Results 111 to 120 of about 55,908 (306)

Covariance matrices for experimental stimuli. [PDF]

, 2016
Covariance matrices for experimental stimuli.
Christian E. Stilp (334561), Keith R. Kluender (204642)   +1 more
core   +1 more source

On Information Rank Deficiency in Phenotypic Covariance Matrices. [PDF]

Syst Biol, 2022
O'Keefe FR, Meachen JA, Polly PD.
europepmc   +1 more source

Condition‐Associated Pattern Extraction and Recovery From Multi‐Condition Single‐Cell RNA‐seq Data With CAPER

Advanced Science, EarlyView.
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li, Jin Ning, An Wang, Minxi Shi, Yuanze Chen, Guoliang Liu, Shiquan Sun   +6 more
wiley   +1 more source

Evaluating covariance matrix forecasts in a value-at-risk framework [PDF]

Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option ...
Christian A. Walter, Jose A. Lopez
core  

Combining partially overlapping covariance / relationship matrices [PDF]

, 2019
Combine partial covariance matrices using a Wishart-EM algorithm. Methods, described in the November 2019 article , can be used to combine partially overlapping covariance matrices from independent trials, partially overlapping multi-view ...
Julio Isidro-Sanchez (4892059), Deniz Akdemir (8140341)   +1 more
core   +1 more source

Combination of KLOE σ (e + e − → π+π−γ(γ)) measurements and determination of a μ π + π − $$ {a}_{\mu}^{\pi^{+}{\pi}^{-}} $$ in the energy range 0.10 < s < 0.95 GeV2

Journal of High Energy Physics, 2018
The three precision measurements of the cross section σ(e + e − → π + π −γ(γ)) using initial state radiation by the KLOE collaboration provide an important input for the prediction of the hadronic contribution to the anomalous magnetic moment of the muon.
The KLOE-2 collaboration, A. Anastasi, D. Babusci, M. Berlowski, C. Bloise, F. Bossi, P. Branchini, A. Budano, L. Caldeira Balkeståhl, B. Cao, F. Ceradini, P. Ciambrone, F. Curciarello, E. Czerwinski, G. D’Agostini, E. Danè, V. De Leo, E. De Lucia, A. De Santis, P. De Simone, A. Di Cicco, A. Di Domenico, D. Domenici, A. D’Uffizi, A. Fantini, G. Fantini, P. Fermani, S. Fiore, A. Gajos, P. Gauzzi, S. Giovannella, E. Graziani, V. L. Ivanov, T. Johansson, X. Kang, D. Kisielewska-Kaminska, E. A. Kozyrev, W. Krzemien, A. Kupsc, S. Loffredo, P. A. Lukin, G. Mandaglio, M. Martini, R. Messi, S. Miscetti, G. Morello, D. Moricciani, P. Moskal, A. Passeri, V. Patera, E. Perez del Rio, N. Raha, P. Santangelo, M. Schioppa, A. Selce, M. Silarski, F. Sirghi, E. P. Solodov, L. Tortora, G. Venanzoni, W. Wislicki, M. Wolke, A. Keshavarzi, S.E. Müller, T. Teubner   +64 more
doaj   +1 more source

Shrinkage estimators of large covariance matrices with Toeplitz targets in array signal processing. [PDF]

Sci Rep, 2022
Zhang B, Yuan S.
europepmc   +1 more source

Natural Variation of COLD and CATECHINS REGULATOR 1 Coordinately Fine‐Tunes Cold Tolerance and Tea Quality in Tea Plants

Advanced Science, EarlyView.
Multi‐trait genome‐wide association mapping identifies a central hub regulator, COLD AND CATECHINS REGULATOR 1 (CCR1), and its excellent natural allele variation, coordinately enhancing cold tolerance and promoting catechins biosyntheis. CsCCR1 interacts with CsCBF1/3 and is transcriptionally activated by CsLUX and CsKUA1 to promote catechins ...
Yanli Wang, Wei Tong, Qiong Wu, Didi Wu, Yanrui Zhang, Qijuan Gao, Fangdong Li, Zhaoliang Zhang, Wenjie Wang, Chuankui Song, Enhua Xia   +10 more
wiley   +1 more source

Eigenvalue variance bounds for covariance matrices [PDF]

, 2013
This work is concerned with finite range bounds on the variance of individual eigenvalues of random covariance matrices, both in the bulk and at the edge of the spectrum.
Dallaporta, Sandrine
core   +4 more sources

Constrained Covariance Matrices With a Biologically Realistic Structure: Comparison of Methods for Generating High-Dimensional Gaussian Graphical Models

Frontiers in Applied Mathematics and Statistics, 2019
High-dimensional data from molecular biology possess an intricate correlation structure that is imposed by the molecular interactions between genes and their products forming various different types of gene networks.
Frank Emmert-Streib, Frank Emmert-Streib, Shailesh Tripathi, Shailesh Tripathi, Matthias Dehmer, Matthias Dehmer, Matthias Dehmer   +6 more
doaj   +1 more source