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Comment: Snowball versus Respondent-Driven Sampling

Sociological methodology, 2011-08, Vol.41 (1), p.355-366

Heckathorn, Douglas D.

2011

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Advanced Sampling Methods

1st ed. 2021., 2021

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A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Computer methods in applied mechanics and engineering, 2023-01, Vol.403 (PA), p.115671, Article 115671

2023

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Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation

Journal of the American Statistical Association, 2011-03, Vol.106 (493), p.135-146

Gile, Krista J.

2011

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Sampling in Interview-Based Qualitative Research: A Theoretical and Practical Guide

Qualitative research in psychology, 2014-01, Vol.11 (1), p.25-41

Robinson, Oliver C.

2014

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Rejoinder

Journal of the American Statistical Association, 2015-12, Vol.110 (512), p.1459-1459

2015

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Comment

Journal of the American Statistical Association, 2015-12, Vol.110 (512), p.1439-1439

2015

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Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

IEEE transactions on information theory, 2010-01, Vol.56 (1), p.520-544

2010

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Imposing Minimax and Quantite Constraints on Optimal Matching in Observational Studies

Journal of computational and graphical statistics, 2017-03, Vol.26 (1), p.66-78

Rosenbaum, Paul R.

2017

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Diagnostics for respondent-driven sampling

Journal of the Royal Statistical Society. Series A, Statistics in society, 2015-01, Vol.178 (1), p.241-269

2015

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A soil sampling design for arable land quality observation by using SPCOSA–CLHS hybrid approach

Land degradation & development, 2021-11, Vol.32 (17), p.4889-4906

2021

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Scalable importance tempering and Bayesian variable selection

Journal of the Royal Statistical Society. Series B, Statistical methodology, 2019-07, Vol.81 (3), p.489-517

2019

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A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis

Reliability engineering & system safety, 2018-01, Vol.169, p.330-338

2018

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Sampling in software engineering research: a critical review and guidelines

Empirical software engineering : an international journal, 2022-07, Vol.27 (4), Article 94

2022

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From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

IEEE journal of selected topics in signal processing, 2010-04, Vol.4 (2), p.375-391

2010

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Comparison of sampling designs for calibrating digital soil maps at multiple depths

Pedosphere, 2022-08, Vol.32 (4), p.588-601

2022

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Sampling bias exaggerates a textbook example of a trophic cascade

Ecology letters, 2022-01, Vol.25 (1), p.177-188

2022

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Network Sampling: From Snowball and Multiplicity to Respondent-Driven Sampling

Annual review of sociology, 2017-07, Vol.43 (1), p.101-119

2017

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Band Sampling for Hyperspectral Imagery

IEEE transactions on geoscience and remote sensing, 2022, Vol.60, p.1-24

Chang, Chein-I

2022

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Reliability analysis with stratified importance sampling based on adaptive Kriging

Reliability engineering & system safety, 2020-05, Vol.197, p.106852-12, Article 106852

2020

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Theory of sampling (TOS) versus measurement uncertainty (MU) – A call for integration

TrAC, Trends in analytical chemistry (Regular ed.), 2014-05, Vol.57, p.93-106

2014

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Monte Carlo Search: First Workshop, MCS 2020, Held in Conjunction with IJCAI 2020, Virtual Event, January 7, 2021, Proceedings

1st Edition 2021, 2021

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AKOIS: An adaptive Kriging oriented importance sampling method for structural system reliability analysis

Structural safety, 2020-01, Vol.82, p.101876, Article 101876

2020

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Variance-based adaptive sequential sampling for Polynomial Chaos Expansion

Computer methods in applied mechanics and engineering, 2021-12, Vol.386, p.114105, Article 114105

2021

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Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models

Environmental modelling & software : with environment data news, 2017-07, Vol.93, p.109-126

2017

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Comment: Snowball versus Respondent-Driven Sampling

Advanced Sampling Methods

A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks

Improved Inference for Respondent-Driven Sampling Data With Application to HIV Prevalence Estimation

Sampling in Interview-Based Qualitative Research: A Theoretical and Practical Guide

Rejoinder

Comment

Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

Imposing Minimax and Quantite Constraints on Optimal Matching in Observational Studies

Diagnostics for respondent-driven sampling

A soil sampling design for arable land quality observation by using SPCOSA–CLHS hybrid approach

Scalable importance tempering and Bayesian variable selection

A new adaptive sequential sampling method to construct surrogate models for efficient reliability analysis

Sampling in software engineering research: a critical review and guidelines

From Theory to Practice: Sub-Nyquist Sampling of Sparse Wideband Analog Signals

Comparison of sampling designs for calibrating digital soil maps at multiple depths

Sampling bias exaggerates a textbook example of a trophic cascade

Network Sampling: From Snowball and Multiplicity to Respondent-Driven Sampling

Band Sampling for Hyperspectral Imagery

Reliability analysis with stratified importance sampling based on adaptive Kriging

Theory of sampling (TOS) versus measurement uncertainty (MU) – A call for integration

Monte Carlo Search: First Workshop, MCS 2020, Held in Conjunction with IJCAI 2020, Virtual Event, January 7, 2021, Proceedings

AKOIS: An adaptive Kriging oriented importance sampling method for structural system reliability analysis

Variance-based adaptive sequential sampling for Polynomial Chaos Expansion

Progressive Latin Hypercube Sampling: An efficient approach for robust sampling-based analysis of environmental models

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