Results 61 to 70 of about 4,208,641 (395)
Local functional principal component analysis
, 2007 Covariance operators of random functions are crucial tools to study the way random elements concentrate over their support. The principal component analysis of a random function X is well-known from a theoretical viewpoint and extensively used in ...
Mas, André
core +1 more source
Principal Component Analysis Of Synthetic Galaxy Spectra [PDF]
, 1998 We analyse synthetic galaxy spectra from the evolutionary models of Bruzual&Charlot and Fioc&Rocca-Volmerange using the method of Principal Component Analysis (PCA).
Alfonso Aragón-Salamanca +29 more
core +3 more sources
Population Ecology, EarlyView.In this study, we compared three methods for kinship identification using different algorithms in samples of wild Pacific bluefin tuna and generated genotyping data. The three methods resulted in different numbers of inferred kinship pairs for both generated and actual data. Particularly for the half‐sibling pairs, considerable number of false‐positive
Yohei Tsukahara +5 more
wiley +1 more source
Principal Component Analysis In Radar Polarimetry [PDF]
Advances in Radio Science, 2005 Second order moments of multivariate (often Gaussian) joint probability density functions can be described by the covariance or normalised correlation matrices or by the Kennaugh matrix (Kronecker matrix).
A. Danklmayer, M. Chandra, E. Lüneburg
doaj
HisCoM-PCA: software for hierarchical structural component analysis for pathway analysis based using principal component analysis [PDF]
Genomics & Informatics, 2020 In genome-wide association studies, pathway-based analysis has been widely performed to enhance interpretation of single-nucleotide polymorphism association results.
Nan Jiang, Sungyoung Lee, Taesung Park
doaj +1 more source
Uncertainty-Aware Principal Component Analysis
, 2019 We present a technique to perform dimensionality reduction on data that is subject to uncertainty. Our method is a generalization of traditional principal component analysis (PCA) to multivariate probability distributions.
Deussen, Oliver +4 more
core +1 more source
The dual nature of TDC – bridging dendritic and T cells in immunity
FEBS Letters, EarlyView.TDC are hematopoietic cells combining dendritic and T cell features. They reach secondary lymphoid organs (SLOs) and peripheral organs (liver and lungs) after FLT3‐dependent development in the bone marrow and maturation in the thymus. TDC are activated and enriched in SLOs upon viral infection, suggesting that they might play unique immune roles, since
Maria Nelli, Mirela Kuka
wiley +1 more source
Stable Analysis of Compressive Principal Component Pursuit
Algorithms, 2017 Compressive principal component pursuit (CPCP) recovers a target matrix that is a superposition of low-complexity structures from a small set of linear measurements. Pervious works mainly focus on the analysis of the existence and uniqueness.
Qingshan You, Qun Wan
doaj +1 more source
Principal Component Analysis of Munich Functional Developmental Diagnosis
Pediatric Reports, 2021 Objectives: Munich Functional Developmental Diagnosis (MFDD) is a scale for assessing the psychomotor development of children in the first months or years of life.
Grażyna Pazera +3 more
doaj +1 more source
Principal Moment Analysis [PDF]
arXiv, 2020 Principal Moment Analysis is a method designed for dimension reduction, analysis and visualization of high dimensional multivariate data. It generalizes Principal Component Analysis and allows for significant statistical modeling flexibility, when approximating an unknown underlying probability distribution, by enabling direct analysis of general ...
arxiv