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Statistics of significant storm events using one- and two-dimensional analyses of the natural and protected coasts of the Dziwnow Spit

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ESTUARINE COASTAL AND SHELF SCIENCE 2024年 306卷

作者： Bugajny, Natalia Furmanczyk, Konrad Furmanczyk, Kazimierz Univ Szczecin Inst Marine & Environm Sci Szczecin Poland Warsaw Univ Life Sci Inst Informat Technol Warsaw Poland

In this paper, one- and two-dimensional statistical analyses of significant storm parameters were conducted along natural and protected coasts of the Dziwnow Spit, based on quantiles and concentration ellipses. In the onedimensional analysis, the quantiles of 0.9, 0.99 and 0.999 erosion magnitude D, sea level F, significant wave height H and storm duration T were determined, and these quantiles correspond to significant storm occurrence once every 10, 100 and 1000 years, respectively. To account for the influence of other variables on the erosion magnitude, log-linear models describing the linear dependence of log(D) on F and log(D) on F and H were built. Based on these models, the corresponding quantiles for the erosion magnitude D were also determined. In the multivariate case, using the 2-dimensional normal distribution, (log(D), F), (log(D), H), and (log(D), T) concentration ellipses were determined for the above pairs of parameters for probabilities of 0.9, 0.99 and 0.999, respectively. The application of one-dimensional distribution results in the lowest values of eroded material of dune, while the use of concentration ellipses estimates the highest values of dune erosion. Moreover, the developed log-linear models better predict the values of eroded material of dune along natural coast than on protected one.

关键词： log-linear models Multiparameter model Concentration ellipses Dune erosion Baltic sea

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Capture-Recapture Techniques for Transport Survey Estimate Adjustment Using Permanently Installed Highway-Sensors

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SOCIAL SCIENCE COMPUTER REVIEW 2021年第4期39卷 527-542页

作者： Klingwort, Jonas Buelens, Bart Schnell, Rainer Univ Duisburg Essen Res Methodol Grp Chair Prof Dr Rainer Schnell Duisburg Germany Univ Duisburg Essen Chair Social Res Methodol Duisburg Germany Stat Netherlands Ctr Big Data Stat Heerlen Netherlands VITO Mol Belgium

In this article, survey, sensor, and administrative data are combined to correct for survey point estimate bias due to underreporting. The response to the Dutch Road Freight Transport Survey is linked to records from a road sensor network consisting of automated weighing stations installed on highways in the Netherlands. Capture-recapture (CRC) methods are used to estimate underreporting in the survey. Heterogeneity of the vehicles with respect to capture and recapture probabilities is modeled through logistic regression and log-linear models. Six different estimators are discussed and compared. Results show a downward bias in the survey estimate due to underreporting, whereas the CRC estimators yield larger estimates. This research is a new example of multisource statistics, a promising approach to improve the benefits of sensor data in the field of official statistics.

关键词： big data administrative data data validation record linkage multisource statistics estimation of population size dual-system estimator Lincoln-Petersen estimator Huggins model log-linear models weigh-in-motion underreporting

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Multiple Systems Estimation for Sparse Capture Data: Inferential Challenges When There Are Nonoverlapping Lists

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JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION 2021年第535期116卷 1297-1306页

作者： Chan, Lax Silverman, Bernard W. Vincent, Kyle Univ Nottingham Rights Lab Nottingham NG7 2RD England

Multiple systems estimation strategies have recently been applied to quantify hard-to-reach populations, particularly when estimating the number of victims of human trafficking and modern slavery. In such contexts, it is not uncommon to see sparse or even no overlap between some of the lists on which the estimates are based. These create difficulties in model fitting and selection, and we develop inference procedures to address these challenges. The approach is based on Poisson log-linear regression modeling. Issues investigated in detail include taking proper account of data sparsity in the estimation procedure, as well as the existence and identifiability of maximum likelihood estimates. A stepwise method for choosing the most suitable parameters is developed, together with a bootstrap approach to finding confidence intervals for the total population size. We apply the strategy to two empirical datasets of trafficking in US regions, and find that the approach results in stable, reasonable estimates. An accompanying R software implementation has been made publicly available. for this article are available online.

关键词： Human trafficking log-linear models Mark-recapture Model identifiability Model selection Modern slavery

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Latent Class Analysis for Estimating an Unknown Population Size-with Application to Censuses

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JOURNAL OF OFFICIAL STATISTICS 2021年第3期37卷 673-697页

作者： Baffour, Bernard Brown, James J. Smith, Peter W. F. Australian Natl Univ Sch Demog Canberra ACT Australia Univ Technol Sydney UTS Sch Math & Phys Sci Sydney NSW Australia Univ Southampton Dept Social Stat & Demog Southampton Hants England

Estimation of the unknown population size using capture-recapture techniques relies on the key assumption that the capture probabilities are homogeneous across individuals in the population. This is usually accomplished via post-stratification by some key covariates believed to influence individual catchability. Another issue that arises in population estimation from data collected from multiple sources is list dependence, where an individual's catchability on one list is related to that of another list. The earlier models for population estimation heavily relied upon list independence. However, there are methods available that can adjust the population estimates to account for dependence among lists. In this article, we propose the use of latent class analysis through log-linear modelling to estimate the population size in the presence of both heterogeneity and list dependence. The proposed approach is illustrated using data from the 1988 US census dress rehearsal.

关键词： Capture-recapture latent class analysis log-linear models

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Quasi-independence models with rational maximum likelihood estimator

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JOURNAL OF SYMBOLIC COMPUTATION 2021年 104卷 917-941页

作者： Coons, Jane Ivy Sullivant, Seth North Carolina State Univ Dept Math Raleigh NC 27695 USA

We classify the two-way quasi-independence models (independence models with structural zeros) that have rational maximum likelihood estimators, or MLEs. We give a necessary and sufficient condition on the bipartite graph associated to the model for the MLE to be rational. In this case, we give an explicit formula for the MLE in terms of combinatorial features of this graph. We also use the Horn uniformization to show that for general log-linear models Mwith rational MLE, any model obtained by restricting to a face of the cone of sufficient statistics of Malso has rational MLE. (C) 2020 Elsevier Ltd. All rights reserved.

关键词： Algebraic statistics Maximum likelihood estimation Quasi-independence models log-linear models Maximum likelihood degree

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Hierarchical models for independence structures of networks

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STATISTICA NEERLANDICA 2020年第3期74卷 439-457页

作者： Sadeghi, Kayvan Rinaldo, Alessandro UCL Dept Stat Sci Gower St London WC1E 6BT England Carnegie Mellon Univ Dept Stat & Data Sci Pittsburgh PA 15213 USA

We introduce a new family of network models, called hierarchical network models, that allow us to represent in an explicit manner the stochastic dependence among the dyads (random ties) of the network. In particular, each member of this family can be associated with a graphical model defining conditional independence clauses among the dyads of the network, called the dependency graph. Every network model with dyadic independence assumption can be generalized to construct members of this new family. Using this new framework, we generalize the Erdos-Renyi and the beta models to create hierarchical Erdos-Renyi and beta models. We describe various methods for parameter estimation, as well as simulation studies for models with sparse dependency graphs.

关键词： dependency graph exponential random graph models graphical models log-linear models social network analysis

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Asymptotic cumulants of the minimum phi-divergence estimator for categorical data under possible model misspecification

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2020年第10期49卷 2448-2465页

作者： Ogasawara, Haruhiko Otaru Univ 3-5-21 Midori Otaru Hokkaido 0478501 Japan

The asymptotic cumulants of the minimum phi-divergence estimators of the parameters in a model for categorical data are obtained up to the fourth order with the higher-order asymptotic variance under possible model misspecification. The corresponding asymptotic cumulants up to the third order for the studentized minimum phi-divergence estimator are also derived. These asymptotic cumulants, when a model is misspecified, depend on the form of the phi-divergence. Numerical illustrations with simulations are given for typical cases of the phi-divergence, where the maximum likelihood estimator does not necessarily give best results. Real data examples are shown using log-linear models for contingency tables.

关键词： Asymptotic variance bias skewness studentization mean square error log-linear models

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Longitudinal networks of dyadic relationships using latent trajectories: evidence from the European interbank market

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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS 2020年第4期69卷 711-739页

作者： Bianchi, Federica Bartolucci, Francesco Peluso, Stefano Mira, Antonietta Univ Svizzera Italiana Lugano Switzerland Univ Perugia Perugia Italy Univ Cattolica Sacro Cuore Milan Italy Univ Insubria Como Italy

Financial markets are ultimately seen as a collection of dyadic transactions. We study the temporal evolution of dyadic relationships in the European interbank market, as induced by monetary transactions registered in the electronic market for interbank deposits (e-MID) during a period of 10 years (2006-2015). In particular, we keep track of how reciprocal exchange patterns have varied with macro events and exogenous shocks and with the emergence of the Global Financial Crisis in 2008. The approach adopted extends the model of Holland and Leinhardt to a longitudinal setting where individuals' temporal trajectories for the tendency to connect and reciprocate transactions are explicitly modelled through splines or polynomials, and individual-specific parameters. We estimate the model by an iterative algorithm that maximizes the log-likelihood for every ordered pair of units. The empirical application shows that the methodology proposed may be applied to large networks and represents the process of exchange at a fine-grained level. Further results are available in on-line supplementary material.

关键词： Financial networks Global Financial Crisis log-linear models p(1)- and p(2)-models Reciprocity

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Selecting a Presmoothing Model in Kernel Equating 1

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84th Psychometric Society Meeting

作者： Wallin, Gabriel Wiberg, Marie Univ Cote dAzur Maasai Res Team INRIA Sophia Antipolis France Univ Cote dAzur Lab JA Dieudonne INRIA Sophia Antipolis France Umea Univ Dept Stat USBE Umea Sweden

ISBN: (数字)9783030434694

ISBN: (纸本)9783030434717;9783030434694;9783030434687

In the kernel method of test score equating, the first step of the procedure is to presmooth the score distributions. The most common way of doing so is by fitting a log-linear model to the observed-score distributions. In this way, irregularities in the score distributions are smoothed, yielding a more stable estimated equating transformation. Within the kernel equating framework, an alternative way of presmoothing by using item response theory models has recently been suggested. There are furthermore several model selection criteria available for both of these classes of models. Here the model selection criteria are studied for both log-linear and item response theory models. Specifically, the likelihood ratio, AIC, and BIC measures are compared using real admissions data. Results show that the different model selection criteria result in equated scores that have real impact differences.

关键词： Model selection log-linear models Item response theory

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Predicting the site-specific distribution of agrochemical spray deposition in vineyards at multiple phenological stages using 2D LiDAR-based primary canopy attributes

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COMPUTERS AND ELECTRONICS IN AGRICULTURE 2021年 189卷 106402-106402页

作者： Cheraiet, A. Naud, O. Carra, M. Codis, S. Lebeau, F. Taylor, J. Univ Montpellier INRAE Inst Agro ITAP 361 Rue Jean Francois Breton F-34000 Montpellier France IFV French Vine & Wine Inst 3430 Route Espiguette Le Grau Du Roi France Univ Liege Gembloux Agrobio Tech TERRA Teaching & Res Ctr Biosyst Dynam & Exchanges BioDynE Gembloux Belgium

Predicting the dose to be applied on the basis of the structural characteristics of the plant canopy is a crucial step for the optimization of the spraying process. Mobile 2D LiDAR sensor data and local measurements of deposition rates from a face-to-face sprayer were made across eight fields in two Mediterranean vineyards at four dates in 2016 and 2017. Primary canopy attributes (height, width and density) were calculated from the LiDAR sensor data and the leaf wall area (LWA) determined. Multivariate models to predict the deposition distribution, as deciles, as a function of the primary canopy attributes were constructed and calibrated using the 2017 data and validated against the 2016 data. The prediction quality and uncertainty of these multivariate statistical models at various stages of growth was evaluated by comparison with a previously proposed univariate deposition models based on LWA at the same growth stages. The results showed that multivariate models can predict the distribution of deposits from a typical face-to-face sprayer more accurately (0.76 < R2 < 0.94), and robustly (10% < nRMSEp < 24%) than LWA-based univariate prediction models over the whole growing season. This improvement was especially clear for the lowest deciles (D1 to D5) of the deposition distribution. Results also demonstrated the importance of canopy density to provide relevant and complementary information to canopy dimensions when predicting deposition deciles with the multivariate models. The improved ability of multivariate models to predict underestimated deposition (-1.5% < bias < -3.2%) when compared to univariate models makes it possible to consider a reduction in the plant protection products while guaranteeing a safety margin for winegrowers when spraying. These predictive multivariate models could enable variable-rate sprayers to modulate doses at an intra-plot scale, which would allow a potential reduction in the quantities of plant protection products to be applied.

关键词： Canopy density Variable-rate spraying 3D vine Leaf Wall Area log-linear models

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