Relevant bibliographies by topics / Sampling with varying probabilities

Academic literature on the topic 'Sampling with varying probabilities'

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Published: 8 September 2023

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Journal articles on the topic "Sampling with varying probabilities"

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Goulionis, J. E. "Strategies for sampling with varying probabilities." Journal of Statistical Computation and Simulation 81, no. 11 (November 2011): 1753. http://dx.doi.org/10.1080/00949655.2011.622434.

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Chaudhuri, Arijit, and Arun Kumar Adhikary. "Circular Systematic Sampling with Varying Probabilities." Calcutta Statistical Association Bulletin 36, no. 3-4 (September 1987): 193–96. http://dx.doi.org/10.1177/0008068319870310.

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Certain conditions connecting the population size, sample size and the sampling interval in circular systematic sampling with equal probabilities are known. We present here a simple “condition” connecting the sample size, size-measures and the sampling interval in pps circular systematic sampling. The condition is important in noting limitations on sample-sizes when a sampling interval is pre-assigned.
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Kumar, Prenesh. "On sampling of three units using varying probabilities." Statistics 18, no. 3 (January 1987): 373–77. http://dx.doi.org/10.1080/02331888708802032.

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Blanchet, Jose, and Jingchen Liu. "Efficient importance sampling in ruin problems for multidimensional regularly varying random walks." Journal of Applied Probability 47, no. 2 (June 2010): 301–22. http://dx.doi.org/10.1239/jap/1276784893.

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We consider the problem of efficient estimation via simulation of first passage time probabilities for a multidimensional random walk with heavy-tailed increments. In addition to being a natural generalization to the problem of computing ruin probabilities in insurance - in which the focus is the maximum of a one-dimensional random walk with negative drift - this problem captures important features of large deviations for multidimensional heavy-tailed processes (such as the role played by the mean of the process in connection to the location of the target set). We develop a state-dependent importance sampling estimator for this class of multidimensional problems. Then, using techniques based on Lyapunov inequalities, we argue that our estimator is strongly efficient in the sense that the relative mean squared error of our estimator can be made arbitrarily small by increasing the number of replications, uniformly as the probability of interest approaches 0.
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Blanchet, Jose, and Jingchen Liu. "Efficient importance sampling in ruin problems for multidimensional regularly varying random walks." Journal of Applied Probability 47, no. 02 (June 2010): 301–22. http://dx.doi.org/10.1017/s0021900200006653.

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We consider the problem of efficient estimation via simulation of first passage time probabilities for a multidimensional random walk with heavy-tailed increments. In addition to being a natural generalization to the problem of computing ruin probabilities in insurance - in which the focus is the maximum of a one-dimensional random walk with negative drift - this problem captures important features of large deviations for multidimensional heavy-tailed processes (such as the role played by the mean of the process in connection to the location of the target set). We develop a state-dependent importance sampling estimator for this class of multidimensional problems. Then, using techniques based on Lyapunov inequalities, we argue that our estimator is strongly efficient in the sense that the relative mean squared error of our estimator can be made arbitrarily small by increasing the number of replications, uniformly as the probability of interest approaches 0.
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Haslett, Stephen. "Best linear unbiased estimation for varying probability with and without replacement sampling." Special Matrices 7, no. 1 (January 1, 2019): 78–91. http://dx.doi.org/10.1515/spma-2019-0007.

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Abstract When sample survey data with complex design (stratification, clustering, unequal selection or inclusion probabilities, and weighting) are used for linear models, estimation of model parameters and their covariance matrices becomes complicated. Standard fitting techniques for sample surveys either model conditional on survey design variables, or use only design weights based on inclusion probabilities essentially assuming zero error covariance between all pairs of population elements. Design properties that link two units are not used. However, if population error structure is correlated, an unbiased estimate of the linear model error covariance matrix for the sample is needed for efficient parameter estimation. By making simultaneous use of sampling structure and design-unbiased estimates of the population error covariance matrix, the paper develops best linear unbiased estimation (BLUE) type extensions to standard design-based and joint design and model based estimation methods for linear models. The analysis covers both with and without replacement sample designs. It recognises that estimation for with replacement designs requires generalized inverses when any unit is selected more than once. This and the use of Hadamard products to link sampling and population error covariance matrix properties are central topics of the paper. Model-based linear model parameter estimation is also discussed.
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Fatima, Khadija, Zahoor Ahmed, and Abeeda Fatima. "JACKKNIFE REPLICATION VARIANCE ESTIMATION OF POPULATION TOTAL UNDER SYSTEMATIC SAMPLING WITH VARYING PROBABILITIES." Matrix Science Mathematic 1, no. 1 (January 20, 2017): 34–39. http://dx.doi.org/10.26480/msmk.01.2017.34.39.

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Blanchet, Jose H., and Jingchen Liu. "State-dependent importance sampling for regularly varying random walks." Advances in Applied Probability 40, no. 4 (December 2008): 1104–28. http://dx.doi.org/10.1239/aap/1231340166.

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Consider a sequence (Xk:k≥ 0) of regularly varying independent and identically distributed random variables with mean 0 and finite variance. We develop efficient rare-event simulation methodology associated with large deviation probabilities for the random walk (Sn:n≥ 0). Our techniques are illustrated by examples, including large deviations for the empirical mean and path-dependent events. In particular, we describe two efficient state-dependent importance sampling algorithms for estimating the tail ofSnin a large deviation regime asn↗ ∞. The first algorithm takes advantage of large deviation approximations that are used to mimic the zero-variance change of measure. The second algorithm uses a parametric family of changes of measure based on mixtures. Lyapunov-type inequalities are used to appropriately select the mixture parameters in order to guarantee bounded relative error (or efficiency) of the estimator. The second example involves a path-dependent event related to a so-called knock-in financial option under heavy-tailed log returns. Again, the importance sampling algorithm is based on a parametric family of mixtures which is selected using Lyapunov bounds. In addition to the theoretical analysis of the algorithms, numerical experiments are provided in order to test their empirical performance.
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Blanchet, Jose H., and Jingchen Liu. "State-dependent importance sampling for regularly varying random walks." Advances in Applied Probability 40, no. 04 (December 2008): 1104–28. http://dx.doi.org/10.1017/s0001867800002986.

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Consider a sequence (X k : k ≥ 0) of regularly varying independent and identically distributed random variables with mean 0 and finite variance. We develop efficient rare-event simulation methodology associated with large deviation probabilities for the random walk (S n : n ≥ 0). Our techniques are illustrated by examples, including large deviations for the empirical mean and path-dependent events. In particular, we describe two efficient state-dependent importance sampling algorithms for estimating the tail of S n in a large deviation regime as n ↗ ∞. The first algorithm takes advantage of large deviation approximations that are used to mimic the zero-variance change of measure. The second algorithm uses a parametric family of changes of measure based on mixtures. Lyapunov-type inequalities are used to appropriately select the mixture parameters in order to guarantee bounded relative error (or efficiency) of the estimator. The second example involves a path-dependent event related to a so-called knock-in financial option under heavy-tailed log returns. Again, the importance sampling algorithm is based on a parametric family of mixtures which is selected using Lyapunov bounds. In addition to the theoretical analysis of the algorithms, numerical experiments are provided in order to test their empirical performance.
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Asmussen, Søren. "Importance Sampling for Failure Probabilities in Computing and Data Transmission." Journal of Applied Probability 46, no. 3 (September 2009): 768–90. http://dx.doi.org/10.1239/jap/1253279851.

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In this paper we study efficient simulation algorithms for estimating P(X›x), whereXis the total time of a job with ideal time T that needs to be restarted after a failure. The main tool is importance sampling, where a good importance distribution is identified via an asymptotic description of the conditional distribution ofTgivenX›x. IfT≡tis constant, the problem reduces to the efficient simulation of geometric sums, and a standard algorithm involving a Cramér-type root, γ(t), is available. However, we also discuss an algorithm that avoids finding the root. IfTis random, particular attention is given toThaving either a gamma-like tail or a regularly varying tail, and to failures at Poisson times. Different types of conditional limit occur, in particular exponentially tilted Gumbel distributions and Pareto distributions. The algorithms based upon importance distributions forTusing these asymptotic descriptions have bounded relative error asx→∞ when combined with the ideas used for a fixedt. Nevertheless, we give examples of algorithms carefully designed to enjoy bounded relative error that may provide little or no asymptotic improvement over crude Monte Carlo simulation when the computational effort is taken into account. To resolve this problem, an alternative algorithm using two-sided Lundberg bounds is suggested.
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Dissertations / Theses on the topic "Sampling with varying probabilities"

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Dimy, Anguima Ibondzi Herve. "Estimation of Limiting Conditional Probabilities for Regularly Varying Time Series." Thèse, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/30906.

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In this thesis we are concerned with estimation of clustering probabilities for univariate heavy tailed time series. We employ functional convergence of a bivariate tail empirical process to conclude asymptotic normality of an estimator of the clustering probabilities. Theoretical results are illustrated by simulation studies.
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Datta, Srabosti. "POWER REDUCTION BY DYNAMICALLY VARYING SAMPLING RATE." UKnowledge, 2006. http://uknowledge.uky.edu/gradschool_theses/275.

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In modern digital audio applications, a continuous audio signal stream is sampled at a fixed sampling rate, which is always greater than twice the highest frequency of the input signal, to prevent aliasing. A more energy efficient approach is to dynamically change the sampling rate based on the input signal. In the dynamic sampling rate technique, fewer samples are processed when there is little frequency content in the samples. The perceived quality of the signal is unchanged in this technique. Processing fewer samples involves less computation work; therefore processor speed and voltage can be reduced. This reduction in processor speed and voltage has been shown to reduce power consumption by up to 40% less than if the audio stream had been run at a fixed sampling rate.
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Liao, Yijie. "Testing of non-unity risk ratio under inverse sampling." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/707.

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Datta, Srabosti. "Power reduction by dynmically [sic] varying sampling rate." Lexington, Ky. : [University of Kentucky Libraries], 2006. http://lib.uky.edu/ETD/ukyelen2006t00492/thesis.pdf.

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Thesis (M.S.)--University of Kentucky, 2006.
Title from document title page (viewed on October 31, 2006). Document formatted into pages; contains: viii, 70 p. : ill. (some col.). Includes abstract and vita. Includes bibliographical references (p. 66-69).
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Gulez, Taner. "Weapon-target Allocation And Scheduling For Air Defense With Time Varying Hit Probabilities." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/12608471/index.pdf.

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In this thesis, mathematical modeling and heuristic approaches are developed for surface-to-air weapon-target allocation problem with time varying single shot hit probabilities (SSHP) against linearly approaching threats. First, a nonlinear mathematical model for the problem is formulated to maximize sum of the weighted survival probabilities of assets to be defended. Next, nonlinear objective function and constraints are linearized. Time varying SSHP values are approximated with appropriate closed forms and adapted to the linear model obtained. This model is tested on different scenarios and results are compared with those of the original nonlinear model. It is observed that the linear model is solved much faster than the nonlinear model and produces reasonably good solutions. It is inferred from the solutions of both models that engagements should be made as late as possible, when the threats are closer to the weapons, to have SSHP values higher. A construction heuristic is developed based on this scheme. An improvement heuristic that uses the solution of the construction heuristic is also proposed. Finally, all methods are tested on forty defense scenarios. Two fastest solution methods, the linear model and the construction heuristic, are compared on a large scenario and proposed as appropriate solution techniques for the weapon-target allocation problems.
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Myhrer, Øystein. "Joint Default Probabilities: A Model with Time-varying and Correlated Sharpe Ratios and Volatilities." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for samfunnsøkonomi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-17400.

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The probabilities of joint default among companies are one of the major concerns in credit risk management, mainly because it aects the distribution of loan portfolio losses and is therefore critical when allocating capital for solvency purposes. This paper proposes a multivariate model with time-varying and correlated Sharpe ratios and volatilities for the value of the rms, calibrated to t sample averages between and within the rating categories A and Ba. We found that, in the standard Merton framework, the model performs well with one average A-rated rm and one average Ba-rated rm and with two average Ba-rated rms when the joint default probabilities are compared with similar empirical probabilities.
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Schelin, Lina. "Spatial sampling and prediction." Doctoral thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-53286.

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This thesis discusses two aspects of spatial statistics: sampling and prediction. In spatial statistics, we observe some phenomena in space. Space is typically of two or three dimensions, but can be of higher dimension. Questions in mind could be; What is the total amount of gold in a gold-mine? How much precipitation could we expect in a specific unobserved location? What is the total tree volume in a forest area? In spatial sampling the aim is to estimate global quantities, such as population totals, based on samples of locations (papers III and IV). In spatial prediction the aim is to estimate local quantities, such as the value at a single unobserved location, with a measure of uncertainty (papers I, II and V). In papers III and IV, we propose sampling designs for selecting representative probability samples in presence of auxiliary variables. If the phenomena under study have clear trends in the auxiliary space, estimation of population quantities can be improved by using representative samples. Such samples also enable estimation of population quantities in subspaces and are especially needed for multi-purpose surveys, when several target variables are of interest. In papers I and II, the objective is to construct valid prediction intervals for the value at a new location, given observed data. Prediction intervals typically rely on the kriging predictor having a Gaussian distribution. In paper I, we show that the distribution of the kriging predictor can be far from Gaussian, even asymptotically. This motivated us to propose a semiparametric method that does not require distributional assumptions. Prediction intervals are constructed from the plug-in ordinary kriging predictor. In paper V, we consider prediction in the presence of left-censoring, where observations falling below a minimum detection limit are not fully recorded. We review existing methods and propose a semi-naive method. The semi-naive method is compared to one model-based method and two naive methods, all based on variants of the kriging predictor.
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李泉志 and Chuen-chi Lee. "The control of a varying gain process using a varying sampling-rate PID controller with application to pH control." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1993. http://hub.hku.hk/bib/B31211598.

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Lee, Chuen-chi. "The control of a varying gain process using a varying sampling-rate PID controller with application to pH control /." [Hong Kong] : University of Hong Kong, 1993. http://sunzi.lib.hku.hk/hkuto/record.jsp?B1366573X.

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Peng, Linghua. "Normalizing constant estimation for discrete distribution simulation /." Digital version accessible at:, 1998. http://wwwlib.umi.com/cr/utexas/main.

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Books on the topic "Sampling with varying probabilities"

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Diebold, Francis X. Regime switching with time-varying transition probabilities. Philadelphia: Federal Reserve Bank of Philadelphia, Economic Research Division, 1993.

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Gurao, Dr Rajendra G. Sampling Methods. Kanpur, India: Chandralok Prakashan, 2015.

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1931-, MacNeill Ian B., and Umphrey Gary J. 1953-, eds. Applied probability, stochastic processes, and sampling theory. Dordrecht: D. Reidel, 1987.

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Wright, Tommy. Exact confidence bounds when sampling from small finite universes: An easy reference based on the hypergeometric distribution. Berlin: Springer-Verlag, 1991.

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Introduction to empirical processes and semiparametric inference. New York: Springer, 2008.

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Gupta, A. K. Theory of sample surveys. New Jersey: World Scientific, 2011.

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G, Meeden, ed. Bayesian methods for finite population sampling. London: Chapman & Hall, 1997.

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Resampling: The new statistics. 2nd ed. Arlington, VA: Resampling Stats, 1999.

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R.C. Bose Symposium (1988 New Delhi). Probability, statistics and design of experiments. New Delhi: Wiley Eastern, 1990.

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Evans, Michael J. Monte Carlo computation of marginal posterior qualities. Toronto: University of Toronto, Dept. of Statistics, 1988.

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Book chapters on the topic "Sampling with varying probabilities"

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Singh, Ravindra, and Naurang Singh Mangat. "Sampling With Varying Probabilities." In Kluwer Texts in the Mathematical Sciences, 67–101. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-017-1404-4_4.

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Chaudhuri, Arijit, and Sanghamitra Pal. "Sampling with Varying Probabilities." In Indian Statistical Institute Series, 43–109. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1418-8_3.

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Chorin, Alexandre J., and Ole H. Hald. "Time-Varying Probabilities." In Texts in Applied Mathematics, 89–107. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6980-3_5.

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Lohr, Sharon L. "Sampling with Unequal Probabilities." In Sampling, 219–72. 3rd ed. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429298899-6.

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Lohr, Sharon L. "Cluster Sampling with Equal Probabilities." In Sampling, 167–218. 3rd ed. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9780429298899-5.

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Lohr, Sharon L. "Sampling with Unequal Probabilities." In SAS® Software Companion for Sampling, 69–82. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003160366-6.

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Lu, Yan, and Sharon L. Lohr. "Sampling with Unequal Probabilities." In R Companion for Sampling, 69–84. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003228196-6.

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Lu, Yan, and Sharon L. Lohr. "Cluster Sampling with Equal Probabilities." In R Companion for Sampling, 57–68. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003228196-5.

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Lohr, Sharon L. "Cluster Sampling with Equal Probabilities." In SAS® Software Companion for Sampling, 55–68. Boca Raton: Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003160366-5.

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Hartung, Lisa, Nina Holden, and Yuval Peres. "Trace reconstruction with varying deletion probabilities." In 2018 Proceedings of the Fifteenth Workshop on Analytic Algorithmics and Combinatorics (ANALCO), 54–61. Philadelphia, PA: Society for Industrial and Applied Mathematics, 2018. http://dx.doi.org/10.1137/1.9781611975062.6.

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Conference papers on the topic "Sampling with varying probabilities"

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Frey, Kristoffer, Ted Steiner, and Jonathan How. "Collision Probabilities for Continuous-Time Systems Without Sampling." In Robotics: Science and Systems 2020. Robotics: Science and Systems Foundation, 2020. http://dx.doi.org/10.15607/rss.2020.xvi.019.

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Kath, W., and G. Biondini. "Calculating PMD statistics and outage probabilities with importance sampling." In OFC 2003 - Optical Fiber Communication Conference and Exhibition. IEEE, 2003. http://dx.doi.org/10.1109/ofc.2003.315983.

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de Angelis, M., E. Patelli, and M. Beer. "Line Sampling for Assessing Structural Reliability with Imprecise Failure Probabilities." In Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA). Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413609.093.

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Agaskar, Ameya, Chuang Wang, and Yue M. Lu. "Randomized Kaczmarz algorithms: Exact MSE analysis and optimal sampling probabilities." In 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP). IEEE, 2014. http://dx.doi.org/10.1109/globalsip.2014.7032145.

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Dieter, W. R., S. Datta, and Wong Key Kai. "Power reduction by varying sampling rate." In ISLPED '05. Proceedings of the 2005 International Symposium on Low Power Electronics and Design. IEEE, 2005. http://dx.doi.org/10.1109/lpe.2005.195519.

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Jin, Fang, and Huan-Jun Zhang. "Control under Time-Varying Sampling Period." In 2010 International Conference on E-Product E-Service and E-Entertainment (ICEEE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iceee.2010.5661238.

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Dieter, William R., Srabosti Datta, and Wong Key Kai. "Power reduction by varying sampling rate." In the 2005 international symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1077603.1077658.

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Yang, Pengyi, Wei Liu, and Jean Yang. "Positive unlabeled learning via wrapper-based adaptive sampling." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/457.

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Learning from positive and unlabeled data frequently occurs in applications where only a subset of positive instances is available while the rest of the data are unlabeled. In such scenarios, often the goal is to create a discriminant model that can accurately classify both positive and negative data by modelling from labeled and unlabeled instances. In this study, we propose an adaptive sampling (AdaSampling) approach that utilises prediction probabilities from a model to iteratively update the training data. Starting with equal prior probabilities for all unlabeled data, our method "wraps" around a predictive model to iteratively update these probabilities to distinguish positive and negative instances in unlabeled data. Subsequently, one or more robust negative set(s) can be drawn from unlabeled data, according to the likelihood of each instance being negative, to train a single classification model or ensemble of models.
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Sato, M., and H. Takeda. "Learning control of finite Markov chains with periodically varying transition probabilities." In 29th IEEE Conference on Decision and Control. IEEE, 1990. http://dx.doi.org/10.1109/cdc.1990.203852.

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Doctor, Katarina Z., and Jeff M. Byers. "Optimal Sampling of BRDF's of Varying Complexity." In IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2018. http://dx.doi.org/10.1109/igarss.2018.8518762.

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Reports on the topic "Sampling with varying probabilities"

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Iyengar, Satish. Importance Sampling for Tail Probabilities. Fort Belvoir, VA: Defense Technical Information Center, February 1991. http://dx.doi.org/10.21236/ada232412.

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Chernoff, Herman, and Yingnian Wu. Bounds on Inconsistent Inferences for Sequences of Trials with Varying Probabilities. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada267146.

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Hsing, Tailen. Extreme Value Theory for Suprema of Random Variables with Regularly Varying Tail Probabilities. Fort Belvoir, VA: Defense Technical Information Center, July 1986. http://dx.doi.org/10.21236/ada179126.

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Peterson, James T. On the Estimation of Detection Probabilities for Sampling Stream-Dwelling Fishes. Office of Scientific and Technical Information (OSTI), November 1999. http://dx.doi.org/10.2172/783958.

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Ghanghas, Ankit, Sayan Dey, and Venkatesh Merwade. Development of a Multiple Water Course Joint Probability Analysis Procedure for Indiana Watersheds. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317616.

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The design of hydraulic structures located near a confluence of two streams must take into consideration the flows from both of the streams. A hydraulic structure located on a small tributary that drains into a large river immediately downstream is not just affected by the flow in the tributary, but also by the backwater flow from the downstream river. Currently INDOT uses a tabular summary (Table 1.1 and Table 7.3 in the HEC-22 manual) of joint probabilities of coincident flows in designing hydraulic structures at confluences. However, the source of the table is unknown, and the tabular summary provides coincidental flows for only 1% and 10% probabilities, and thus it cannot be used directly for other probabilities. This study analyzed the interdependence of flows in mainstream and tributary and then developed a Gumbel-Hougard Copula-based procedure for estimating joint probabilities for confluences in Indiana. The study found that the mainstream and tributary streamflow are significantly correlated with Kendall’s Tau varying generally ranging from 0.5 to 0.8. Furthermore, the Kendall’s Tau, which is the key parameter for Gumbel-Hougard Copula, was found to be significantly related to drainage area ratio (DAR). Regression-based equations between DAR and τ are used as a basis to relate DAR to joint probabilities at confluences. The study also found that the currently used tabular summary (Table 1.1 and Table 7.3 in HEC-22 manual) resulted in significantly conservative design estimates and therefore overdesigned structures.
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George and Hawley. PR-015-12600-R01 Ability of Ultrasonic Meters to Measure Accurately in Compressor-Induced Pulsating Flows. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), November 2013. http://dx.doi.org/10.55274/r0010808.

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Transmission and storage operations frequently move natural gas using reciprocating compressors that may generate flow pulsations. Most measurement systems cannot accurately measure the flow rate of a pulsating gas stream, and the resulting errors can cause inaccurate gas volumes and accounting imbalances. Recent advances in ultrasonic meters may provide the ability to function without measurement error in pulsating gas streams. Tests were performed to examine the relationship between ultrasonic meter transducer sampling rates, the frequency and amplitude of pulsations from reciprocating compressors, and meter accuracy as a possible basis for using ultrasonic meters in gas pipelines with varying pulsations. Two ultrasonic natural gas meters of current design were tested at SwRI in flows that simulated reciprocating compressor pulsations. Diagnostics and flow data were collected from the meters and analyzed to identify pulsation conditions in which the meters read accurately, or in which meter data could be used to correct measurement errors.
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7

George, Darin, and Christopher Grant. PR-015-15601-R01 Pulsation Effects on Ultrasonic Meters Phase II. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), April 2016. http://dx.doi.org/10.55274/r0010905.

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Transmission and storage operations frequently move natural gas using reciprocating compressors that may generate flow pulsations. Most measurement systems cannot accurately measure the flow rate of a pulsating gas stream, and the resulting errors can cause inaccurate gas volumes and accounting imbalances. A previous PRCI research project tested whether recent advances in ultrasonic meters may allow them to function without measurement error in pulsating flows. This project expanded on the previous work and tested similar ultrasonic meters to look for relationships between ultrasonic meter transducer sampling rates, the frequency and amplitudes of pulsations from reciprocating compressors, and meter accuracy. Diagnostics and flow data were collected from the meters and analyzed, and a useful relationship was found between the pulsation conditions and the meter measurement error. The findings were used to recommend a basis for installing ultrasonic meters in gas pipelines with varying pulsations. Additional testing evaluated a fast-response differential pressure transducer connected across a plate flow conditioner as a potential pulsation diagnostic tool.
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Harter, Rachel, Joseph McMichael, and S. Grace Deng. New Approach for Handling Drop Point Addresses in Mail/ Web Surveys. RTI Press, August 2022. http://dx.doi.org/10.3768/rtipress.2022.op.0074.2209.

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The purpose of this paper is to introduce the concept of drop unit substitution in address-based samples for mail and web surveys. A drop point is a single US Postal Service (USPS) delivery point or receptacle that services multiple businesses, families, or households (USPS, 2017). Residential drop units are the individual housing units served by the drop point address. For the most part, address-based sampling frames list the number of units at a drop point address but will not contain information identifying specific units. Drop units comprise less than 2 percent of all residential addresses in the United States (McMichael, 2017), but they tend to be concentrated in certain large cities. In Queens, New York, for example, drop units constitute 27 percent of residential housing units. The problem with drop units for address-based surveys with mail contacts is that, without names or unit identifiers, there is no way to control which unit receives the various mailings. This limitation leads to distorted selection probabilities, renders the use of cash incentives by mail impractical, and precludes traditional methods for mail nonresponse follow-up, thus resulting in higher nonresponse. Alternatively, excluding drop units results in coverage error, which can be considerable for some subnational estimates. The authors propose a substitution approach when a drop unit is sampled—in other words, replacing the unit with a similar nearby unit in a non–drop point building.
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Russo, David, Daniel M. Tartakovsky, and Shlomo P. Neuman. Development of Predictive Tools for Contaminant Transport through Variably-Saturated Heterogeneous Composite Porous Formations. United States Department of Agriculture, December 2012. http://dx.doi.org/10.32747/2012.7592658.bard.

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The vadose (unsaturated) zone forms a major hydrologic link between the ground surface and underlying aquifers. To understand properly its role in protecting groundwater from near surface sources of contamination, one must be able to analyze quantitatively water flow and contaminant transport in variably saturated subsurface environments that are highly heterogeneous, often consisting of multiple geologic units and/or high and/or low permeability inclusions. The specific objectives of this research were: (i) to develop efficient and accurate tools for probabilistic delineation of dominant geologic features comprising the vadose zone; (ii) to develop a complementary set of data analysis tools for discerning the fractal properties of hydraulic and transport parameters of highly heterogeneous vadose zone; (iii) to develop and test the associated computational methods for probabilistic analysis of flow and transport in highly heterogeneous subsurface environments; and (iv) to apply the computational framework to design an “optimal” observation network for monitoring and forecasting the fate and migration of contaminant plumes originating from agricultural activities. During the course of the project, we modified the third objective to include additional computational method, based on the notion that the heterogeneous formation can be considered as a mixture of populations of differing spatial structures. Regarding uncertainly analysis, going beyond approaches based on mean and variance of system states, we succeeded to develop probability density function (PDF) solutions enabling one to evaluate probabilities of rare events, required for probabilistic risk assessment. In addition, we developed reduced complexity models for the probabilistic forecasting of infiltration rates in heterogeneous soils during surface runoff and/or flooding events Regarding flow and transport in variably saturated, spatially heterogeneous formations associated with fine- and coarse-textured embedded soils (FTES- and CTES-formations, respectively).We succeeded to develop first-order and numerical frameworks for flow and transport in three-dimensional (3-D), variably saturated, bimodal, heterogeneous formations, with single and dual porosity, respectively. Regarding the sampling problem defined as, how many sampling points are needed, and where to locate them spatially in the horizontal x₂x₃ plane of the field. Based on our computational framework, we succeeded to develop and demonstrate a methdology that might improve considerably our ability to describe quntitaively the response of complicated 3-D flow systems. The results of the project are of theoretical and practical importance; they provided a rigorous framework to modeling water flow and solute transport in a realistic, highly heterogeneous, composite flow system with uncertain properties under-specified by data. Specifically, they: (i) enhanced fundamental understanding of the basic mechanisms of field-scale flow and transport in near-surface geological formations under realistic flow scenarios, (ii) provided a means to assess the ability of existing flow and transport models to handle realistic flow conditions, and (iii) provided a means to assess quantitatively the threats posed to groundwater by contamination from agricultural sources.
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Wozniakowska, P., D. W. Eaton, C. Deblonde, A. Mort, and O. H. Ardakani. Identification of regional structural corridors in the Montney play using trend surface analysis combined with geophysical imaging, British Columbia and Alberta. Natural Resources Canada/CMSS/Information Management, 2021. http://dx.doi.org/10.4095/328850.

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The Western Canada Sedimentary Basin (WCSB) is a mature oil and gas basin with an extraordinary endowment of publicly accessible data. It contains structural elements of varying age, expressed as folding, faulting, and fracturing, which provide a record of tectonic activity during basin evolution. Knowledge of the structural architecture of the basin is crucial to understand its tectonic evolution; it also provides essential input for a range of geoscientific studies, including hydrogeology, geomechanics, and seismic risk analysis. This study focuses on an area defined by the subsurface extent of the Triassic Montney Formation, a region of the WCSB straddling the border between Alberta and British Columbia, and covering an area of approximately 130,000 km2. In terms of regional structural elements, this area is roughly bisected by the east-west trending Dawson Creek Graben Complex (DCGC), which initially formed in the Late Carboniferous, and is bordered to the southwest by the Late Cretaceous - Paleocene Rocky Mountain thrust and fold belt (TFB). The structural geology of this region has been extensively studied, but structural elements compiled from previous studies exhibit inconsistencies arising from distinct subregions of investigation in previous studies, differences in the interpreted locations of faults, and inconsistent terminology. Moreover, in cases where faults are mapped based on unpublished proprietary data, many existing interpretations suffer from a lack of reproducibility. In this study, publicly accessible data - formation tops derived from well logs, LITHOPROBE seismic profiles and regional potential-field grids, are used to delineate regional structural elements. Where seismic profiles cross key structural features, these features are generally expressed as multi-stranded or en echelon faults and structurally-linked folds, rather than discrete faults. Furthermore, even in areas of relatively tight well control, individual fault structures cannot be discerned in a robust manner, because the spatial sampling is insufficient to resolve fault strands. We have therefore adopted a structural-corridor approach, where structural corridors are defined as laterally continuous trends, identified using geological trend surface analysis supported by geophysical data, that contain co-genetic faults and folds. Such structural trends have been documented in laboratory models of basement-involved faults and some types of structural corridors have been described as flower structures. The distinction between discrete faults and structural corridors is particularly important for induced seismicity risk analysis, as the hazard posed by a single large structure differs from the hazard presented by a corridor of smaller pre-existing faults. We have implemented a workflow that uses trend surface analysis based on formation tops, with extensive quality control, combined with validation using available geophysical data. Seven formations are considered, from the Late Cretaceous Basal Fish Scale Zone (BFSZ) to the Wabamun Group. This approach helped to resolve the problem of limited spatial extent of available seismic data and provided a broader spatial coverage, enabling the investigation of structural trends throughout the entirety of the Montney play. In total, we identified 34 major structural corridors and number of smaller-scale structures, for which a GIS shapefile is included as a digital supplement to facilitate use of these features in other studies. Our study also outlines two buried regional foreland lobes of the Rocky Mountain TFB, both north and south of the DCGC.
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