Journal ArticleDOI
Parameter Orthogonality and Approximate Conditional Inference
David Cox,Nancy Reid +1 more
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In this paper, the authors propose a statisticalique du rapport de vraisemblance construite a partir de la distribution conditionnelle des observations, and donne les estimateurs du maximum de VRAISEMblance for les parametres de nuisance.Abstract:
On propose une statistique du rapport de vraisemblance construite a partir de la distribution conditionnelle des observations, etant donne les estimateurs du maximum de vraisemblance pour les parametres de nuisanceread more
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Journal ArticleDOI
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Posted ContentDOI
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
TL;DR: This work presents DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates, which enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression.
Journal ArticleDOI
Approximate inference in generalized linear mixed models
Norman E. Breslow,D. G. Clayton +1 more
TL;DR: In this paper, generalized linear mixed models (GLMM) are used to estimate the marginal quasi-likelihood for the mean parameters and the conditional variance for the variances, and the dispersion matrix is specified in terms of a rank deficient inverse covariance matrix.
Journal ArticleDOI
Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
TL;DR: This work considers approximate Bayesian inference in a popular subset of structured additive regression models, latent Gaussian models, where the latent field is Gaussian, controlled by a few hyperparameters and with non‐Gaussian response variables and can directly compute very accurate approximations to the posterior marginals.
Journal ArticleDOI
Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation
TL;DR: A flexible statistical framework is developed for the analysis of read counts from RNA-Seq gene expression studies, and parallel computational approaches are developed to make non-linear model fitting faster and more reliable, making the application of GLMs to genomic data more convenient and practical.
References
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Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Regression models and life tables (with discussion
TL;DR: The drum mallets disclosed in this article are adjustable, by the percussion player, as to balance, overall weight, head characteristics and tone production of the mallet, whereby the adjustment can be readily obtained.
Journal ArticleDOI
Recovery of inter-block information when block sizes are unequal
H. D. Patterson,Robin Thompson +1 more
TL;DR: In this article, a modified maximum likelihood procedure is proposed for estimating intra-block and inter-block weights in the analysis of incomplete block designs with block sizes not necessarily equal, and the method consists of maximizing the likelihood, not of all the data, but of selected error contrasts.
Journal ArticleDOI
On the Mathematical Foundations of Theoretical Statistics
TL;DR: In this paper, the authors define the center of location as the abscissa of a frequency curve for which the sampling errors of optimum location are uncorrelated with those of optimum scaling.