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This chapter concludes with discussion of linear and non-linear optimization methods in application to the performance characteristics of materials and processes.
The methods in application to Plasmodium spp. are described, for example, in [ 19, 21– 23].
A large gap is apparent between statistical methods research related to missing data and use of these methods in application settings, including RCTs in top medical journals.
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The finite element approach offers certain advantages over alternative methods in applications to problems in plasma physics.
Laser machining competes with conventional machining methods in applications involving rapid processing with simple fixturing and flexible geometries.
Different MCMC methods in applications have been proposed by selecting different transition kernels, and two main types of commonly used in MCMC methods are Gibbs sampler [18] and Metropolis–Hastings algorithm [19].
As the limitation seemed not to prohibit the success of these methods in applications, it is unlikely that it will significantly confine the application of our framework.
There appears to be a large gap in translation between statistical methods research and the use of these methods in applications, such as RCTs.
This includes our recently described phase scatter correction (PSC) normalization method, which has been shown to outperform previous methods in applications requiring PCA or PLS decomposition of NMR spectral data.
We illustrate the method in application to a spike-processing problem.
The paper presents the comparison of these two method in application OMA for engineering structures.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com