517-540 %G eng %& 517 %0 Book Section %B Trade, Networks and Hierarchies %D 2002 %T Combined Model of Interregional Commodity Flows on a Transportation Network %A Boyce, David %E Hewings, Geoffrey J.D. %E Sonis, Michael %E Boyce, David %X

This chapter is motivated by two ongoing research objectives of the author. The first concerns models of flows on transportation networks. Whether the subject is personal travel or freight transportation, representation of the transportation network is necessary to determine realistically interzonal/interregional travel/transportation costs. The methodological effort required to achieve such results is nontrivial, but the issues raised by such an attempt are enlightening and worthwhile. This insight is demonstrated once more by the models considered here.

%B Trade, Networks and Hierarchies %S Advances in Spatial Science %I Springer Berlin Heidelberg %P 29-40 %@ 978-3-642-07712-8 %G eng %U http://dx.doi.org/10.1007/978-3-662-04786-6_3 %R 10.1007/978-3-662-04786-6_3 %0 Conference Proceedings %B Workshop on Foundations for Modeling and Simulation %D 2002 %T A Framework for Validating Computer Models %A M.J. Bayarri %A J. Berger %A D. Higdon %A M. Kottas %A R. Paulo %A J. Sacks %A J. Cafeo %A J. Cavendish %A C. Lin %A J. Tu %B Workshop on Foundations for Modeling and Simulation %I Society for Computer Simulation %8 2002 %G eng %0 Book Section %B Transportation Planning %D 2002 %T Origin-based Network Assignment %A Bar-Gera, Hillel %A Boyce, David %E Patriksson, Michael %E Labbé, Martine %K network optimization %K Origin-based traffic assignment %K user equilibrium %B Transportation Planning %S Applied Optimization %I Springer US %V 64 %P 1-17 %@ 978-1-4020-0546-6 %G eng %U http://dx.doi.org/10.1007/0-306-48220-7_1 %R 10.1007/0-306-48220-7_1 %0 Book Section %B Transportation Planning %D 2002 %T Origin-based Network Assignment %A Bar-Gera, Hillel %A Boyce, David %E Patriksson, Michael %E Labbé, Martine %K network optimization %K Origin-based traffic assignment %K user equilibrium %X

Most solution methods for the traffic assignment problem can be categorized as either link-based or route-based. Only a few attempts have followed the intermediate, origin-base dapproach. This paper describes the main concepts of a new, origin-based method for the static user equilibrium traffic assignment problem. Computational efficiency in time and memory makes this method suitable for large-scale networks of practical interest. Experimental results show that the new method is especially efficient in finding highly accurate solutions.

%B Transportation Planning %S Applied Optimization %I Springer US %V 64 %P 1-17 %@ 978-1-4020-0546-6 %G eng %U http://dx.doi.org/10.1007/0-306-48220-7_1 %R 10.1007/0-306-48220-7_1 %0 Conference Paper %B Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining %D 2000 %T Defection detection: Using online activity profiles to predict ISP customer vulnerability %A A. F. Karr %A N. Raghavan %A R. Bell %A M. Schonlau %A D. Pregibon %B Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining %P 506?515 %G eng %R 10.1145/347090.347193 %0 Journal Article %D 1999 %T Network equilibrium models of travel choices with multiple classes %A Boyce, D. E. %A Bar-Gera, H. %G eng %0 Conference Proceedings %B 14th International Symposium on Transportation and Traffic Theory %D 1999 %T Route flow entropy maximization in origin-based traffic assignment, transportation and traffic theory %A Bar-Gera, H. %A Boyce, D. E. %B 14th International Symposium on Transportation and Traffic Theory %I Elsevier Science %G eng %0 Conference Proceedings %B Transportation Networks: Recent Methodological Advances. Selected Proceedings of the 4th EURO Transportation Meeting %D 1999 %T Variational inequality Model of Ideal Dynamic User-Optimal Route Choice %A Boyce, D. E. %A Lee, D.-H. %A Janson, B.N. %K Advanced traffic management systems %K Advanced Traveler Information Systems %K Links (Networks) %K Route choice %K Variational inequalities (Mathematics) %X

An ideal dynamic user-optimal (DUO) route choice model is described for predicting dynamic traffic conditions, as required for off-line evaluation of Advanced Traffic Management Systems and Advanced Traveler Information Systems. The model is formulated as a variational inequality (VI), a general way of describing a dynamic network equilibrium. Although route-based VI models have an intuitive interpretation, their computational complexity makes them intractable for real applications. Consequently, the proposed model is formulated as a link-based variational inequality for use in large-scale implementations. Using the diagonalization technique with discrete time intervals, the model is solved to a specified level of convergence. Computational results for a real, large-scale traffic network are presented.

%B Transportation Networks: Recent Methodological Advances. Selected Proceedings of the 4th EURO Transportation Meeting %C Newcastle, England %P 289-302 %G eng %0 Journal Article %J Journal of the Royal Statistical Society: Series C %D 1998 %T Circuit optimization via sequential computer experiments: design of an output buffer %A Aslett, Robert %A Buck, Robert J. %A Duvall, Steven G. %A Jerome Sacks %A Welch, William J. %K Circuit simulator %K Computer code %K Computer model %K Engineering design %K Parameter design %K Stochastic process %K Visualization %X

In electrical engineering, circuit designs are now often optimized via circuit simulation computer models. Typically, many response variables characterize the circuit’s performance. Each response is a function of many input variables, including factors that can be set in the engineering design and noise factors representing manufacturing conditions. We describe a modelling approach which is appropriate for the simulator’s deterministic input–output relationships. Non-linearities and interactions are identified without explicit assumptions about the functional form. These models lead to predictors to guide the reduction of the ranges of the designable factors in a sequence of experiments. Ultimately, the predictors are used to optimize the engineering design. We also show how a visualization of the fitted relationships facilitates an understanding of the engineering trade-offs between responses. The example used to demonstrate these methods, the design of a buffer circuit, has multiple targets for the responses, representing different trade-offs between the key performance measures.

%B Journal of the Royal Statistical Society: Series C %V 47 %P 31-48 %G eng %0 Journal Article %J Journal of Educational Measurement %D 1998 %T Projecting to the NAEP Scale: Results from the North Carolina End-of-Grade Testing Program %A Williams, Valerie %A Billeaud, Kathleen %A Davis, Lori A. %A Thissen, David %A Sanford, Eleanor E. %X

Data from the North Carolina End-of-Grade test of eighth-grade mathematics are used to estimate the achievement results on the scale of the National Assessment of Educational Progress (NAEP) Trial State Assessment. Linear regression models are used to develop projection equations to predict state NAEP results in the future, and the results of such predictions are compared with those obtained in the 1996 administration of NAEP. Standard errors of the parameter estimates are obtained using a bootstrap resampling technique.

%B Journal of Educational Measurement %V 35 %P 277-296 %G eng %0 Book Section %B Knowledge and Networks in a Dynamic Economy %D 1998 %T Roadway Incident Analysis with a Dynamic User-Optimal Route Choice Model %A Boyce, D. E. %A Lee, D.-H. %A Janson, B.N. %E Beckmann, Martin J. %E Johannsson, Börje %E Snickars, Folke %E Thord, Roland %X

The transportation system conveys interdependencies. When analysing the costs and benefits of transport investment projects, it is therefore necessary to address the question of linkages among projects. Such linkages can occur in terms of economies of scale in arising from the combination of projects during the construction phase. Intelligent Transportation Systems (ITS), also known as Intelligent Vehicle Highway Systems (IVHS), are applying advanced technologies (such as navigation, automobile, computer science, telecommunication, electronic engineering, automatic information collection and processing) in an effort to bring revolutionary improvements in traffic safety, network capacity utilization, vehicle emission reductions, travel time and fuel consumption savings, etc. Within the framework of ITS, Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS) both aim to manage and predict traffic congestion and provide historical and real time network-wide traffic information to support drivers’ route choice decisions. To enable ATMS/ATIS to achieve the above described goals, traffic flow prediction models are needed for system operation and evaluation. Linkages may also arise in supply through interaction among network components, or among the producers of transportation services. Linkages may also emerge in demand through the creation of new opportunities for interaction.

%B Knowledge and Networks in a Dynamic Economy %I Springer Berlin Heidelberg %P 371-390 %@ 978-3-642-64350-7 %G eng %U http://dx.doi.org/10.1007/978-3-642-60318-1_21 %R 10.1007/978-3-642-60318-1_21 %0 Book Section %D 1998 %T SoftStat ?97: Advances in Statistical Software 6 %A A. F. Karr %A G. Eick %A A. Mockus %A T.L. Graves %E W. Badilla %E F. Faulbaum %I Lucius & Lucius %P 3-10 %G eng %& Web-based text visualization %0 Book Section %B Case Studies in Bayesian Statistics %D 1997 %T A Random-Effects Multinomial Probit Model of Car Ownership Choice %A Nobile, Agostino %A Bhat, Chandra R. %A Pas, Eric I. %E Gatsonis, Constantine %E Hodges, JamesS. %E Kass, RobertE. %E McCulloch, Robert %E Rossi, Peter %E Singpurwalla, NozerD. %K car ownership %K longitudinal data %K Multinomial probit model %X

The number of cars in a household has an important effect on its travel behavior (e.g., choice of number of trips, mode to work and non-work destinations), hence car ownership modeling is an essential component of any travel demand forecasting effort. In this paper we report on a random effects multinomial probit model of car ownership level, estimated using longitudinal data collected in the Netherlands. A Bayesian approach is taken and the model is estimated by means of a modification of the Gibbs sampling with data augmentation algorithm considered by McCulloch and Rossi (1994). The modification consists in performing, after each Gibbs sampling cycle, a Metropolis step along a direction of constant likelihood. An examination of the simulation output illustrates the improved performance of the resulting sampler.

%B Case Studies in Bayesian Statistics %S Lecture Notes in Statistics %I Springer New York %V 121 %P 419-434 %@ 978-0-387-94990-1 %G eng %U http://dx.doi.org/10.1007/978-1-4612-2290-3_13 %R 10.1007/978-1-4612-2290-3_13 %0 Book Section %B Modelling Longitudinal and Spatially Correlated Data %D 1997 %T Scaled Link Functions for Heterogeneous Ordinal Response Data* %A Xie, Minge %A Simpson, Douglas G %A Carroll, Raymond J. %E Gregoire, Timothy G. %E Brillinger, David R. %E Diggle, PeterJ. %E Russek-Cohen, Estelle %E Warren, William G. %E Wolfinger, Russell D. %K Aggregated observations %K Generalized likelihood inference %K Marginal modeling approach %K Ordinal regression %X

This paper describes a class ordinal regression models in which the link function has scale parameters that may be estimated along with the regression parameters. One motivation is to provide a plausible model for group level categorical responses. In this case a natural class of scaled link functions is obtained by treating the group level responses as threshold averages of possible correlated latent individual level variables. We find scaled link functions also arise naturally in other circumstances. Our methodology is illustrated through environmental risk assessment data where (correlated) individual level responses and group level responses are mixed.

%B Modelling Longitudinal and Spatially Correlated Data %S Lecture Notes in Statistics %I Springer New York %V 122 %P 23-36 %@ 978-0-387-98216-8 %G eng %U http://dx.doi.org/10.1007/978-1-4612-0699-6_3 %R 10.1007/978-1-4612-0699-6_3 %0 Journal Article %J Atmospheric Environment %D 1996 %T Accounting for meteorological effects in measuring urban ozone levels and trends %A Bloomfield, Peter %A Royle, Andy %A Yang, Qing %K median polish %K meteorological adjustment %K nonlinear regression %K nonparametric regression %K Ozone concentration %X

Observed ozone concentrations are valuable indicators of possible health and environmental impacts. However, they are also used to monitor changes and trends in the sources of ozone and of its precursors, and for this purpose the influence of meteorological variables is a confounding factor. This paper examines ozone concentrations and meteorology in the Chicago area. The data are described using least absolute deviations and local regression. The key relationships observed in these analyses are then used to construct a nonlinear regression model relating ozone to meteorology. The model can be used to estimate that part of the trend in ozone levels that cannot be accounted for by trends in meteorology, and to ‘adjust’ observed ozone concentrations for anomalous weather conditions.

%B Atmospheric Environment %V 30 %P 3067-3077 %G eng %& 3067 %R 10.1016/1352-2310(95)00347-910.1016/1352-2310(95)00347-9 %0 Journal Article %J Atmospheric Environment %D 1996 %T Accounting for Meteorological Effects in Measuring Urban Ozone Levels and Trends %A Bloomfield, Peter %A Royle, Andy %A Steinberg, Laura J. %A Yang, Qing %K median polish %K meteorological adjustment %K nonlinear regression %K nonparametric regression %K Ozone concentration %X

Observed ozone concentrations are valuable indicators of possible health and environmental impacts. However, they are also used to monitor changes and trends in the sources of ozone and of its precursors, and for this purpose the influence of meteorological variables is a confounding factor. This paper examines ozone concentrations and meteorology in the Chicago area. The data are described using least absolute deviations and local regression. The key relationships observed in these analyses are then used to construct a nonlinear regression model relating ozone to meteorology. The model can be used to estimate that part of the trend in ozone levels that cannot be accounted for by trends in meteorology, and to ‘adjust’ observed ozone concentrations for anomalous weather conditions.

%B Atmospheric Environment %V 30 %P 3067–3077 %G eng %N 17 %0 Journal Article %J Journal of Geophysical Research: Oceans %D 1994 %T Arctic sea ice variability: Model sensitivities and a multidecadal simulation %A Chapman, W.L. %A Welch, W. %A Bowman, K.P. %A Jerome Sacks %A Walsh, J.E. %K Arctic region %K Climate and interannual variability %K Climate and interannual variability Ice mechanics and air/sea/ice exchange processes %K Ice mechanics and air/sea/ice exchange processes %K Information Related to Geographic Region: Arctic region %K Numerical modeling %X

A dynamic-thermodynamic sea ice model is used to illustrate a sensitivity evaluation strategy in which a statistical model is fit to the output of the ice model. The statistical model response, evaluated in terms of certain metrics or integrated features of the ice model output, is a function of a selected set of d (= 13) prescribed parameters of the ice model and is therefore equivalent to a d-dimensional surface. The d parameters of the ice model are varied simultaneously in the sensitivity tests. The strongest sensitivities arise from the minimum lead fraction, the sensible heat exchange coefficient, and the atmospheric and oceanic drag coefficients. The statistical model shows that the interdependencies among these sensitivities are strong and physically plausible. A multidecadal simulation of Arctic sea ice is made using atmospheric forcing fields from 1960 to 1988 and parametric values from the approximate midpoints of the ranges sampled in the sensitivity tests. This simulation produces interannual variations consistent with submarine-derived data on ice thickness from 1976 and 1987 and with ice extent variations obtained from satellite passive microwave data. The ice model results indicate that (1) interannual variability is a major contributor to the differences of ice thickness and extent over timescales of a decade or less, and (2) the timescales of ice thickness anomalies are much longer than those of ice-covered areas. However, the simulated variations of ice coverage have less than 50% of their variance in common with observational data, and the temporal correlations between simulated and observed anomalies of ice coverage vary strongly with longitude.A dynamic-thermodynamic sea ice model is used to illustrate a sensitivity evaluation strategy in which a statistical model is fit to the output of the ice model. The statistical model response, evaluated in terms of certain metrics or integrated features of the ice model output, is a function of a selected set of d (= 13) prescribed parameters of the ice model and is therefore equivalent to a d-dimensional surface. The d parameters of the ice model are varied simultaneously in the sensitivity tests. The strongest sensitivities arise from the minimum lead fraction, the sensible heat exchange coefficient, and the atmospheric and oceanic drag coefficients. The statistical model shows that the interdependencies among these sensitivities are strong and physically plausible. A multidecadal simulation of Arctic sea ice is made using atmospheric forcing fields from 1960 to 1988 and parametric values from the approximate midpoints of the ranges sampled in the sensitivity tests. This simulation produces interannual variations consistent with submarine-derived data on ice thickness from 1976 and 1987 and with ice extent variations obtained from satellite passive microwave data. The ice model results indicate that (1) interannual variability is a major contributor to the differences of ice thickness and extent over timescales of a decade or less, and (2) the timescales of ice thickness anomalies are much longer than those of ice-covered areas. However, the simulated variations of ice coverage have less than 50% of their variance in common with observational data, and the temporal correlations between simulated and observed anomalies of ice coverage vary strongly with longitude.

%B Journal of Geophysical Research: Oceans %V 99 %P 919-935 %G eng %& 919 %R 10.1029/93JC02564 %0 Book Section %B Dynamic Urban Transportation Network Models %D 1994 %T Variational Inequality Models of Ideal Dynamic User-Optimal Route Choice Problems %A Ran, Bin %A Boyce, David E. %X

In this chapter, we present both route-based and link-based variational inequality models for the ideal dynamic user-optimal route choice problem. In Section 13.1, a route-time-based VI model for ideal DUO route choice is proposed. This model is the most straight-forward formulation of route-time-based, ideal DUO route choice conditions. In Section 13.2, a multi-group route-time-based VI model is developed. In this model, each group of travelers is associated with a disutility function. Thus, the route-based ideal DUO route choice conditions are defined for each group of travelers on the basis of travel disutilities instead of travel times only.

%B Dynamic Urban Transportation Network Models %S Lecture Notes in Economics and Mathematical Systems %I Springer Berlin Heidelberg %V 417 %P 267-290 %@ 978-3-540-58360-8 %G eng %U http://dx.doi.org/10.1007/978-3-662-00773-0_13 %R 10.1007/978-3-662-00773-0_13