Results 141 to 150 of about 1,566,040 (193)

Multivariate logistische Regression [PDF]

, 2019
openaire   +1 more source

Multivariate regression analysis of structural MRI connectivity matrices in Alzheimer's disease. [PDF]

PLoS One, 2017
Rasero J, Amoroso N, La Rocca M, Tangaro S, Bellotti R, Stramaglia S, Alzheimer’s Disease Neuroimaging Initiative.   +6 more
europepmc   +1 more source

Multivariate Regression Models

, 2015
openaire   +1 more source

Some of the next articles are maybe not open access.

Related searches:

Multivariate Multilinear Regression

IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), 2012
Conventional regression methods, such as multivariate linear regression (MLR) and its extension principal component regression (PCR), deal well with the situations that the data are of the form of low-dimensional vector. When the dimension grows higher, it leads to the under sample problem (USP): the dimensionality of the feature space is much higher ...
Su, Ya, Gao, Xinbo, Li, Xuelong, Tao, Dacheng   +3 more
openaire   +3 more sources

Bayesian Multivariate Logistic Regression

Biometrics, 2004
SummaryBayesian analyses of multivariate binary or categorical outcomes typically rely on probit or mixed effects logistic regression models that do not have a marginal logistic structure for the individual outcomes. In addition, difficulties arise when simple noninformative priors are chosen for the covariance parameters.
O'Brien, Sean M., Dunson, David B.
openaire   +3 more sources

Estimation of Multivariate Regression

Theory of Probability & Its Applications, 2004
Summary: Let \((X,Y)\) be a random vector whose first component takes values in a measurable space \(({\mathfrak{X}},{\mathfrak{A}},\mu)\) with measure \(\mu\), and let \(Y\) be a real-valued random variable. Let \(f(x)={\mathbf E}\{Y\mid X=x\} \) be the regression function of \(Y\) on \(X\).
openaire   +2 more sources

Multivariate Regression Modeling

Journal of Solar Energy Engineering, 1998
An empirical or regression modeling approach is simple to develop and easy to use compared to detailed hourly simulations of energy use in commercial buildings. Therefore, regression models developed from measured energy data are becoming an increasingly popular method for determining retrofit savings or identifying operational and maintenance (O&M)
S. Katipamula, T. A. Reddy, D. E. Claridge   +2 more
openaire   +1 more source