Linear models (Statistics)
Overview
Works: | 148 works in 57 publications in 57 languages |
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Titles
Methods and applications of linear models :regression and the analysis of variance /
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Multivariate statistical modelling based on generalized linear models /
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Applied linear statistical models :regression, analysis of variance, and experimental designs /
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Nonlinear economic models :cross-sectional, times series and neural network applications /
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Linear and graphical models :for the multivariate complex normal distribution /
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A first course in the design of experiments :a linear models approach /
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Advanced linear modeling :multivariate, time series, and spatial data; nonparametric regression and response surface maximization /
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Regression modeling strategies :with applications to linear models, logistic regression, and survival analysis /
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Methods and applications of linear models :regression and the analysis of variance /
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Multivariate statistical modelling based on generalized linear models /
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Multivariate statistical modelling based on generalized linear models /
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Hierarchical linear models :applications and data analysis methods /
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Interpreting probability models :logit, probit, and other generalized linear models /
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Generalized linear models with random effects :unified analysis via h-likelihood /
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Fixed effects regression methods for longitudinal data using SAS /
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Recent Advances in Linear Models and Related AreasEssays in Honour of Helge Toutenburg /
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Linear models :the theory and application of analysis of variance /
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Conditional and unconditional conservatismimplications for accounting based valuation and risky projects /
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Linear and generalized linear mixed models and their applications /
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Univariate and multivariate general linear models :theory and applications with SAS /
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Statistical modelling and regression structuresfestschrift in honour of Ludwig fahrmeir /
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Linearization models for complex dynamical systemstopics in univalent functions, functional equations and semigroup theory /
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Advances in directional and linear statisticsa festschrift for Sreenivasa Rao Jammalamadaka /
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Generalized linear modelswith applications in engineering and the sciences /
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Regression, ANOVA, and the general linear model :a statistics primer /
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Vector generalized linear and additive modelswith an implementation in R /
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Bayesian data analysis in ecology using linear models withR, Bugs, and Stan
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Statistical learning with sparsity :the lasso and generalizations /
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Trends and perspectives in linear statistical inferenceproceedings of the LINSTAT2016 meeting held 22-25 August 2016 in Istanbul, Turkey /
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Linear models and time-series analysis :regression, ANOVA, ARMA and GARCH /
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Interaction effects in linear and generalized linear models :examples and applications using Stata /
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Effective statistical learning methods for actuaries.I,GLMs and extensions /
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Effective statistical learning methods for actuaries.III,Neural networks and extensions /
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Advanced linear modeling :statistical learning and dependent data /
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Effective statistical learning methods for actuaries IGLMs and extensions /
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The catalogue of computational material modelsbasic geometrically linear models in 1D /
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Applications of linear and nonlinear modelsfixed effects, random effects, and total least squares /
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Modeling correlated outcomes using extensions of generalized estimating equations and linear mixed modeling
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