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Empirical Processes in Survey Sampling with (Conditional) Poisson Designs

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Outgoing claims: the papers this work cites, builds on, or argues with.

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Sample distribution function based goodness-of-fit test for complex surveys
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Rate of convergence to normal distribution for the Horvitz-Thompson estimator
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Tail index estimation based on survey data
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On-line learning gossip algorithm in multi-agent systems with local decision rules
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Scaling up M-estimation via sampling designs: The Horvitz-Thompson stochastic gradient descent
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On the Convergence of the Horvitz‐Thompson Estimator
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A Z‐theorem with Estimated Nuisance Parameters and Correction Note for ‘Weighted Likelihood for Semiparametric Models and Two‐phase Stratified Samples, with Application to Cox Regression’
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Variance Estimation and Asymptotic Confidence Bands for the Mean Estimator of Sampled Functional Data with High Entropy Unequal Probability Sampling Designs
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Limit Theorems for Harris Markov Chains, I
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Struggles with Survey Weighting and Regression Modeling
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Approximation of rejective sampling inclusion probabilities and application to high order correlations
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Functional central limit theorems for single-stage sampling designs
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Asymptotic Theory of Rejective Sampling with Varying Probabilities from a Finite Population
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A Rank Statistics Approach to the Consistency of a General Bootstrap
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Uniform convergence of the empirical cumulative distribution function under informative selection from a finite population

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Functional Calibration Under Non-Probability Survey Sampling
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Méthodes de sondage pour les données massives
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