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Littérature scientifique sur le sujet « Latent Models, Small Area Estimation »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 31 juillet 2025

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Articles de revues sur le sujet "Latent Models, Small Area Estimation"

Porter, Aaron T., Christopher K. Wikle, and Scott H. Holan. "Small Area Estimation via Multivariate Fay-Herriot Models with Latent Spatial Dependence." Australian & New Zealand Journal of Statistics 57, no. 1 (2015): 15–29. http://dx.doi.org/10.1111/anzs.12101.

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Choi, Jungsoon, and Andrew B. Lawson. "Bayesian spatially dependent variable selection for small area health modeling." Statistical Methods in Medical Research 27, no. 1 (2016): 234–49. http://dx.doi.org/10.1177/0962280215627184.

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Statistical methods for spatial health data to identify the significant covariates associated with the health outcomes are of critical importance. Most studies have developed variable selection approaches in which the covariates included appear within the spatial domain and their effects are fixed across space. However, the impact of covariates on health outcomes may change across space and ignoring this behavior in spatial epidemiology may cause the wrong interpretation of the relations. Thus, the development of a statistical framework for spatial variable selection is important to allow for

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Badru, Jamiu O., and Kamilu A. Saka. "Structural Equation Modeling Analysis of Equity-Based Islamic Financing for Nigerian Small-Scale Enterprises Growth." American Journal of Applied Statistics and Economics 4, no. 1 (2025): 32–40. https://doi.org/10.54536/ajase.v4i1.4424.

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This study investigates within Covariance-based Structural Equation Modeling (CV-SEM) the potential causal relationships between Islamic equity-based financing and Nigerian Small Scale Enterprises (SSEs) expansion. A quantitative survey design was employed to collect questionnaire-based, cross-sectional primary data from 512 educated SSE owners and managers in eight business districts in the Abeokuta metropolis. STATA 12.1 software was utilized to estimate CV-SEM with the maximum likelihood method. Intuitively, the Principal Component Analysis (PCA) estimator was applied to derive continuous d

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Bekalo, Daniel Biftu, Anthony Kibira Wanjoya, and Samuel Musili Mwalili. "Bayesian rank likelihood-based estimation: An application to low birth weight in Ethiopia." PLOS ONE 19, no. 5 (2024): e0303637. http://dx.doi.org/10.1371/journal.pone.0303637.

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Background Low birth weight is a significant risk factor associated with high rates of neonatal and infant mortality, particularly in developing countries. However, most studies conducted on this topic in Ethiopia have small sample sizes, often focusing on specific areas and using standard models employing maximum likelihood estimation, leading to potential bias and inaccurate coverage probability. Methods This study used a novel approach, the Bayesian rank likelihood method, within a latent traits model, to estimate parameters and provide a nationwide estimate of low birth weight and its risk

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Marcq, S., and J. Weiss. "Influence of leads widths distribution on turbulent heat transfer between the ocean and the atmosphere." Cryosphere Discussions 5, no. 5 (2011): 2765–97. http://dx.doi.org/10.5194/tcd-5-2765-2011.

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Abstract. Leads are linear-like structures of open water within the sea ice cover that develop as the result of fracturing due to divergence or shear. Through leads, air and water come into contact and directly exchange latent and sensible heat through convective processes driven by the large temperature and moisture differences between them. In the central Arctic, leads only cover 1 to 2% of the ocean during winter, but account for more than 80% of the heat fluxes. Furthermore, narrow leads (several meters) are more than twice as efficient at transmitting turbulent heat than larger ones (seve

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Marcq, S., and J. Weiss. "Influence of sea ice lead-width distribution on turbulent heat transfer between the ocean and the atmosphere." Cryosphere 6, no. 1 (2012): 143–56. http://dx.doi.org/10.5194/tc-6-143-2012.

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Abstract. Leads are linear-like structures of open water within the sea ice cover that develop as the result of fracturing due to divergence or shear. Through leads, air and water come into contact and directly exchange latent and sensible heat through convective processes driven by the large temperature and moisture differences between them. In the central Arctic, leads only cover 1 to 2% of the ocean during winter, but account for more than 70% of the upward heat fluxes. Furthermore, narrow leads (several meters) are more than twice as efficient at transmitting turbulent heat than larger one

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Nassar, Ayman, Alfonso Torres-Rua, Lawrence Hipps, et al. "Using Remote Sensing to Estimate Scales of Spatial Heterogeneity to Analyze Evapotranspiration Modeling in a Natural Ecosystem." Remote Sensing 14, no. 2 (2022): 372. http://dx.doi.org/10.3390/rs14020372.

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Understanding the spatial variability in highly heterogeneous natural environments such as savannas and river corridors is an important issue in characterizing and modeling energy fluxes, particularly for evapotranspiration (ET) estimates. Currently, remote-sensing-based surface energy balance (SEB) models are applied widely and routinely in agricultural settings to obtain ET information on an operational basis for use in water resources management. However, the application of these models in natural environments is challenging due to spatial heterogeneity in vegetation cover and complexity in

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Babel, W., S. Huneke, and T. Foken. "A framework to utilize turbulent flux measurements for mesoscale models and remote sensing applications." Hydrology and Earth System Sciences Discussions 8, no. 3 (2011): 5165–225. http://dx.doi.org/10.5194/hessd-8-5165-2011.

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Abstract. Meteorologically measured fluxes of energy and matter between the surface and the atmosphere originate from a source area of certain extent, located in the upwind sector of the device. The spatial representativeness of such measurements is strongly influenced by the heterogeneity of the landscape. The footprint concept is capable of linking observed data with spatial heterogeneity. This study aims at upscaling eddy covariance derived fluxes to a grid size of 1 km edge length, which is typical for mesoscale models or low resolution remote sensing data. Here an upscaling strategy is pr

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Klees, R., E. A. Zapreeva, H. C. Winsemius, and H. H. G. Savenije. "The bias in GRACE estimates of continental water storage variations." Hydrology and Earth System Sciences Discussions 3, no. 6 (2006): 3557–94. http://dx.doi.org/10.5194/hessd-3-3557-2006.

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Abstract. The estimation of terrestrial water storage variations at river basin scale is among the best documented applications of the GRACE (Gravity and Climate Experiment) satellite gravity mission. In particular, it is expected that GRACE closes the water balance at river basin scale and allows the verification, improvement and modeling of the related hydrological processes by combining GRACE amplitude estimates with hydrological models' output and in-situ data. When computing monthly mean storage variations from GRACE gravity field models, spatial filtering is mandatory to reduce GRACE err

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Kubokawa, Tatsuya. "Linear Mixed Models and Small Area Estimation." Japanese journal of applied statistics 35, no. 3 (2006): 139–61. http://dx.doi.org/10.5023/jappstat.35.139.

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Thèses sur le sujet "Latent Models, Small Area Estimation"

BERTARELLI, GAIA. "LATENT MARKOV MODELS FOR AGGREGATE DATA: APPLICATION TO DISEASE MAPPING AND SMALL AREA ESTIMATION." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/96252.

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Latent Markov Models (LMMs) are a particular class of statistical models in which a latent process is assumed. LMMs allow for the analysis of longitudinal data when the response variables measure common characteristics of interest, which are not directly observable. In LMMs the characteristics of interest, and their evolution in time, are represented by a latent process that follows a first order discrete Markov chain and units are allowed to change latent state over time. In studying LMMs, it is important to distinguish between two components: the measurement model, i.e. the conditional dist

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Moura, Fernando Antonio da Silva. "Small area estimation using multilevel models." Thesis, University of Southampton, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.241157.

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Oleson, Jacob J. "Bayesian spatial models for small area estimation /." free to MU campus, to others for purchase, 2002. http://wwwlib.umi.com/cr/mo/fullcit?p3052203.

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Zhang, Qiong. "Small area quantile estimation under unit-level models." Thesis, University of British Columbia, 2017. http://hdl.handle.net/2429/62871.

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Sample surveys are widely used as a cost-effective way to collect information on variables of interest in target populations. In applications, we are generally interested in parameters such as population means, totals, and quantiles. Similar parameters for subpopulations or areas, formed by geographic areas and socio-demographic groups, are also of interest in applications. However, the sample size might be small or even zero in subpopulations due to the probability sampling and the budget limitation. There has been intensive research on how to produce reliable estimates for characteristics of

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Ganesh, Nadarajasundaram. "Small area estimation and prediction problems spatial models, Bayesian multiple comparisons and robust MSE estimation /." College Park, Md. : University of Maryland, 2007. http://hdl.handle.net/1903/7241.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2007.<br>Thesis research directed by: Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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Stukel, Diana M. (Diane Maria) Carleton University Dissertation Mathematics. "Small area estimation under one and two-fold nested error regression models." Ottawa, 1991.

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Wanjoya, Antony Kibira. "A Flexible Characterization of models for small area estimation: Theoretical developments and Applications." Doctoral thesis, Università degli studi di Padova, 2011. http://hdl.handle.net/11577/3421673.

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The demand for reliable small area estimates derived from survey data has increased greatly in recent years due to, among other things, their growing use in formulating policies and programs, allocation of government funds, regional planning, small area business decisions and other applications. Traditional area-specific (direct) estimates may not provide acceptable precision for small areas because sample sizes are seldom large enough in many small areas of interest. This makes it necessary to borrow information across related areas through indirect estimation based on models, using auxiliary

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Warnholz, Sebastian [Verfasser]. "Small Area Estimation Using Robust Extensions to Area Level Models : Theory, Implementation and Simulation Studies / Sebastian Warnholz." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1112553045/34.

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Yu, Mingyu Carleton University Dissertation Mathematics. "Nested-error regression models and small area estimation combining cross-sectional and time series data." Ottawa, 1993.

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Liu, Shiao. "Bayesian Analysis of Crime Survey Data with Nonresponse." Digital WPI, 2018. https://digitalcommons.wpi.edu/etd-theses/1175.

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Bayesian hierarchical models are effective tools for small area estimation by pooling small datasets together. The pooling procedures allow individual areas to “borrow strength” from each other to desirably improve the estimation. This work is an extension of Nandram and Choi (2002), NC, to perform inference on finite population proportions when there exists non-identifiability of the missing pattern for nonresponse in binary survey data. We review the small-area selection model (SSM) in NC which is able to incorporate the non-identifiability. Moreover, the proposed SSM, together with the indi

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Livres sur le sujet "Latent Models, Small Area Estimation"

Sugasawa, Shonosuke, and Tatsuya Kubokawa. Mixed-Effects Models and Small Area Estimation. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9486-9.

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Morales, Domingo, María Dolores Esteban, Agustín Pérez, and Tomáš Hobza. A Course on Small Area Estimation and Mixed Models. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63757-6.

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Sugasawa, Shonosuke. Mixed-Effects Models and Small Area Estimation. Springer, 2023.

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Pratesi, Monica. Analysis of Poverty Data by Small Area Estimation. Wiley & Sons, Incorporated, John, 2016.

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Pratesi, Monica. Analysis of Poverty Data by Small Area Estimation. Wiley & Sons, Incorporated, John, 2015.

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Analysis of poverty data by small area estimation. John Wiley & Sons, 2016.

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Pratesi, Monica. Analysis of Poverty Data by Small Area Estimation. Wiley & Sons, Incorporated, John, 2015.

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Pratesi, Monica. Analysis of Poverty Data by Small Area Estimation. Wiley & Sons, Limited, John, 2016.

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Course on Small Area Estimation and Mixed Models: Methods, Theory and Applications in R. Springer International Publishing AG, 2022.

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Morales, Domingo, María Dolores Esteban, Agustín Pérez, and Tomás Hobza. Course on Small Area Estimation and Mixed Models: Methods, Theory and Applications in R. Springer International Publishing AG, 2021.

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Chapitres de livres sur le sujet "Latent Models, Small Area Estimation"

Longford, Nicholas T. "Small-area estimation." In Models for Uncertainty in Educational Testing. Springer New York, 1995. http://dx.doi.org/10.1007/978-1-4613-8463-2_8.

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Morales, Domingo, María Dolores Esteban, Agustín Pérez, and Tomáš Hobza. "Small Area Estimation." In A Course on Small Area Estimation and Mixed Models. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63757-6_1.

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Jiang, Jiming, and Sunil J. Rao. "More Flexible Models." In Robust Small Area Estimation. Chapman and Hall/CRC, 2025. https://doi.org/10.1201/9781003395171-5.

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Haughton, Dominique, and Jonathan Haughton. "Multilevel Models and Small-Area Estimation." In Living Standards Analytics. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4614-0385-2_13.

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Esteban, María Dolores, Domingo Morales, and Agustín Pérez. "Area-level Spatio-temporal Small Area Estimation Models." In Analysis of Poverty Data by Small Area Estimation. John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118814963.ch11.

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Sugasawa, Shonosuke, and Tatsuya Kubokawa. "Extensions of Basic Small Area Models." In Mixed-Effects Models and Small Area Estimation. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9486-9_8.

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Sugasawa, Shonosuke, and Tatsuya Kubokawa. "Advanced Theory of Basic Small Area Models." In Mixed-Effects Models and Small Area Estimation. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9486-9_6.

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Morales, Domingo, María Dolores Esteban, Agustín Pérez, and Tomáš Hobza. "Area-Level Poisson Mixed Models." In A Course on Small Area Estimation and Mixed Models. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-63757-6_20.

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Bocci, Chiara, and Alessandra Petrucci. "Spatial Information and Geoadditive Small Area Models." In Analysis of Poverty Data by Small Area Estimation. John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781118814963.ch13.

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Sugasawa, Shonosuke, and Tatsuya Kubokawa. "General Mixed-Effects Models and BLUP." In Mixed-Effects Models and Small Area Estimation. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9486-9_2.

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Actes de conférences sur le sujet "Latent Models, Small Area Estimation"

He, Jia, Changying Du, Changde Du, Fuzhen Zhuang, Qing He, and Guoping Long. "Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel." In Twenty-Sixth International Joint Conference on Artificial Intelligence. International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/254.

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Existing multi-view learning methods based on kernel function either require the user to select and tune a single predefined kernel or have to compute and store many Gram matrices to perform multiple kernel learning. Apart from the huge consumption of manpower, computation and memory resources, most of these models seek point estimation of their parameters, and are prone to overfitting to small training data. This paper presents an adaptive kernel nonlinear max-margin multi-view learning model under the Bayesian framework. Specifically, we regularize the posterior of an efficient multi-view la

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Tanabe, Yuji, and Hiromitsu Shimakawa. "Assessing Engagement of the Elderly in Active Listening from Body Movement." In 10th International Conference on Human Interaction and Emerging Technologies (IHIET 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004022.

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This study propose s a method for estimating the conversational state in active listening using voice and body movement data to facilitate for participants to exchange their words. In recent years, the problem of apathy among the elderly has run into a serious problem as the population ages. Active listening, a type of counseling technique, is useful to address the problem. In active listening, to activate the elderly person, a listener should do nothing other than listen to what the elderly person talks. However, it is difficult for the elderly person to willingly talk because they are not fa

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Sofronov, Georgy. "A hybrid algorithm for spatial small area estimation under models with complex contiguity." In 2013 IEEE Symposium on Differential Evolution (SDE). IEEE, 2013. http://dx.doi.org/10.1109/sde.2013.6601438.

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Chen, Wei, Xiaokai Huang, Zijian Li, Ruichu Cai, Zhiyi Huang, and Zhifeng Hao. "Individual Causal Structure Learning from Population Data." In Thirty-Third International Joint Conference on Artificial Intelligence {IJCAI-24}. International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/ijcai.2024/786.

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Learning the causal structure of each individual plays a crucial role in neuroscience, biology, and so on. Existing methods consider data from each individual separately, which may yield inaccurate causal structure estimations in limited samples. To leverage more samples, we consider incorporating data from all individuals as population data. We observe that the variables of all individuals are influenced by the common environment variables they share. These shared environment variables can be modeled as latent variables and serve as a bridge connecting data from different individuals. In part

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Bass, D., and K. Haddara. "Roll Damping For Small Fishing Vessels." In SNAME 22nd American Towing Tank Conference. SNAME, 1989. http://dx.doi.org/10.5957/attc-1989-050.

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The successes of Naval Architects in predicting ship motions in waves, have been mainly confined to motions other than roll. For roll motions it has long been recognized that roll damping for wave encounter frequencies near the natural roll frequency is not only an extremely significant parameter but also very difficult to predict accurately. Because of the need to consider viscous flow (or even 'slightly viscous flow') to correctly model roll damping phenomena, there is still some way to go before an adequate numerical model of the hydrodynamics of roll is forthcoming. For this reason empiric

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Drake, Arthur, Jun Wang, Qiuyi Chen, Ardalan Nejat, James Guest, and Mark Fuge. "To Quantize or Not to Quantize: Effects on Generative Models for 2D Heat Sink Design." In ASME 2024 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/detc2024-142052.

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Abstract In Topology Optimization (TO) and related engineering applications, physics-constrained simulations are often used to optimize candidate designs given some set of boundary conditions. However, such models are computationally expensive and do not guarantee convergence to a desired result, given the frequent non-convexity of the performance objective. Creating data-based approaches to warm-start these models — or even replace them entirely — has thus been a top priority for researchers in this area of engineering design. In this paper, we present a new dataset of two-dimensional heat si

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Diz-Rosales, Naomi, María José Lombardía, and Domingo Morales. "Mapping the Poverty Proportion in Small Areas under Random Regression Coefficient Poisson Models." In Congreso XoveTIC: impulsando el talento científico (6º. 2023. A Coruña). Servizo de Publicacions. Universidade da Coruña, 2023. http://dx.doi.org/10.17979/spudc.000024.18.

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In a complex socio-economic context, policy makers need highly disaggregated poverty indicators. In this work, we develop a methodology in small area estimation to derive predictors of poverty proportions under a random regression coefficient Poisson model, introducing bootstrap estimators of mean squared errors. Maximum likelihood estimators of model parameters and random effects mode predictors are calculated using a Laplace approximation algorithm. Simulation experiments are conducted to investigate the behaviour of the fitting algorithm, the predictors and the mean squared error estimator.

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Терехин, Э. А. "ASSESSMENT OF CHANGES IN THE FOREST OF CENTRAL RUSSIAN UPLAND USING REMOTE SENSING DATA." In Лесные экосистемы в условиях изменения климата: биологическая продуктивность и дистанционный мониторинг. Crossref, 2020. http://dx.doi.org/10.25686/7234.2020.6.58832.

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Оценка изменений в лесах, обусловленных влиянием негативных факторов, является одной из ключевых задач мониторинга лесных земель. В статье изложен новый подход к автоматизированному геоинформационному картографированию участков лесов с нарушенным древостоем. Метод основан на оценке изменений в высотах лесных насаждений с использованием спектрального отклика. Исследование выполнено на примере лесных массивов юга Среднерусской возвышенности, охватывающего территорию Белгородской области. Для оценки высот предложено использовать логистическую модель, описывающую зависимость коэффициентов спектрал

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Escalante, Alfredo, Manuel Sanjurjo Rivo, and Pablo Ghiglino. "Bennunet - Applying Machine Learning Techniques for Autonomous Optical Relative Navigation of an Asteroid." In ESA 12th International Conference on Guidance Navigation and Control and 9th International Conference on Astrodynamics Tools and Techniques. ESA, 2023. http://dx.doi.org/10.5270/esa-gnc-icatt-2023-015.

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Small Solar System bodies have been the target of space missions since the ICE (International Cometary Explorer) crossed the plasma tail of Comet Giacobini-Zinner on September 11, 1985, and became the first spacecraft visitor of a comet. The main challenge of navigating small bodies is that the ephemeris and physical properties of the target are typically not known with enough accuracy for orbit determination. In addition, low-gravity field and non-uniform target shape means that orbit and attitude estimation must be calculated with the spacecraft on-board computer. Among the sensors used for

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Morales-Valdez, Jesús, and Luis Alvarez-Icaza. "Building Stiffness Estimation by Wave Traveling Times." In ASME 2014 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/dscc2014-6314.

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A novel technique to estimate stiffness in buildings is presented. In contrast with most of the available work in the literature that resorts to diverse forms of modal analysis, this local technique is based on the propagation of a Ricker pulse through the structure and on measuring the wave arrival times at each story of the building, represented as a single layer in a multiple stratum model. These arrival times are later used to recuperate building stiffness at each story. Wave propagation is based on the Thomson-Haskell method, that allows to generalize the wave propagation method to multi-

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Rapports d'organisations sur le sujet "Latent Models, Small Area Estimation"

Ulloa, Alfie, and Rodrigo Wagner. Why don't All Exporters Benefit from Free Trade Agreements?: Estimating Utilization Costs. Inter-American Development Bank, 2012. http://dx.doi.org/10.18235/0011503.

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Free Trade Agreements (FTA) attract significant interest, but after these treaties are signed not all exporters use them. We provide a model of heterogeneous utilization, also developing a novel method to estimate treaty-utilization costs. We later apply the model to estimate the evolution utilization costs for the FTA between the US and a small open economy, Chile. Consistent with other studies, we find that utilization is indeed partial (on average 67% on the first year of the treaty, with 10 percentage points more at the third year). This made tariff revenues to the US 10% higher than expec

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