Results 211 to 220 of about 89,713 (255)

Fast Estimation and Valid Statistical Inference for Mixed-Effect Location-Scale Models Using Variational Inference. [PDF]

Stat Med
Wu BP, Hedeker D.
europepmc   +1 more source

Unraveling the Influence of Elevation on Moss Species-Area Relationships and the Effect of Spatial Scale on Elevational Richness Patterns in Mt Wutai With a Nested-Plot Sampling Design. [PDF]

Ecol Evol
Wang H, Wang F, Zhao Y, Li C, Ma X, Wang X, Zhang L, Gao.   +7 more
europepmc   +1 more source

Robust Bayesian multilevel meta-analysis: Adjusting for publication bias in the presence of dependent effect sizes. [PDF]

Behav Res Methods
Bartoš F, Maier M, Wagenmakers EJ.
europepmc   +1 more source

Wave spectrum Reconstruction Parameters for nested wave modeling in the China-adjacent seas from 2000 to 2024. [PDF]

Sci Data
Jiang X, Yang Y, Yin X, Zha Y.
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Prediction in an Unbalanced Nested Error Components Panel Data Model

Journal of Forecasting, 2013
ABSTRACTThis paper derives the best linear unbiased predictor for an unbalanced nested error components panel data model. This predictor is useful in many econometric applications that are usually based on unbalanced panel data and have a nested (hierarchical) structure.
Badi Baltagi
exaly   +2 more sources

On Testing Linear Hypothesis in a Nested Error Regression Model

Communications in Statistics - Theory and Methods, 2010
Consider the problem of testing the linear hypothesis on regression coefficients in the nested error regression model. The standard F-test statistic based on the ordinary least squares (OLS) estimator has the serious shortcoming that its type I error rates (sizes) are much larger than nominal significance levels, because the covariance matrix of data ...
Tatsuya Kubokawa
exaly   +2 more sources

BLUP in the nested panel regression model with serially correlated errors

Computational Statistics and Data Analysis, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Myoungshic Jhun, Seuck Heun Song
exaly   +2 more sources

Prediction in a spatial nested error components panel data model

International Journal of Forecasting, 2014
Abstract This paper derives the Best Linear Unbiased Predictor (BLUP) for a spatial nested error components panel data model. This predictor is useful for panel data applications that exhibit spatial dependence and a nested (hierarchical) structure. The predictor allows for unbalancedness in the number of observations in the nested groups.
Badi Baltagi
exaly   +2 more sources