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Representative Samples, Random Sampling
Cambio, 2022 della redazione: In the social sciences literature the expressions ‘random sample’ and ‘representative sample’ are often used improperly and sometimes even interchangeably by students who seem to think that sample is representative in so far, and ...
Alberto Marradi
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Random fields and random sampling [PDF]
Kybernetika, 2020 The authors study the limit in distribution of the maximum of a stationary bivariate real random field, sampled at double random times under some dependence conditions. It is shown that the limit distribution is a max-semistable distribution when the random samples have a geometric growth pattern. When the random field is sampled at double random times,
Dias, Sandra, Temido, Maria da Graça
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Inclusive random sampling in graphs and networks
Applied Network Science, 2023 It is often of interest to sample vertices from a graph with a bias towards higher-degree vertices. One well-known method, which we call random neighbor or RN, involves taking a vertex at random and exchanging it for one of its neighbors.
Yitzchak Novick, Amotz Bar-Noy
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Field sampling methods for investigating forest-floor bryophytes: Microcoenose vs. random sampling [PDF]
Archives of Biological Sciences, 2018 Because of the high importance of bryophytes in forest ecosystems, it is necessary to develop standardized field sampling methodologies. The quadrat method is commonly used for bryophyte diversity and distribution pattern surveys.
Ilić Miloš +3 more
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Animals, 2021 Within paratuberculosis control programs Mycobacterium avium subsp. paratuberculosis (MAP)-infected herds have to be detected with minimum effort but with sufficient reliability.
Annika Wichert +4 more
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Biased Boltzmann samplers and generation of extended linear languages with shuffle [PDF]
Discrete Mathematics & Theoretical Computer Science, 2012 This paper is devoted to the construction of Boltzmann samplers according to various distributions, and uses stochastic bias on the parameter of a Boltzmann sampler, to produce a sampler with a different distribution for the size of the output.
Alexis Darrasse +3 more
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Statistical Analysis in the Presence of Spatial Autocorrelation: Selected Sampling Strategy Effects
Stats, 2022 Fundamental to most classical data collection sampling theory development is the random drawings assumption requiring that each targeted population member has a known sample selection (i.e., inclusion) probability.
Daniel A. Griffith, Richard E. Plant
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Sampling Random Colorings of Sparse Random Graphs [PDF]
, 2017 We study the mixing properties of the single-site Markov chain known as the Glauber dynamics for sampling $k$-colorings of a sparse random graph $G(n,d/n)$ for constant $d$.
Efthymiou, Charilaos +3 more
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Quantifying errors without random sampling
BMC Medical Research Methodology, 2003 Background All quantifications of mortality, morbidity, and other health measures involve numerous sources of error. The routine quantification of random sampling error makes it easy to forget that other sources of error can and should be quantified ...
LaPole Luwanna M, Phillips Carl V
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Parallel Weighted Random Sampling [PDF]
, 2019 Data structures for efficient sampling from a set of weighted items are an important building block of many applications. However, few parallel solutions are known. We close many of these gaps both for shared-memory and distributed-memory machines.
, Sanders, Peter
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