Results 81 to 90 of about 690,275 (266)
Robust sparse principal component analysis. [PDF]
A method for principal component analysis is proposed that is sparse and robust at the same time. The sparsity delivers principal components that have loadings on a small number of variables, making them easier to interpret.
Croux, Christophe +2 more
core
Linear Dimensionality Reduction: What Is Better?
DataThis research paper focuses on dimensionality reduction, which is a major subproblem in any data processing operation. Dimensionality reduction based on principal components is the most used methodology. Our paper examines three heuristics, namely Kaiser’
Mohit Baliyan, Evgeny M. Mirkes
doaj +1 more source
Mining gene expression data by interpreting principal components
BMC Bioinformatics, 2006 Background There are many methods for analyzing microarray data that group together genes having similar patterns of expression over all conditions tested. However, in many instances the biologically important goal is to identify relatively small sets of
Mortazavi Ali +5 more
doaj +1 more source
Immunoglobulin Depletion and Recovery Following Blinatumomab in Infants With KMT2A‐Rearranged ALL
Pediatric Blood &Cancer, EarlyView.ABSTRACT Adding blinatumomab to standard chemotherapy for infants with KMT2A‐rearranged acute B‐cell lymphoblastic leukemia (KMT2A‐r B‐ALL) improves outcomes. Although blinatumomab impairs immunoglobulin G (lgG) production, increasing infection susceptibility, IgG recovery remains poorly understood.
Miguel Vieira Martins +14 more
wiley +1 more source
Pediatric Blood &Cancer, EarlyView.ABSTRACT As part of the European Cooperative Study Group for Paediatric Rare Tumours initiative, we developed standard clinical practice guidelines for ovarian sex cord stromal tumors, based on comprehensive national and international cohort analyses, literature review, and a final expert consensus conference.
Dominik T. Schneider +15 more
wiley +1 more source
Detecting Genotype-Population Interaction Effects by Ancestry Principal Components
Frontiers in Genetics, 2020 Heterogeneity in the phenotypic mean and variance across populations is often observed for complex traits. One way to understand heterogeneous phenotypes lies in uncovering heterogeneity in genetic effects.
Chenglong Yu +8 more
doaj +1 more source
A principal components analysis of the UK term structure and the influence of fiscal policy [PDF]
This study examines the use of principal component techniques in analysing term structures of interest rates. It employs original methods of estimating B-Spline models with endogenous knot positions and applies the method of Dierckx (1981) to generate ...
Egginton, D. M. (Donald Michael)
core
Principal Components and Factor Analysis. A Comparative Study. [PDF]
A comparison between Principal Component Analysis (PCA) and Factor Analysis (FA) is performed both theoretically and empirically for a random matrix X:(n x p) , where n is the number of observations and both coordinates may be very large.
Travaglini, Guido
core +1 more source
Principal component analysis of functional principal components. [PDF]
, 2018 Principal component analysis of functional principal components.
Seungmi Yang (611033) +6 more
core +1 more source