Gotowe bibliografie tematyczne / Auxiliary variable

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Gotowa bibliografia na temat „Auxiliary variable”

Autor: Grafiati

Data publikacji: 4 czerwca 2021

Data aktualizacji: 17 czerwca 2025

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Artykuły w czasopismach na temat "Auxiliary variable"

Kaur, Harinder, and M. K Sharma. "Efficient Estimators of Population Variance Using Known Population Mode & Variance of Auxiliary Variable." International Journal of Scientific Engineering and Research 4, no. 10 (2016): 108–16. https://doi.org/10.70729/ijser151036.

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Cabrera-Álvarez, Pablo. "Datos agregados para corregir los sesgos de no respuesta y de cobertura en encuestas." Empiria. Revista de metodología de ciencias sociales, no. 49 (December 30, 2020): 39. http://dx.doi.org/10.5944/empiria.49.2021.29231.

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En las últimas décadas la incidencia creciente de los sesgos de no respuesta y cobertura en las encuestas han puesto en entredicho la capacidad de inferir los resultados a la población. Una forma extendida de corregir los sesgos de no respuesta y cobertura en las encuestas es el uso de ponderaciones que equilibran la muestra final de entrevistados. La construcción de ponderaciones requiere información auxiliar, totales poblacionales que estén disponibles para los que responden y para los que no cooperan. En este trabajo, a partir de simulaciones estadísticas, se comprueba la capacidad de la información agregada para corregir el sesgo de no respuesta. Para ello se comparan el ajuste con datos individuales y el sistema de datos agregados, dando como resultado que el uso de datos agregados puede ser útil si se cumplen tres requisitos: 1) la variable estimada está agrupada, 2) la variable estimada y la auxiliar están correlacionadas y 3) la probabilidad de completar la encuesta está relacionada con la variable auxiliar.In the last decades the effect of nonresponse and coverage bias in surveys have questioned the ability of inferring the results to the population. An extended procedure used to correct nonresponse and coverage problems is the use of weights to balance the sample of respondents. However auxiliary information available for respondents and nonrespondents is required to compute weights. In this paper statistical simulations are used to test the potential of aggregate data to correct nonresponse bias. This research compares individual data adjustments to the use of auxiliary aggregate data. The results show the use of aggregate data can improve survey representativity if three requirements are met: 1) the dependent variable is grouped, 2) the dependent and auxiliary variables are correlated and 3) the auxiliary variable is correlated with response propensities.

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Yadav, S. K., O. P. Yadav, and D. K. Yadav. "Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error." International Journal of Mathematical, Engineering and Management Sciences 4, no. 6 (2019): 1307–24. http://dx.doi.org/10.33889/ijmems.2019.4.6-103.

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In this scripture, we ponder the problem of efficient estimation of population mean of study variable utilizing information on highly correlated auxiliary variables under the presence of non-response on either of the variables. For this purpose, we suggest, an improved estimator under three different situations of non-response. Under the first situation, estimation of population mean is done with the problem of non-response on both the study and the auxiliary variables with the additional condition that the population means of the auxiliary variables are known. The second situation is to estimate the population mean of primary variable when the problem of non-response is only on the primary variable but the population means of the auxiliary variables are known while under the third situation estimation is performed with the problem of non-response on both the study and the auxiliary variables but population mean of one of the auxiliary variables is unknown. We study the sampling properties of the suggested estimator under above three different situations of non-response. We compare the proposed estimator with the competing estimators of population mean, under three different situations of non-response. The efficiency conditions are obtained for all three situations. A numerical study is also carried out to verify the efficiency conditions.

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Gupta, Ruchi, and Sangeeta Malik. "Evaluating New Estimators in Ranked Set Sampling Using Auxiliary Variable." International Journal of Science and Research (IJSR) 13, no. 8 (2024): 1494–97. http://dx.doi.org/10.21275/sr24824152543.

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Kanwai, M. E., O. E. Asiribo, and A. Isah. "Use of Auxiliary Variables and Asymptotically Optimum Estimators in Double Sampling." International Journal of Statistics and Probability 5, no. 3 (2016): 55. http://dx.doi.org/10.5539/ijsp.v5n3p55.

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This paper explore the need for exploiting auxiliary variables in sample survey and utilizing asymptotically optimum estimator in double sampling to increase the efficiency of estimators. The study proposed two types of estimators with two auxiliary variables for two phase sampling when there is no information about auxiliary variables at population level. The expressions for the Mean Squared Error (MSE) of the proposed estimators were derived to the first order of approximation. An empirical comparative approach of the minimum variances and percent relative efficiency were adopted to study the efficiency of the proposed and existing estimators. It was established that, the proposed estimators performed more efficiently than the mean per unit estimator and other previous estimators that don’t use auxiliary variable and that are not asymptotically optimum. Also, it was established that estimators that are asymptotically optimum that utilized single auxiliary variable are more efficient than those that are not asymptotically optimum with two auxiliary variables.

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Chutiman. "ADAPTIVE CLUSTER SAMPLING USING AUXILIARY VARIABLE." Journal of Mathematics and Statistics 9, no. 3 (2013): 249–55. http://dx.doi.org/10.3844/jmssp.2013.249.255.

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Feng, Shiyong, and Guohua Zou. "Sample rotation method with auxiliary variable." Communications in Statistics - Theory and Methods 26, no. 6 (1997): 1497–509. http://dx.doi.org/10.1080/03610929708831996.

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Wang, Ting, Xiaofei Wang, Haibo Zhou, Jianwen Cai, and Stephen L. George. "Auxiliary variable-enriched biomarker-stratified design." Statistics in Medicine 37, no. 30 (2018): 4610–35. http://dx.doi.org/10.1002/sim.7938.

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Chhalotre, Rakesh, B. Samuel Naik, V. C. Karthik, et al. "Evaluating Model-assisted Estimators: A Comparative Study in High-dimensional Survey Data." Journal of Scientific Research and Reports 30, no. 9 (2024): 707–18. http://dx.doi.org/10.9734/jsrr/2024/v30i92398.

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Model-assisted estimators have gained significant attention due to their ability to efficiently utilize auxiliary information during the estimation process. These estimators rely on a working model that links the survey variable to the auxiliary variables, which is then fitted to the sample data to generate predictions. These predictions are subsequently integrated into the estimation procedures. In this study, were explores various model-assisted estimators including Generalized Regression (GREG), Ridge regression, Lasso regression, CART (Classification and Regression Tree), Random Forest, Cubist and Principal Components Regression (PCR) estimator. The analysis involved 2,000 samples of size 50 (n/N ≈ 10%) and employed a stepwise variable selection method to determine the most significant auxiliary variables, incrementally adding them to the model. The performance of these estimators was assessed using relative bias (RB), relative root mean square error (RRMSE) and relative efficiency (RE). Our findings reveal that tree-based models like CART and Random Forest and penalized regression estimators such as Ridge and Lasso display robustness with increased number of auxiliary variables. Among all the estimators, Random Forest consistently yielded the lowest RRMSE, particularly with five auxiliary variables, demonstrating superior efficiency. Conversely, the GREG estimator exhibited poor performance as the number of auxiliary variables increased. This study underscores the importance of selecting suitable model-assisted estimation procedures tailored to the data characteristics and the relationship between survey and auxiliary variables within this high-dimensional dataset.

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Erciulescu, Andreea L., and Wayne A. Fuller. "Small area prediction under alternative model specifications." Statistics in Transition new series 17, no. 1 (2016): 9–24. http://dx.doi.org/10.59170/stattrans-2016-001.

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Construction of small area predictors and estimation of the prediction mean squared error, given different types of auxiliary information are illustrated for a unit level model. Of interest are situations where the mean and variance of an auxiliary variable are subject to estimation error. Fixed and random specifications for the auxiliary variables are considered. The efficiency gains associated with the random specification for the auxiliary variable measured with error are demonstrated. A parametric bootstrap procedure is proposed for the mean squared error of the predictor based on a logit model. The proposed bootstrap procedure has smaller bootstrap error than a classical double bootstrap procedure with the same number of samples.

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Rozprawy doktorskie na temat "Auxiliary variable"

Vanetti, Paul Justin Cesare. "Auxiliary variable transformations for intractable distributions." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/44340.

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Expectations over probability distributions can be approximated by Markov chain Monte Carlo methods when the density can be evaluated up to a normalizing constant. However, there exist cases where this density takes on the form of an intractable integral and therefore cannot be computed exactly. We explore a class of auxiliary variable methods which allow correct sampling from such distributions. In some cases, existing approaches which employ these methods can be inefficient, requiring long computation times. We identify causes for this inefficiency and demonstrate how this can be improved when we can develop a reasonable importance sampling estimate of the integral. We discuss applications for our methods, placing a particular focus on the Dirichlet process with a non-conjugate base distribution. We show how the auxiliary variables can be interpreted in this non-parametric context, and how we can develop proposals which provide greater computational efficiency.

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Graham, Matthew McKenzie. "Auxiliary variable Markov chain Monte Carlo methods." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/28962.

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Markov chain Monte Carlo (MCMC) methods are a widely applicable class of algorithms for estimating integrals in statistical inference problems. A common approach in MCMC methods is to introduce additional auxiliary variables into the Markov chain state and perform transitions in the joint space of target and auxiliary variables. In this thesis we consider novel methods for using auxiliary variables within MCMC methods to allow approximate inference in otherwise intractable models and to improve sampling performance in models exhibiting challenging properties such as multimodality. We first consider the pseudo-marginal framework. This extends the Metropolis–Hastings algorithm to cases where we only have access to an unbiased estimator of the density of target distribution. The resulting chains can sometimes show ‘sticking’ behaviour where long series of proposed updates are rejected. Further the algorithms can be difficult to tune and it is not immediately clear how to generalise the approach to alternative transition operators. We show that if the auxiliary variables used in the density estimator are included in the chain state it is possible to use new transition operators such as those based on slice-sampling algorithms within a pseudo-marginal setting. This auxiliary pseudo-marginal approach leads to easier to tune methods and is often able to improve sampling efficiency over existing approaches. As a second contribution we consider inference in probabilistic models defined via a generative process with the probability density of the outputs of this process only implicitly defined. The approximate Bayesian computation (ABC) framework allows inference in such models when conditioning on the values of observed model variables by making the approximation that generated observed variables are ‘close’ rather than exactly equal to observed data. Although making the inference problem more tractable, the approximation error introduced in ABC methods can be difficult to quantify and standard algorithms tend to perform poorly when conditioning on high dimensional observations. This often requires further approximation by reducing the observations to lower dimensional summary statistics. We show how including all of the random variables used in generating model outputs as auxiliary variables in a Markov chain state can allow the use of more efficient and robust MCMC methods such as slice sampling and Hamiltonian Monte Carlo (HMC) within an ABC framework. In some cases this can allow inference when conditioning on the full set of observed values when standard ABC methods require reduction to lower dimensional summaries for tractability. Further we introduce a novel constrained HMC method for performing inference in a restricted class of differentiable generative models which allows conditioning the generated observed variables to be arbitrarily close to observed data while maintaining computational tractability. As a final topicwe consider the use of an auxiliary temperature variable in MCMC methods to improve exploration of multimodal target densities and allow estimation of normalising constants. Existing approaches such as simulated tempering and annealed importance sampling use temperature variables which take on only a discrete set of values. The performance of these methods can be sensitive to the number and spacing of the temperature values used, and the discrete nature of the temperature variable prevents the use of gradient-based methods such as HMC to update the temperature alongside the target variables. We introduce new MCMC methods which instead use a continuous temperature variable. This both removes the need to tune the choice of discrete temperature values and allows the temperature variable to be updated jointly with the target variables within a HMC method.

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Sousa, Rita Cristina Pinto de. "Parameter estimation in the presence of auxiliary information." Doctoral thesis, Faculdade de Ciências e Tecnologia, 2013. http://hdl.handle.net/10362/11295.

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Dissertação para obtenção do Grau de Doutora em Estatística e Gestão de Risco, Especialidade em Estatística<br>In survey research, there are many situations when the primary variable of interest is sensitive. The sensitivity of some queries can give rise to a refusal to answer or to false answers given intentionally. Survey can be conducted in a variety of settings, in part dictated by the mode of data collection, and these settings can differ in how much privacy they offer the respondent. The estimates obtained from a direct survey on sensitive questions would be subject to high bias. A variety of techniques have been used to improve reporting by increasing the privacy of the respondents. The Randomized Response Technique (RRT), introduced byWarner in 1965, develops a random relation between the individual’s response and the question. This technique provides confidentiality to respondents and still allows the interviewers to estimate the characteristic of interest at an aggregate level. In this thesis we propose some estimators to improve the mean estimation of a sensitive variable based on a RRT by making use of available non-sensitive auxiliary information. In the first part of this thesis we present the ratio and the regression estimators as well as some generalizations in order to study the gain in the estimation over the ordinary RRT mean estimator. In chapters 4 and 5 we study the performance of some exponential type estimators, also based on a RRT. The final part of the thesis illustrates an approach to mean estimation in stratified sampling. This study confirms some previous results for a different sample design. An extensive simulation study and an application to a real dataset are done for all the study estimators to evaluate their performance. In the last chapter we present a general discussion referring to the main results and conclusions as well as showing an application to a real dataset which compares the performance of study estimators.

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Tüchler, Regina. "Bayesian Variable Selection for Logistic Models Using Auxiliary Mixture Sampling." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2006. http://epub.wu.ac.at/984/1/document.pdf.

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The paper presents an Markov Chain Monte Carlo algorithm for both variable and covariance selection in the context of logistic mixed effects models. This algorithm allows us to sample solely from standard densities, with no additional tuning being needed. We apply a stochastic search variable approach to select explanatory variables as well as to determine the structure of the random effects covariance matrix. For logistic mixed effects models prior determination of explanatory variables and random effects is no longer prerequisite since the definite structure is chosen in a data-driven manner in the course of the modeling procedure. As an illustration two real-data examples from finance and tourism studies are given. (author's abstract)<br>Series: Research Report Series / Department of Statistics and Mathematics

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Mao, Wenjin. "Dimension jumping and auxiliary variable techniques for Markov chain Monte Carlo algorithms." Connect to online resource, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3284426.

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Lindberg, Mattias, and Peter Guban. "Auxiliary variables a weight against nonresponse bias : A simulation study." Thesis, Stockholms universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-142977.

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Today’s surveys face a growing problem with increasing nonresponse. The increase in nonresponse rate causes a need for better and more effective ways to reduce the nonresponse bias. There are three major scientific orientation of today’s research dealing with nonresponse. One is examining the social factors, the second one studies different data collection methods and the third investigating the use of weights to adjust estimators for nonresponse. We would like to contribute to the third orientation by evaluating estimators which use and adjust weights based on auxiliary variables to balance the survey nonresponse through simulations. For the simulation we use an artificial population consisting of 35455 participants from the Representativity Indicators for Survey Quality project. We model three nonresponse mechanisms (MCAR, MAR and MNAR) with three different coefficient of determination s between our study variable and the auxiliary variables and under three response rates resulting in 63 simulation scenarios. The scenarios are replicated 1000 times to acquire the results. We outline our findings and results for each estimator in all scenarios with the help of bias measures.

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Lasseigne, Alexis. "Optimization of variable-thickness composite structures. Application to a CROR blade." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSEM006/document.

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Cette thèse aborde la problématique de la conception optimale de structures composites stratifiées d’épaisseur variable. Les variables d’empilement définissent un problème d’optimisation combinatoire et des espaces de décisions de grande taille et potentiellement multimodaux. Les algorithmes d’optimisation stochastiques permettent de traiter ce type de problème et de tirer profit des performances et de l’anisotropie des plis composites pour l’allègement des structures composites stratifiées. Le but de cette étude est double : (i) développer un algorithme d’optimisation dédié aux composites stratifiés d’épaisseur variable et (ii) estimer le potentiel des composites stratifiés pour la maîtrise des performances aérodynamiques d’une pale de CROR composite.Dans la première partie de cette thèse, un algorithme évolutionnaire est spécialisé pour l’optimisation de tables de drapage et la gestion d’un ensemble de règles de conception représentatif des pratiques de l’industrie. Pour se faire, un encodage spécifique des solutions est proposé et des opérateurs de variations spécialisés sont développés.Dans la deuxième partie, l’algorithme est enrichi d’une technique de guidage basée sur l’exploitation d’un espace auxiliaire afin d'accroître son efficacité et d’intégrer davantage de connaissances des composites dans la résolution du problème.Finalement, la méthode est appliquée pour la conception d’une pale de CROR composite à l’échelle de la maquette de soufflerie. Au préalable, des processus itératifs de mise à froid et mise à chaud de la pale sont mis en place afin d’estimer la forme de la pale au repos et l’état de contraintes dans la pale en fonctionnement<br>This thesis deals with the optimal design of variable-thickness laminated composite structures. The stacking variables define a combinatorial optimization problem and large decision spaces which are potentially multimodal. Stochastic optimization algorithms allow solving this type of problem and allow taking advantage from the performance and the anisotropic nature of unidirectional composite plies to lighten laminated composite structures.The purpose of this study is twofold: (i) developing an optimization algorithm dedicated to variable-thickness laminated composites and (ii) assessing the potential of laminated composites in influencing the aerodynamic performances of a composite CROR blade.Firstly, an evolutionary algorithm is specialized in order to optimize layup tables and handle a set of design guidelines which is representative of industrial practices. In this purpose, a specific encoding of the solutions is suggested and specialized variation operators are developed.Secondly, the algorithm is enriched with a guiding technique based on the exploitation of an auxiliary space in order to improve its efficiency and to include further composites-related knowledge for the resolution of the problem.Finally, the method is applied for the design of a reduced-scale composite CROR blade intended for wind-tunnel testing. Beforehand, iterative processes are implemented to estimate the shape of the non-operating blade and the stress state within the operating blade

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Achelpohl, Scott Alan. "Analysis of an Existing Coal Fired Power Generation Facility with Recommendations for Efficiency and Production Improvement." OpenSIUC, 2010. https://opensiuc.lib.siu.edu/theses/378.

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This study examined the Lake of Egypt Power Plant operated by Southern Illinois Power Cooperative located on the Lake of Egypt south of Marion, IL. The facility has a 173 MW rated turbine operating on a pulverized coal cyclone boiler and three 33 MW rated turbines operating on an oversized circulating fluidized bed boiler with 120 MW capacity. The first area examined was reduction of auxiliary power consumption possible with the addition of variable frequency drives to the forced draft fan and booster fan motors. Included in this examination was an analysis of the economic and environmental impact of such a reduction. From the analysis an annual savings of 24.4 GWh of electricity is possible. The second area examined was the generation capacity lost due to condenser fouling and the possible reduction in facility emissions with altered condenser treatment. From the analysis an additional 3.0 MW of capacity facility wide is possible or a reduction steam production of 1.5% for each boiler.

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Green, Jeffrey Andrew. "IMPROVING THE ENERGY EFFICIENCY OF A MID-SIZE POWER PLANT BY REDUCTION IN AUXILIARY POWER AND IMPROVED HEAT TRANSFER." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/theses/1502.

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This study incorporates the potential use of Variable Frequency Drives on various motors as well as areas of improved heat transfer in an older, mid-sized coal fired power plant. In power plants, fluid flow rates are often controlled using dampers or valves while the motors that power the pumps stay at full speed resulting in a significant amount of wasted electrical power; energy is also lost due to poor heat recovery prior to gases leaving the system. By examining pump usage as well as additional heat available for recovery, potential energy savings will be determined. Preliminary results of five motors suggested for variable frequency drive application show annual savings that total 31.1 GWh, resulting in a 1.66% increase in overall plant efficiency. Total project costs are near $2 million resulting in a simple payback period of less than two years assuming 0.04 $/kWh. For every degree reduction of the flue gas temperature by means of heat recovery that is reused elsewhere in the cycle, 2 Billion BTU of coal would be saved annually. One realistic scenario suggested heat recovery resulting in a 120°F degree reduction of flue gas temperature amounting to a 2.54% increase in cycle efficiency.

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DE, PAOLA ROSITA. "Median estimation using auxiliary variables." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2012. http://hdl.handle.net/10281/36075.

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In the present study the estimation of the median has been taken into consideration using different methods of analysis. First of all the estimation of the median without auxiliary information is analyzed. Then the method of Kuk and Mak proposed in 1989 is exposed: this way of estimating the median is based on the knowledge of the population median of auxiliary variable X. Another method, which considers the median of the auxiliary variable is the ratio estimator. Then two methods based on the regression estimator are analyzed : the first one considers the regression based on the median regression, the second one is based on the minimum square method. Two experiments have been carried out in order to compare the methods proposed. First of all the methods are compared selecting all possible samples from nine di_erent small populations. The second application is based on the selection of couples of random numbers from a bivariate random variable distributed as a Bivariate Log-Normal distribution. Also in this situation the methods of estimation of the median are compared considering the expected values and mean square errors.

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Książki na temat "Auxiliary variable"

Bedier, Mostafa Abdellatif. Post stratified estimation using a known auxiliary variable. Oregon State University, 1989.

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Owen, Benjamin, and United States. National Aeronautics and Space Administration., eds. Development of a computer algorithm for the analysis of variable -frequency A.C. drives: Case studies included. National Aeronautics and Space Administration, 1991.

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Spanos, Aris. Omitted variables and misspecification testing using auxiliary regressions. Birkbeck College, Dept. of Economics, 1985.

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Wywiał, Janusz L. Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63413-4.

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Wywiał, Janusz L. Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47383-2.

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Paczkowski, Pawel. Proving total correctness of concurrent programs without using auxiliary variables. University of Edinburgh, Laboratory for Foundations of Computer Science, 1989.

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Bedier, Mostafa Abdellatif. Post stratified estimation using a known auxiliary variable. 1989.

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Wywiał, Janusz L. Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer Berlin / Heidelberg, 2021.

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Wywiał, Janusz L. L. Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer, 2015.

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Janusz L. Wywiał. Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer London, Limited, 2015.

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Części książek na temat "Auxiliary variable"

Pitt, Michael K., and Neil Shephard. "Auxiliary Variable Based Particle Filters." In Sequential Monte Carlo Methods in Practice. Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4757-3437-9_13.

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Wywiał, Janusz L. "Sampling Designs Dependent on a Continuous Auxiliary Variable." In Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63413-4_5.

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Ono, Nobutaka, and Shigeki Miyabe. "Auxiliary-Function-Based Independent Component Analysis for Super-Gaussian Sources." In Latent Variable Analysis and Signal Separation. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15995-4_21.

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D'Orazio, Marcello, Marco Di Zio, and Mauro Scanu. "Auxiliary variable selection in a statistical matching problem." In Analysis of Integrated Data. Chapman and Hall/CRC, 2019. http://dx.doi.org/10.1201/9781315120416-5.

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Wywiał, Janusz L. "Sampling Designs Based on Order Statistics of Auxiliary Variable." In Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-47383-2_3.

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Bocci, Chiara, and Emilia Rocco. "On the use of auxiliary information in spatial sampling." In Proceedings e report. Firenze University Press and Genova University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0106-3.27.

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Technology development has led to a growing availability of low-cost data ready-to-use, frequently derived from large scale observations (i.e. data from pervasive systems like GPS sensors, or remote sensing data from earth observation technologies). Oftentimes, these data can’t directly answer specific questions posed by researchers and data users, or even if they can they are subject to measurement errors or self-selection bias. In both cases it is still necessary to rely, at least partially, on ad-hoc probabilistic surveys. On the other hand, the precision and quality of surveys estimates can be improved by using the data derived from these new sources as auxiliary information in the design phase and/or in the estimation phase. We present a sequential sampling strategy, suitable to investigate a spatially-related phenomenon, which exploits the auxiliary information at design level in order to obtain efficient estimates when the relation between the auxiliary and study variables it is not completely known and/or is not univocally defined for the whole population under study. Using this strategy the final sample is obtained after two (or more) steps: (i) in the first step we collect an initial sample of observations on the target variable, which is used also to investigate the relation between the auxiliary and study variables; (ii) then, this relation is exploited to target and tailor the subsequent sampling step; (iii) additional steps can be included by applying the procedure iteratively. The performance of the suggested strategy is investigated through Monte Carlo experiments by considering several scenarios, which differ in the distributions of the auxiliary and study variables and in their relation.

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Wywiał, Janusz L. "Sampling Designs Based on Order Statistics of an Auxiliary Variable." In Sampling Designs Dependent on Sample Parameters of Auxiliary Variables. Springer Berlin Heidelberg, 2021. http://dx.doi.org/10.1007/978-3-662-63413-4_3.

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Monette, Jean-Noël, Pierre Flener, and Justin Pearson. "Automated Auxiliary Variable Elimination Through On-the-Fly Propagator Generation." In Lecture Notes in Computer Science. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23219-5_22.

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Yao, Wenjuan, Junyi Zhang, and Zhongxiang Zhou. "A Three-Stage Variational Image Segmentation via Scalar Auxiliary Variable Algorithm." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-77411-9_30.

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Lu, Bo, Yuzhen Chen, and Qingshan Zhang. "The Exact Solutions of Variable Coefficient Auxiliary High Order Generalized KdV Equation." In Advances in Computer Science, Environment, Ecoinformatics, and Education. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23324-1_80.

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Streszczenia konferencji na temat "Auxiliary variable"

Oladimeji, Olatunji Muhammad, Amos Adedayo Adewara, Femi Emmanuel Amoyedo, Ezekiel Olaoluwa Omole, Peter Onu, and Kehinde Peter Ajewole. "Improved Ratio Estimator under Stratified Simple Random Sampling Using Auxiliary Variable." In 2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG). IEEE, 2024. http://dx.doi.org/10.1109/seb4sdg60871.2024.10630033.

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Liu, Fei, Guanbin Gao, and Jing Na. "A Kinematic Parameter Identification Method Based on Auxiliary Variable for Industrial Robots." In 2024 3rd International Conference on Automation, Robotics and Computer Engineering (ICARCE). IEEE, 2024. https://doi.org/10.1109/icarce63054.2024.00019.

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Afolayan, Temitope, Amos Adedayo Adewara, Femi Emmanuel Amoyedo, Olaoluwa E. Omole, Peter Onu, and Kehinde Peter Ajewole. "An Enhanced Stratified Ratio and Product Estimators in Double Sampling Using Auxiliary Variable." In 2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG). IEEE, 2024. http://dx.doi.org/10.1109/seb4sdg60871.2024.10630417.

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Liu, Shuo, Wei Xiao, and Calin A. Belta. "Auxiliary-Variable Adaptive Control Lyapunov Barrier Functions for Spatio-Temporally Constrained Safety-Critical Applications." In 2024 IEEE 63rd Conference on Decision and Control (CDC). IEEE, 2024. https://doi.org/10.1109/cdc56724.2024.10886196.

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Duan, Zhongjian, and Xiangchun Yu. "Bias-variance knowledge distillation based on auxiliary classifier." In Ninth International Symposium on Advances in Electrical, Electronics, and Computer Engineering (ISAEECE 2024), edited by Pierluigi Siano and Wenbing Zhao. SPIE, 2024. http://dx.doi.org/10.1117/12.3033417.

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Kusum and Sangeeta Malik. "Modify unbiased estimator using auxiliary variable." In PROCEEDING OF INTERNATIONAL CONFERENCE ON FRONTIERS OF SCIENCE AND TECHNOLOGY 2021. AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0115269.

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Pickert, V. "DSP controlled auxiliary resonant commutated pole inverter without switch status sensors." In Seventh International Conference on Power Electronics and Variable Speed Drives. IEE, 1998. http://dx.doi.org/10.1049/cp:19980602.

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Marnissi, Yosra, Emilie Chouzenoux, Jean-Christophe Pesquei, and Amel Benazza-Benyahia. "An auxiliary variable method for Langevin based MCMC algorithms." In 2016 IEEE Statistical Signal Processing Workshop (SSP). IEEE, 2016. http://dx.doi.org/10.1109/ssp.2016.7551764.

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Ruan Xinbo. "Zero-voltage-switched, PWM, phase-shifted converter employing an auxiliary resonant net." In 6th International Conference on Power Electronics and Variable Speed Drives. IEE, 1996. http://dx.doi.org/10.1049/cp:19960970.

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He, XiaoQiong, Yang Chen, Chen Chen, ZhiQin Zhao, and PengCheng Han. "Resonance Parameter of Variable Mode LLC Converter for Auxiliary Converter." In 2019 10th International Conference on Power Electronics and ECCE Asia (ICPE 2019 - ECCE Asia). IEEE, 2019. http://dx.doi.org/10.23919/icpe2019-ecceasia42246.2019.8796931.

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Raporty organizacyjne na temat "Auxiliary variable"

Baader, Franz, and Anton Claußnitzer. Maximum Entropy Reasoning via Model Counting in (Description) Logics that Count Extended Version. Technische Universität Dresden, 2025. https://doi.org/10.25368/2025.015.

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In previous work it was shown that the logic ALC^ME , which extends the description logic (DL) ALC with probabilistic conditionals, has domain-lifted inference. Here, we extend this result from the base logic ALC to two logics that can count, the two-variable fragment C2 of first-order logic (FOL) with counting quantifiers, and the DL ALCSCC, which is not a fragment of FOL. As an auxiliary result, we prove that model counting in ALCSCC can be realized in a domain-liftable way.

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Jebrail, F. F., and R. S. Kistler. L51753 Natural Draft Aerial Coolers. Pipeline Research Council International, Inc. (PRCI), 1996. http://dx.doi.org/10.55274/r0010422.

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In recent years, environmental regulations have tightened and community involvement in environmental issues has increased. The pipeline industry has responded by attempting to reduce the negative economic and environmental impact of conventional air-cooled heat exchangers, which are characterized by high noise levels, excessive energy consumption, and high maintenance costs. While industry has had limited success in reducing air cooler noise using silencers and timed variable-speed fans, these solutions are costly. The most effective noise reduction method is to reduce or eliminate noise at its source. The primary goals of this investigation were to address key technical issues and to document natural draft aerial cooler (NDAC) design knowledge. The following objectives were identified: - Form a project team from PRCI-recommended aerial cooler manufacturers to design a quiet aerial cooler - Conduct technical and economic analyses to determine the actual operating needs and constraints of NDACs - Conduct market analyses to evaluate and identify the marketing issues associated with NDACs - Document the results of the project in a final report In recent years, the number of environmental permits mandating the use of natural draft aerial coolers to reduce noise has increased. Natural draft aerial cooler technology can potentially eliminate noise and improve operational energy efficiency. A broad group of applications could benefit from this technology, including natural gas, engine jacket water, auxiliary water, and engine lube oil cooling. With noise regulations and penalties becoming increasingly stringent, natural draft heat transfer technology is becoming more important. No organization has as yet fully investigated it. The technical and economic feasibility of NDACs were investigated for natural gas, engine jacket water, auxiliary water, and lube oil cooler applications.

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Ahmad, M., and R. S. Singh. Role of Auxiliary Variate and Additional Data in Density Estimation. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada160287.

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Baader, Franz, and Marcel Lippmann. Runtime Verification Using a Temporal Description Logic Revisited. Technische Universität Dresden, 2014. http://dx.doi.org/10.25368/2022.203.

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Formulae of linear temporal logic (LTL) can be used to specify (wanted or unwanted) properties of a dynamical system. In model checking, the system’s behaviour is described by a transition system, and one needs to check whether all possible traces of this transition system satisfy the formula. In runtime verification, one observes the actual system behaviour, which at any point in time yields a finite prefix of a trace. The task is then to check whether all continuations of this prefix to a trace satisfy (violate) the formula. More precisely, one wants to construct a monitor, i.e., a finite automaton that receives the finite prefix as input and then gives the right answer based on the state currently reached. In this paper, we extend the known approaches to LTL runtime verification in two directions. First, instead of propositional LTL we use the more expressive temporal logic ALC-LTL, which can use axioms of the Description Logic (DL) ALC instead of propositional variables to describe properties of single states of the system. Second, instead of assuming that the observed system behaviour provides us with complete information about the states of the system, we assume that states are described in an incomplete way by ALC-knowledge bases. We show that also in this setting monitors can effectively be constructed. The (double-exponential) size of the constructed monitors is in fact optimal, and not higher than in the propositional case. As an auxiliary result, we show how to construct Büchi automata for ALC-LTL-formulae, which yields alternative proofs for the known upper bounds of deciding satisfiability in ALC-LTL.

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García Zaballos, Antonio, Enrique Iglesias Rodriguez, and Pau Puig Gabarró. Informe anual del Indice de Desarrollo de la Banda Ancha: brecha digital en América Latina y el Caribe: IDBA 2021. Banco Interamericano de Desarrollo, 2022. http://dx.doi.org/10.18235/0004379.

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Este informe describe y presenta los resultados del Indice de Desarrollo de la Banda Ancha (IDBA) en América Latina y el Caribe (ALC). El principal objetivo del IDBA es medir la brecha digital en ALC mediante la evaluación del desarrollo de la banda ancha en los 26 países prestatarios del Banco Interamericano de Desarrollo (BID) y también en países adicionales de referencia de otras regiones (65 naciones en total). El BID tiene como misión ayudar al desarrollo de ALC y financiar los esfuerzos tendientes a reducir la pobreza y la desigualdad social en la región. El IDBA contribuirá a focalizar la financiación que el BID destina a proyectos que tienen entre sus objetivos el desarrollo de la banda ancha en una región o país. El IDBA es una potente herramienta que permite identificar la magnitud de la brecha digital mediante dos enfoques geográficos diferentes. En primer lugar, al comparar el estado de un país frente al clúster al que pertenece y, en segundo lugar, al compararlo con los países de la Organización para la Cooperación y el Desarrollo Económicos (OCDE). Además el IDBA presenta comparaciones anuales, ya que se actualiza cada año. Este año se han realizado cambios en la metodología de cálculo del Indice debido al concepto dinámico de la banda ancha, la cual avanza junto con los cambios económicos y demográficos y también por las nuevas necesidades y preferencias de los usuarios. Como consecuencia, se buscan indicadores más adecuados para medir el desarrollo de la banda ancha en ALC y las brechas y desafíos del sector en comparación con otras regiones más avanzadas. En la actualidad el Indice está formado por 44 variables: 30 forman parte directa del mismo y 14 se consideran variables auxiliares. Las 30 variables que componen el IDBA se distribuyen en cuatro pilares: Políticas públicas y visión estratégica, Regulación estratégica, Infraestructuras, y Aplicaciones y capacitación. Como resultado, el IDBA proporciona una herramienta actualizada para la toma de decisiones, el desarrollo de políticas públicas y la elaboración de planes de acción concretos para la mejora de cada país, gracias a la identificación de debilidades y fortalezas de cada uno.

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Duque Rodríguez, John Alexander, Gloria Patricia Castro Torres, and Lina Tatiana Ochoa Murillo. ¿La desarticulación entre el Plan Integral de Cambio Climático de Antioquia y los planes de desarrollo municipales afecta las inversiones de las administraciones municipales? Contraloría General de Antioquia, 2023. http://dx.doi.org/10.58373/obscga.010.

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El cambio climático –tema de gran relevancia a nivel mundial puesto que es una amenaza acelerada, existente y vigente para la humanidad, los recursos naturales y el ambiente– es considerado por muchos como uno de los mayores desafíos a nivel mundial. Lo anterior contribuido a que el gobierno de Colombia genere nuevas políticas territoriales, basadas en instrumentos de corto, mediano y largo plazo, en las cuales las administraciones municipales adoptan, revisan, actualizan e incorporan, en sus Planes de Desarrollo Municipal, acciones encaminadas a la mitigación de gases efecto invernadero y a la destinación de recursos financieros. Es por esto, que la Contraloría General de Antioquia, desde la Contraloría Auxiliar de los Recursos Naturales y del Ambiente, desarrolla el presente artículo con el fin de conocer si la desarticulación entre el Plan Integral de Cambio Climático de Antioquia y los Planes de Desarrollo Municipales afecta las inversiones de las administraciones municipales del departamento de Antioquia para la gestión de cambio climático. La metodología aplicada consideró un enfoque cualitativo, donde se analizaron las variables: instrumentos de planificación (Plan de Desarrollo Municipal y Plan Integral de Gestión de Cambio Climático de Antioquia) y las inversiones con recursos propios de las administraciones municipales en el componente de cambio climático en la vigencia 2021. Para lo cual, los resultados obtenidos evidenciaron que la desarticulación entre los planes mencionados, no afectaron las inversiones municipales ejecutadas. Así, con esta investigación se da apertura a posibles desarrollos de nuevos estudios o informes asociados, que permitan indagar o conocer factores que inciden en la eficiencia de las inversiones realizadas en cambio climático al no tener incorporado el Plan Integral de Gestión de Cambio Climático de Antioquia en los Planes de Desarrollo Municipal.

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