Results 21 to 30 of about 11,879,570 (313)

Combination of Sequential Sampling Technique with GLR Control Charts for Monitoring Linear Profiles Based on the Random Explanatory Variables

open access: yesMathematics, 2023
Control charts play a beneficial role in the manufacturing process by reduction of non-compatible products and improving the final quality. In line with these aims, several adaptive methods in which samples can be taken with variable sampling rates and ...
Ali Yeganeh   +4 more
doaj   +1 more source

Sequential Sampling in Biological Assay [PDF]

open access: yesNature, 1953
IN an investigation relating to the isolation and purification of chorionic gonadotrophin from pregnancy urine, the following problem has arisen : “Does fraction A contain at least the amount X of chorionic gonadotrophin?” It was necessary to answer this question in the shortest possible time and to use as little material of A as possible.
E, BUKOVICS, F X, WOHLZOGEN
openaire   +2 more sources

Sequential spatially balanced sampling

open access: yesEnvironmetrics, 2022
AbstractSequential sampling occurs when an entire population is unknown in advance and data are received one by one or in groups of units. This article proposes a new algorithm to sequentially select a balanced sample. The algorithm respects equal and unequal inclusion probabilities.
Raphaël Jauslin   +2 more
openaire   +3 more sources

Resampling: an improvement of Importance Sampling in varying population size models [PDF]

open access: yes, 2016
Sequential importance sampling algorithms have been defined to estimate likelihoods in models of ancestral population processes. However, these algorithms are based on features of the models with constant population size, and become inefficient when the ...
Leblois, Raphaël   +3 more
core   +4 more sources

Sequential Sampling Models in Cognitive Neuroscience: Advantages, Applications, and Extensions. [PDF]

open access: yesAnnu Rev Psychol, 2016
Sequential sampling models assume that people make speeded decisions by gradually accumulating noisy information until a threshold of evidence is reached.
Forstmann BU   +2 more
europepmc   +2 more sources

On Inadequacy of Sequential Design of Experiments for Performance-Driven Surrogate Modeling of Antenna Input Characteristics

open access: yesIEEE Access, 2020
Design of contemporary antennas necessarily involves electromagnetic (EM) simulation tools. Their employment is imperative to ensure evaluation reliability but also to carry out the design process itself, especially, the adjustment of antenna dimensions.
Anna Pietrenko-Dabrowska   +1 more
doaj   +1 more source

Cognitive Control of Working Memory: A Model-Based Approach

open access: yesBrain Sciences, 2021
Working memory (WM)-based decision making depends on a number of cognitive control processes that control the flow of information into and out of WM and ensure that only relevant information is held active in WM’s limited-capacity store.
Russell J. Boag   +5 more
doaj   +1 more source

Probability distribution, sampling unit, data transformations and sequential sampling of European vine moth, Lobesia botrana (Lepidoptera: Tortricidae) larval counts from Northern Greece vineyards

open access: yesEuropean Journal of Entomology, 2007
Studies were conducted to investigate the distribution of larvae of the European vine moth, Lobesia botrana (Denis & Schiffermüller) (Lepidoptera: Tortricidae), a key vineyard pest of grape cultivars.
Antonis A. IFOULIS   +1 more
doaj   +1 more source

Sequential Changes in Antioxidant Potential of Oakleaf Lettuce Seedlings Caused by Nano-TiO2 Treatment

open access: yesNanomaterials, 2021
Nowadays, there is an increasing interest in nanoparticle (NP) technology used in household and industrial products. It could cause an accumulation and dispersion of NPs in the environment, with possible harmful effects on living organisms. Nanoparticles
Rita Jurkow   +4 more
doaj   +1 more source

Generalised linear mixed model analysis via sequential Monte Carlo sampling [PDF]

open access: yes, 2008
We present a sequential Monte Carlo sampler algorithm for the Bayesian analysis of generalised linear mixed models (GLMMs). These models support a variety of interesting regression-type analyses, but performing inference is often extremely difficult ...
D S. Leslie   +5 more
core   +6 more sources

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