Results 251 to 260 of about 620,297 (279)

Longitudinal omics data analysis: approaches and applications. [PDF]

Comput Struct Biotechnol J
Taheriyoun AR, Ross A, Safikhani A, Soudbakhsh D, Rahnavard A.   +4 more
europepmc   +1 more source

AI-enhanced clustering of mine tailings using Geostatistical data augmentation and Gaussian mixture models. [PDF]

Sci Rep
Madani N, Sabanov S.
europepmc   +1 more source

A reference tissue implementation of Simultaneous Multifactor Bayesian Analysis (SiMBA) of PET time activity curve data. [PDF]

Imaging Neurosci (Camb)
Matheson GJ, Lundberg J, Gärde M, Veldman ER, Tateno A, Okubo Y, Tiger M, Ogden RT.   +7 more
europepmc   +1 more source

Meta-analysis and Meta-regression for Uncertain Areas and the Estimation of Possible Benefit of Future Therapies. [PDF]

Eur Cardiol
Cordero A, Santos-Gallego CG, Oterino A, Rodriguez-Mañero M, Fernández-Olmo R, Quesada AJ.   +5 more
europepmc   +1 more source

A study on the role of cuproptosis-related immune checkpoint genes in non-small cell lung cancer. [PDF]

Medicine (Baltimore)
Han K, Wang JK, Yao J.
europepmc   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Composite likelihood estimation in multivariate data analysis

Canadian Journal of Statistics, 2005
Summary: The authors propose two composite likelihood estimation procedures for multivariate models with regression/univariate and dependence parameters. One is a two-stage method based on both univariate and bivariate margins. The other estimates all the parameters simultaneously based on bivariate margins.
Zhao, Yinshan, Joe, Harry
openaire   +2 more sources

Analysis of Uncertainties in Estimates of Components of Variance in Multivariate ROC Analysis

Academic Radiology, 2001
Solutions have previously been presented to the problem of estimating the components of variance in the general linear model used for multivariate receiver operating characteristic (ROC) analysis. The case where the variance components do not change across the modalities under comparison was first treated, followed by the case where they are permitted ...
S V, Beiden, R F, Wagner, G, Campbell, H P, Chan   +3 more
openaire   +2 more sources

Estimation in High-Dimensional Analysis and Multivariate Linear Models

Communications in Statistics - Theory and Methods, 2011
This article presents a new approach of estimating the parameters describing the mean structure in the Growth Curve model when the number of variables compared with the number of observations is large. An unbiased, consistent, and asymptotic normal estimator is derived as well as its.
Tõnu Kollo, Tatjana Von Rosen, Dietrich Von Rosen   +2 more
openaire   +1 more source

Robust Procedures in Multivariate Analysis I: Robust Covariance Estimation

Applied Statistics, 1980
SUMMARY The detection of atypical observations from multivariate data sets can be enhanced by examining probabilityplotsofMahalanobis squared distances using robust M-estimates of means and of covariances, rather than the usual maximum likelihood estimates.
openaire   +1 more source

Bayes Estimate of the Noncentrality Parameter in Multivariate Analysis

Communications in Statistics - Simulation and Computation, 1974
Madansky and Olkin (1969) derived approximate confidence intervals for the parameter,μ∑-1μ This paper deals with the estimation of the parameter using a Bayes technique. The general case with parameter Ω=∑-1MN is also considered and Bayes estimates of Ω and tr j Ω derived.
openaire   +2 more sources