Results 41 to 50 of about 148 (142)
Item response theory for longitudinal data: Item and population ability parameters estimation
Logistic model, covariance structures, multivariate latent distribution, repeated measure, binary response, 62F10, 62H05, 62H12, 62J02,
Dalton Andrade, Heliton Tavares
core +1 more source
In this paper, we consider an estimation algorithm called cyclic iterative algorithm (CA) that is used in statistics to estimate the unknown vector parameter of a crash data model.
Geraldo, Issa Cherif +2 more
core +1 more source
Assessing copula models for mixed continuous-ordinal variables
Vine pair-copula constructions exist for a mix of continuous and ordinal variables. In some steps, this can involve estimating a bivariate copula for a pair of mixed continuous-ordinal variables.
Pan Shenyi, Joe Harry
doaj +1 more source
Ultrasensitive Detection of Circulating LINE-1 ORF1p as a Specific Multicancer Biomarker. [PDF]
Taylor MS +58 more
europepmc +1 more source
Monotone missing data, Elliptically contoured distributions, Estimation, Discriminant Analysis, Error rate, Multivariate t-distribution, 62H12, 62H15,
K. Zografos, A. Batsidis
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Test for Independence of the Variables with Missing Elements in One and the Same Column of the Empirical Correlation Matrix [PDF]
2000 Mathematics Subject Classification: 62H15, 62H12.We consider variables with joint multivariate normal distribution and suppose that the sample correlation matrix has missing elements, located in one and the same column.
Veleva, Evelina
core
Classifiers, Repeated measures data, Kronecker product covariance structure, Maximum likelihood estimates, Primary 62H30, Secondary 62H12,
Mirosław Krzyśko, Michał Skorzybut
core +1 more source
Non-convex problem, Constrained optimisation, Primal and dual problem, Robust estimators, Image analysis, 62J05, 90C26, 90C55, 90C90, 49M29, 65K05, 62H12, 62H35,
Jean-Philippe Tarel +2 more
core +1 more source
Nonparametric methods in multivariate factorial designs
A nonparametric approach to the analysis of multivariate data is presented that is based on seperate rankings for different variables and extends the results of Akritas ct al. (1997. J. Amer. Statist. Assoc.
Brunner, E., Munzel, U.
core +1 more source
On misspecification of the dispersion matrix in mixed linear models
Mixed linear model, True model, Misspecified model, Dispersion, Random regression coefficient model, Compound symmetric, 62H12, 62F10, 62M20, 15A09,
Xu-Qing Liu, Jian-Ying Rong
core +1 more source

