A penalized likelihood framework for high-dimensional phylogenetic comparative methods and an application to new-world monkeys brain evolution
Working with high-dimensional phylogenetic comparative data sets is challenging because
likelihood-based multivariate methods suffer from low statistical performances as the …
likelihood-based multivariate methods suffer from low statistical performances as the …
Reliable phylogenetic regressions for multivariate comparative data: illustration with the MANOVA and application to the effect of diet on mandible morphology in …
Understanding what shapes species phenotypes over macroevolutionary timescales from
comparative data often requires studying the relationship between phenotypes and putative …
comparative data often requires studying the relationship between phenotypes and putative …
Regularization methods for fitting linear models with small sample sizes: Fitting the lasso estimator using R
WH Finch, MEH Finch - Practical Assessment, Research …, 2019 - scholarworks.umass.edu
Researchers and data analysts are sometimes faced with the problem of very small
samples, where the number of variables approaches or exceeds the overall sample size; ie …
samples, where the number of variables approaches or exceeds the overall sample size; ie …
A pathway for multivariate analysis of ecological communities using copulas
MJ Anderson, P de Valpine, A Punnett… - Ecology and …, 2019 - Wiley Online Library
We describe a new pathway for multivariate analysis of data consisting of counts of species
abundances that includes two key components: copulas, to provide a flexible joint model of …
abundances that includes two key components: copulas, to provide a flexible joint model of …
Group-wise ANOVA simultaneous component analysis for designed omics experiments
Introduction Modern omics experiments pertain not only to the measurement of many
variables but also follow complex experimental designs where many factors are …
variables but also follow complex experimental designs where many factors are …
Milk renneting: Study of process factor influences by FT-NIR spectroscopy and chemometrics
The dairy industry is continuously developing new strategies to obtain healthier dairy
products preserving expected properties. However, when modifying a food process, the …
products preserving expected properties. However, when modifying a food process, the …
Multivariate Kruskal_Wallis tests based on principal component score and latent source of independent component analysis
A Mukherjee, H Murakami - … & New Zealand Journal of Statistics, 2022 - Wiley Online Library
Analysing multivariate and high_dimensional multi_sample data is essential in many
scientific fields. One of the most crucial and popular topics in modern nonparametric …
scientific fields. One of the most crucial and popular topics in modern nonparametric …
Limiting behavior of eigenvalues in high-dimensional MANOVA via RMT
Z Bai, KP Choi, Y Fujikoshi - 2018 - projecteuclid.org
Supplement to “Limiting behavior of eigenvalues in high-dimensional MANOVA via RMT”. In
the supplementary material, we presented (i) the truncation and normalization techniques as …
the supplementary material, we presented (i) the truncation and normalization techniques as …
Similarity-based multimodal regression
To better understand complex human phenotypes, large-scale studies have increasingly
collected multiple data modalities across domains such as imaging, mobile health, and …
collected multiple data modalities across domains such as imaging, mobile health, and …
A comparison of methods for estimating the determinant of high-dimensional covariance matrix
The determinant of the covariance matrix for high-dimensional data plays an important role
in statistical inference and decision. It has many real applications including statistical tests …
in statistical inference and decision. It has many real applications including statistical tests …