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Study objective: The purpose of this paper is to give an overview and comparison of different easily applicable statistical techniques to analyse recurrent event data. Setting: These techniques ...
Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is utilized to examine the mass spectra and fragmentation patterns of seven isomeric monosaccharides. Multivariate statistical analysis ...
Additionally, cluster analysis was also employed to decrease the dimensionality of the dataset, and squared Euclidean distance measures the distance between the clusters. Cluster analysis was ...
Milestone articles have highlighted the frequency and types of statistical errors in research,1–5 yet fundamental errors ...
This paper discusses CV for kernel canonical correlation analysis (KCCA), and proposes a new regularization approach for KCCA. As we demonstrate with Gaussian kernels, the CV errors for KCCA tend to ...
Objective We aimed to estimate prevalence and identify determinants of hypertension in adults aged 15–49 years in Tanzania.
About the course Medical statistics plays an essential role in all stages of a quantitative health care research project from design through to analysis and interpretation. This intensive course ...
This brief discusses a novel quality-driven principal component analysis method for statistical process monitoring. Through a nonlinear mapping, the original measurement space is mapped to another ...
Flexible Statistics and Data Analysis (FSDA) extends MATLAB for a robust analysis of data sets affected by different sources of heterogeneity. It is open source software licensed under the European ...
A framework of establishing standard reference scale (texture) is proposed by multivariate statistical analysis according to instrumental measurement and sensory evaluation. Multivariate statistical ...
Anthropic says it has released a new set of AI models tailored for U.S. national security customers. The new models, a custom set of “Claude Gov” models, were “built based on direct feedback ...
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