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About 10,000 papers for “Sequential sampling”

Sequential Sampling

John B. Heppner, David B. Richman, Steven E. Naranjo et al. · 2008

Cited by 0

Sequential Sampling

2004

This chapter includes the following topics: Gains from Sequential Sampling Sequential Decision Procedures The Risk of a Sequential Decision Procedure Backward Induction Optimal Bounded Sequential Decision Procedures Illustrative Examples Unbounded Sequential Decision Procedures Regular Sequential Decision Procedures Existence of an Optimal Procedure Approximating an Optimal Procedure by Bounded Procedures Regions for Continuing or Terminating Sampling The Functional Equation Approximations and Bounds for the Bayes Risk The Sequential Probability-Ratio Test Characteristics of Sequential Probability-Ratio Tests Approximating the Expected Number of Observations

Cited by 0

Sampling, Sequential

Jack G. Calvert · IUPAC Standards Online · 2016

Over 620 atmospheric chemistry terms which are in common use by the international research community in the atmospheric sciences are defined. The diversified nature of the scientists involved in research in atmospheric chemistry (chemists, meteorologists, physicists, biologists, engineers, and others) requires that special attention be paid to the consistency of the terminology employed. Where alternative terms are in common use to describe a given process, piece of equipment, feature, or quantity used in atmospheric chemistry, recommended choices of the IUPAC Commission on Atmospheric Chemistry are given; these are consistent with the other IUPAC publications and recommendations on nomenclature. The range of terms includes composition of the atmosphere, clouds, solar radiation, chemical and physical changes in atmospheric components, instrumentation employed in analysis of the atmospheric components and in air quality control, and in effects of certain trace gases on materials, plants, and animals.

Cited by 0

Sequential Sampling Paper

Darren Lytle · Environmental Protection Agency (EPA) Repository · 2019

This work discusses drinking water sampling efforts for lead in Flint, MI.

Cited by 0Open access

Normal sequential sampling

G. Barrie Wetherill, J. Köllerström · Communications in Statistics Part C Sequential Analysis · 1983

Bayesian sequential sampling plans are investigated numerically, for testing the mean of a normal distribution (‘high’ values are acceptable, but 'low' values are not). The variance is known, the prior of the mean is normal, and a linear loss function is used. Various properties of these plans are presented here and compared with results for single and double sampling plans. Robustness of these plans with respect to errors in some of the parameters are investigated as well as methods for reducing the computation for the sequential plans.

Cited by 2

Pedigrees, Sequential Sampling

Veronica J. Vieland · Encyclopedia of Biostatistics · 2005

Abstract Families are frequently selected for genetic epidemiologic study based upon (i) initial ascertainment of (affected) individuals, and (ii) subsequent intrafamilial sampling of (subsets of) relatives of those individuals. Such procedures must be taken into consideration when writing genetic likelihoods, estimating genetic parameters, or performing statistical tests based on ascertained pedigree data.

Cited by 0

Sequential random sampling

Joachim Ahrens, U. Dieter · ACM Transactions on Mathematical Software · 1985

Fast algorithms for selecting a random set of exactly k records from a file of n records are constructed. Selection is sequential: the sample records are chosen in the same order in which they occur in the file. All procedures run in O(k) time. The “geometric” method has two versions: with or without O(k) auxiliary space. A further procedure uses hashing techniques and requires O(k) space.

Cited by 29Open access

Pedigrees, Sequential Sampling

Veronica J. Vieland · Wiley StatsRef: Statistics Reference Online · 2014

Abstract Families are frequently selected for genetic epidemiologic study based upon (i) initial ascertainment of (affected) individuals, and (ii) subsequent intrafamilial sampling of (subsets of) relatives of those individuals. Such procedures must be taken into consideration when writing genetic likelihoods, estimating genetic parameters, or performing statistical tests based on ascertained pedigree data.

Cited by 0

Sequential Sampling Equilibrium

Duarte Gon\c{c}alves · RePEc: Research Papers in Economics

This paper introduces an equilibrium framework based on sequential sampling in which players face strategic uncertainty over their opponents' behavior and acquire informative signals to resolve it. Sequential sampling equilibrium delivers a disciplined model featuring an endogenous distribution of choices, beliefs, and decision times, that not only rationalizes well-known deviations from Nash equilibrium, but also makes novel predictions supported by existing data. It grounds a relationship between empirical learning and strategic sophistication, and generates stochastic choice through randomness inherent to sampling, without relying on indifference or choice mistakes. Further, it provides a rationale for Nash equilibrium when sampling costs vanish.

Cited by 0

Sequential batch sampling

Eitan Greenshtein · Sequential Analysis · 1991

Let {Xi} be i.i.d.{Fθ}.We consider the testing problem H1θ<θ0 vs H2θ≥θ0, where sampling is done sequentially in batches with variable batch sizes.For some parametric families {Fθ}, and under natural cost struc-ture, we characterize the Bayes procedures. This characterization of Bayes procedures lead to a similar characterization of essentially complete class of procedures.

Cited by 1

Padrecocha Sequential Sampling

Christian A Ganoza (20721), Michael A Matthias (20722), Devon Collins-Richards (20723) et al. · Figshare · 2015

&lt;p&gt;A total of 17 wells and six stream sampling points were tested over time. Filled boxes indicate PCR-positivity on that day (A). Bars indicate percentage of positivity of wells and stream sampled points for each tested day (B). The streams had a statistically significant higher frequency of positivity over time than the wells (χ&lt;sup&gt;2&lt;/sup&gt; = 133.74, &lt;i&gt;p&lt;/i&gt; &lt; 0.001). NS, not sampled.&lt;/p&gt;

Cited by 0Open access

Truncated sequential sampling plan

Waters Edward · Figshare · 2016

Contains code to implement truncated sequential sampling on data simulated from a PERT distribution. Truncated sampling, as described in the reference below, can be used to classify the prevalence of a disease as low, medium, or high according to pre-determined threshold criteria. It also has more general applications in quality assurance and decision support.

Cited by 1Open access

sps: Sequential Poisson Sampling

Martin, Steve · Zenodo (CERN European Organization for Nuclear Research) · 2025

Sequential Poisson sampling is a variation of Poisson sampling for drawing probability-proportional-to-size samples with a given number of units, and is commonly used for price-index surveys. This package gives functions to draw stratified sequential Poisson samples according to the method by Ohlsson (1998, ISSN:0282-423X), as well as other order sample designs by Rosén (1997, ), and generate approximate bootstrap replicate weights according to the generalized bootstrap method by Beaumont and Patak (2012, ).

Cited by 0Open access