Results 21 to 30 of about 12,200,920 (299)
Effective Bi-immunity and Randomness [PDF]
, 2016 We study the relationship between randomness and effective bi-immunity. Greenberg and Miller have shown that for any oracle X, there are arbitrarily slow-growing DNR functions relative to X that compute no ML random set. We show that the same holds when ML randomness is replaced with effective bi-immunity.
Achilles A. Beros +2 more
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Mathematics, 2022 This article presents the results of the implementation of a forecasting model, to predict the relief materials needed for assisting in decisions prior to natural disasters, thus filling a gap in the exploration of Generalized Linear Mixed Models (GLMM ...
Camila Pareja Yale +2 more
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On random-effects meta-analysis [PDF]
Biometrika, 2015 Meta-analysis is widely used to compare and combine the results of multiple independent studies. To account for between-study heterogeneity, investigators often employ random-effects models, under which the effect sizes of interest are assumed to follow a normal distribution.
D. Zeng, D. Y. Lin
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Misspecification in Generalized Linear Mixed Models and Its Impact on the Statistical Wald Test
Applied Sciences, 2023 Generalized linear mixed models are commonly used in repeated measurement studies and account for the dependence between observations obtained from the same experimental unit.
Diana Arango-Botero +2 more
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The effect of splitting on random forests [PDF]
Machine Learning, 2014 The effect of a splitting rule on random forests (RF) is systematically studied for regression and classification problems. A class of weighted splitting rules, which includes as special cases CART weighted variance splitting and Gini index splitting, are studied in detail and shown to possess a unique adaptive property to signal and noise. We show for
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The effect of random-effects misspecification on classification accuracy [PDF]
The International Journal of Biostatistics, 2021 Abstract Mixed models are a useful way of analysing longitudinal data. Random effects terms allow modelling of patient specific deviations from the overall trend over time. Correlation between repeated measurements are captured by specifying a joint distribution for all random effects in a model.
Riham El Saeiti +2 more
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Statistical Inference of Wiener Constant-Stress Accelerated Degradation Model with Random Effects
Mathematics, 2022 In the field of reliability analysis, the constant-stress accelerated degradation test is one of the most commonly used methods to evaluate a product’s reliability as degradation data are provided. In this paper, a constant-stress accelerated degradation
Peihua Jiang
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Effective aspects of Bernoulli randomness [PDF]
Journal of Logic and Computation, 2019 AbstractIn this paper, we study Bernoulli random sequences, i.e. sequences that are Martin-Löf random with respect to a Bernoulli measure $\mu _p$ for some $p\in [0,1]$, where we allow for the possibility that $p$ is noncomputable. We focus in particular on the case in which the underlying Bernoulli parameter $p$ is proper (i.e.
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Random-effects pooled MD for VAT and SAT.
, 2022 Random-effects pooled MD for VAT and SAT.
Hongli Zhang (518920) +7 more
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Revstat Statistical Journal, 2018 The generalized linear mixed effects model (GLMM) approach is widely used to analyze longitudinal binary data when the goal of the study is a subject-specific interpretation because it allows missing values on the response, provided they are missing at ...
M. Salomé Cabral +1 more
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