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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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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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Comment

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

2015

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Rejoinder

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

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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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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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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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 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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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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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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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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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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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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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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Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring

Ecological applications, 2023-01, Vol.33 (1), p.e2745-n/a

2023

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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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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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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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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

Sampling in software engineering research: a critical review and guidelines

Comment

Rejoinder

Beyond Nyquist: Efficient Sampling of Sparse Bandlimited Signals

Diagnostics for respondent-driven sampling

Imposing Minimax and Quantite Constraints on Optimal Matching in Observational Studies

Scalable importance tempering and Bayesian variable selection

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

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

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

Sampling bias exaggerates a textbook example of a trophic cascade

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

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

Variance-based adaptive sequential sampling for Polynomial Chaos Expansion

Are we telling the same story? Comparing inferences made from camera trap and telemetry data for wildlife monitoring

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

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

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

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