Article
Statistics & Probability
Christian Rohrbeck, Daniel Cooley
Summary: This paper addresses the issue of generating hazard event sets of extreme river flow for northern England and southern Scotland. Through analyzing historical extreme river flow, the paper reveals interesting connections between the extremal dependence structure and the region's topography/climate. A generative framework is introduced to model the distribution of extremal principal components for generating synthetic events, which shows good agreement with observed extreme river flow dynamics.
ANNALS OF APPLIED STATISTICS
(2023)
Article
Public, Environmental & Occupational Health
Emma L. Anderson, Rebecca C. Richmond, Samuel E. Jones, Gibran Hemani, Kaitlin H. Wade, Hassan S. Dashti, Jacqueline M. Lane, Heming Wang, Richa Saxena, Ben Brumpton, Roxanna Korologou-Linden, Jonas B. Nielsen, Bjorn Olav Asvold, Goncalo Abecasis, Elizabeth Coulthard, Simon D. Kyle, Robin N. Beaumont, Jessica Tyrrell, Timothy M. Frayling, Marcus R. Munafo, Andrew R. Wood, Yoav Ben-Shlomo, Laura D. Howe, Deborah A. Lawlor, Michael N. Weedon, George Davey Smith
Summary: The study found limited evidence to support a causal effect of sleep traits on Alzheimer's disease (AD) risk. However, there was suggestive evidence that daytime napping may reduce AD risk. Further replication with independent samples is needed to confirm these findings.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY
(2021)
Article
Computer Science, Theory & Methods
Alec Koppel, Hrusikesha Pradhan, Ketan Rajawat
Summary: Gaussian processes provide a framework for nonlinear nonparametric Bayesian inference, but face computational burden scaling issues. The Parsimonious Online Gaussian Processes (POG) method has been developed to address approximation challenges with streaming data.
STATISTICS AND COMPUTING
(2021)
Article
Engineering, Chemical
Chun-Chin Hsu, Po-Chou Shih, Fang-Chih Tien
Summary: A novel weight strategy for multiblock PCA was proposed in this study, which considers the dependence and skewness of data to additionally take distribution information into account. The proposed weight matrix based on non-parametric ranks leads to shorter computation time. Experimental results show that the proposed method outperforms regular PCA, dynamic PCA, multiblock PCA, and WCMBPCA in fault detection rate for Tennessee Eastman (TE) process monitoring. Furthermore, the weight matrix calculation time is significantly shorter for the proposed method compared to WCMBPCA.
JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS
(2021)
Article
Computer Science, Interdisciplinary Applications
Raanju R. Sundararajan
Summary: Dimension reduction techniques for multivariate time series transform the observed series into lower-dimensional multivariate subseries using a spectral domain method, allowing for decomposition and reconstruction of the series.
COMPUTATIONAL STATISTICS & DATA ANALYSIS
(2021)
Article
Statistics & Probability
Karl Oskar Ekvall
Summary: In this article, we propose a principal components regression method that maximizes a joint pseudo-likelihood for both responses and predictors. Our method overcomes a common deficiency of conventional principal components regression by using both responses and predictors to select relevant linear combinations of predictors. Simulation results show that our method is more accurate than traditional principal components regression and is asymptotically more efficient compared to competing methods.
JOURNAL OF MULTIVARIATE ANALYSIS
(2022)
Article
Statistics & Probability
Caleb Kwon, Eric Mbakop
Summary: In this study, a novel estimator for the number of mixture components in a nonparametric finite mixture model is proposed. The estimator is based on the rank of an integral operator identified from the data and the stability of singular values under perturbations. It is shown to be consistent and has finite sample performance guarantees. Monte Carlo simulations demonstrate good performance for moderate sample sizes.
ANNALS OF STATISTICS
(2021)
Article
Humanities, Multidisciplinary
Hugh Craig
Summary: In response to a 2021 article criticizing the use of PCA in stylometry, the current article refutes the claims and shows the effectiveness of PCA through permutation testing and experiments. It highlights the lack of credibility in the theoretical claims and experimental results of the criticized article.
DIGITAL SCHOLARSHIP IN THE HUMANITIES
(2023)
Article
Computer Science, Artificial Intelligence
Stanislav Nagy
Summary: Depth functions are valuable tools in nonparametric statistics for analyzing multivariate data. This article explores the properties of the classical definition of simplicial depth, even when applied to data or measures without symmetric density. Recent advancements in discrete geometry are utilized to improve the understanding of the robustness and continuity of simplicial depth and its resultant multivariate median. Additionally, the article computes the exact simplicial depth in various scenarios and highlights some counterintuitive observations regarding its behavior.
STATISTICAL ANALYSIS AND DATA MINING
(2023)
Article
Chemistry, Analytical
Carollina de Melo Molinari Ortiz Antunes, Frederico Luis Felipe Soares, Noemi Nagata
Summary: Chemical analyses based on digital images are widely studied due to their non-invasive nature and simplicity. However, controlling instrumental and structural parameters for image acquisition is crucial for analysis repeatability and reproducibility. The high cost of accessing robust instruments is also a practical limitation. To overcome these limitations, a low-cost prototype using Raspberry Pi and multivariate tools was developed.
MICROCHEMICAL JOURNAL
(2023)
Article
Chemistry, Applied
Xiaoyue Ji
Summary: The study used HS-SPME and GC-MS to analyze the volatile components in commercial beers, with alcohols and esters identified as the predominant volatile compounds. Multivariate analysis can differentiate different beer types, and the type and content of volatile compounds can influence beer quality and taste.
FLAVOUR AND FRAGRANCE JOURNAL
(2021)
Article
Food Science & Technology
Maryia Bakhtsiyarava, Tim G. Williams, Andrew Verdin, Seth D. Guikema
Summary: This study uses nonparametric regression methods to analyze the relationship between food insecurity and household survey data, revealing complex nonlinear and threshold relationships between food security measures, livestock ownership, and climatic conditions. The findings suggest that policy decisions should take into account nonlinearity, and that random forest and other nonparametric methods may be particularly useful in uncovering nuances in these relationships during suboptimal climatic conditions.
Review
Behavioral Sciences
Chiara Andreola, Sara Mascheretti, Raffaella Belotti, Anna Ogliari, Cecilia Marino, Marco Battaglia, Simona Scaini
Summary: Reading ability involves the integration of multiple cognitive and perceptual systems, including language, visual, memory, attention, and motor functions. Genetic and environmental influences vary for different reading-related neurocognitive components, with shared environment playing a more important role in language. Generally, the causal architecture for most components can be represented by a specific equation, and school grade levels can moderate the heritability of certain reading skills.
NEUROSCIENCE AND BIOBEHAVIORAL REVIEWS
(2021)
Article
Ecology
Michael L. Collyer, Dean C. Adams
Summary: Phylogenetically aligned component analysis (PACA) is a new ordination approach that aligns phenotypic data with phylogenetic signal, allowing visualization of trends in phylogenetic signal in multivariate data spaces. By maximizing variation in directions that describe phylogenetic signal, PACA can distinguish between weak and strong phylogenetic signals, providing a more precise description of the phylogenetic signal in studies focused on phylogenetic signal. Comparing PACA and Phy-PCA results can help determine the relative importance of phylogenetic and other signals in the data.
METHODS IN ECOLOGY AND EVOLUTION
(2021)
Article
Mathematical & Computational Biology
Ralph Moller Trane, Hyunseung Kang
Summary: This article explores the use of nonparametric bound-based analysis in two-sample MR studies and proposes a framework to assess the possibility of obtaining more informative bounds using different MR designs. The results suggest that bound-based analysis is more conservative in two-sample settings compared to one-sample settings.
STATISTICS IN MEDICINE
(2022)
Article
Neuroimaging
Yaakov Stern
BRAIN IMAGING AND BEHAVIOR
(2017)
Article
Neurosciences
C. Habeck, Q. Razlighi, Y. Gazes, D. Barulli, J. Steffener, Y. Stern
Article
Neurosciences
Qolamreza R. Razlighi, Hwamee Oh, Christian Habeck, Deirdre O'Shea, Elaine Gazes, Teal Eich, David B. Parker, Seonjoo Lee, Yaakov Stern
Article
Neurosciences
Carolyn W. Zhu, Stephanie Cosentino, Katherine A. Ornstein, Yian Gu, Howard Andrews, Yaakov Stern
JOURNAL OF ALZHEIMERS DISEASE
(2017)
Article
Neurosciences
Martin J. Lan, R. Todd Ogden, Dileep Kumar, Yaakov Stern, Ramin V. Parsey, Gregory H. Pelton, Harry Rubin-Falcone, Gnanavalli Pradhaban, Francesca Zanderigo, Jeffrey M. Miller, J. John Mann, D. P. Devanand
JOURNAL OF ALZHEIMERS DISEASE
(2017)
Article
Neurosciences
Bruce P. Dore, Chelsea Boccagno, Daisy Burr, Alexa Hubbard, Kan Long, Jochen Weber, Yaakov Stern, Kevin N. Ochsner
JOURNAL OF COGNITIVE NEUROSCIENCE
(2017)
Article
Geriatrics & Gerontology
Justin S. Golub, Jose A. Luchsinger, Jennifer J. Manly, Yaakov Stern, Richard Mayeux, Nicole Schupf
JOURNAL OF THE AMERICAN GERIATRICS SOCIETY
(2017)
Article
Geriatrics & Gerontology
Nicolai Franzmeier, Katharina Buerger, Stefan Teipel, Yaakov Stern, Martin Dichgans, Michael Ewers
NEUROBIOLOGY OF AGING
(2017)
Article
Behavioral Sciences
A. Tsapanou, Y. Gu, D. M. O'Shea, M. Yannakoulia, M. Kosmidis, E. Dardiotis, G. Hadjigeorgiou, P. Sakka, Y. Stern, N. Scarmeas
NEUROBIOLOGY OF LEARNING AND MEMORY
(2017)
Article
Neurosciences
Qolamreza R. Razlighi, Christian Habeck, Daniel Barulli, Yaakov Stern
Article
Clinical Neurology
Giuseppe Tosto, Thomas D. Bird, Debby Tsuang, David A. Bennett, Bradley F. Boeve, Carlos Cruchaga, Kelley Faber, Tatiana M. Foroud, Martin Farlow, Alison M. Goate, Sarah Bertlesen, Neill R. Graff-Radford, Martin Medrano, Rafael Lantigua, Jennifer Manly, Ruth Ottman, Roger Rosenberg, Daniel J. Schaid, Nicole Schupf, Yaakov Stern, Robert A. Sweet, Richard Mayeux
Article
Medicine, General & Internal
Yaakov Stern, Seonjoo Lee, David Predovan, Richard P. Sloan
JOURNAL OF CLINICAL MEDICINE
(2019)
Article
Genetics & Heredity
Angeliki Tsapanou, Niki Mourtzi, Sokratis Charisis, Alex Hatzimanolis, Eva Ntanasi, Mary H. Kosmidis, Mary Yannakoulia, Georgios Hadjigeorgiou, Efthimios Dardiotis, Paraskevi Sakka, Yaakov Stern, Nikolaos Scarmeas
Summary: Sleep problems are associated with cognition, and specific genes are associated with sleep regulation and cognition. This study validates the association between Sleep Polygenic Risk Score (Sleep PRS) and self-reported sleep duration, and finds an association between Sleep PRS and cognitive changes related to visuo-spatial ability in older non-demented adults.
Article
Genetics & Heredity
Angeliki Tsapanou, Margaret Gacheru, Seonjoo Lee, Niki Mourtzi, Yunglin Gazes, Christian Habeck, Daniel W. Belsky, Yaakov Stern
Summary: This study analyzed the relationship between genetics and cognitive performance, and found that genetics play a moderating role in cognitive aging. The results suggest that genetics have a stronger association with cognitive performance in young and midlife older adults.
Article
Clinical Neurology
Yaakov Stern, Yian Gu, Stephanie Cosentino, Martina Azar, Siobhan Lawless, Oksana Tatarina
ALZHEIMERS & DEMENTIA
(2017)