Results 21 to 30 of about 205 (138)
Some theoretical foundations for the design and analysis of randomized experiments
Journal of Causal InferenceNeyman’s seminal work in 1923 has been a milestone in statistics over the century, which has motivated many fundamental statistical concepts and methodology.
Shi Lei, Li Xinran
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Aligned Rank Statistics for Repeated Measurement Models with Orthonormal Design, Employing a Chernoff-Savage Approach [PDF]
, 2004 AMS classifications: 62G10, 62G20 ...
Einmahl, J.H.J. +3 more
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Regression(s) discontinuity: Using bootstrap aggregation to yield estimates of RD treatment effects
Journal of Causal InferenceFollowing Efron (2014), we propose an algorithm for estimating treatment effects for use by researchers employing a regression-discontinuity (RD) design.
Long Mark C., Rooklyn Jordan
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A matrix approach to determine optimal predictors in a constrained linear mixed model
Open MathematicsFor a general vector of all unknown vectors in a constrained linear mixed model (CLMM), this study compared the dispersion matrices of the best linear unbiased predictors with any symmetric matrix for determining the optimality of predictors among others.
Güler Nesrin, Büyükkaya Melek Eriş
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A new stochastic mixed ridge estimator in linear regression model
, 2010 Ordinary ridge estimator, Ordinary mixed estimator, Stochastic mixed ridge estimator, Mean squared error matrix, 62J05, 62F30,
Hu Yang, Yalian Li
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Bayesian regression analysis with linked data using mixture normal distributions
Record linkage, Bayesian regression, Mixture distribution, 62J05, 14M99,
Afshin Fallah, Mohsen Mohammadzadeh
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Bayesian reference prior analysis for polynomial calibration models
Clearance circle bioassay, inverse prediction, Noninformative prior, polynomial regression, 62F15, 62F25, 62J05, 62P10,
Keying Ye, Daniel Eno
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Bootstrap for estimating the MSE of the Spatial EBLUP
, 2009 Spatial correlation, Simultaneously autoregressive process, Small area estimation, Parametric bootstrap, Non-parametric bootstrap, 62D05, 62J05,
SALVATI, NICOLA +5 more
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InPrimeSmall area estimation (SAE) is an important technique for estimating parameters in regions or sub-populations with limited sample sizes, particularly when direct estimators are inadequate in capturing area-specific information. The Empirical Best Linear
Alya Safira Irtiqa Miolo +2 more
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Bayesian prediction in growth-curve models with correlated errors
Autoregressive model, calibration, correlated errors, Gibbs sampling, growth curves, hicrarchical model, inverse prediction, panel data, prediction, 62F15, 62J05,
Ulrich Menzefricke
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