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Linear models (Statistics)
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The concept ** Linear models (Statistics)** represents the subject, aboutness, idea or notion of resources found in **University of Liverpool**.

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Linear models (Statistics)
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**Linear models (Statistics)**represents the subject, aboutness, idea or notion of resources found in**University of Liverpool**.- Label
- Linear models (Statistics)

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- 2-Inverses and their statistical application
- A beginner's guide to generalized additive models with R
- A course in linear models
- A first course in linear model theory
- A unified theory of estimation and inference for nonlinear dynamic models
- ANOVA and ANCOVA : a GLM approach
- ANOVA and ANCOVA : a GLM approach
- Advanced linear modeling : statistical learning and dependent data
- Advanced linear models : theory and applications
- Advances in growth curve models : topics from the Indian Statistical Institute
- An introduction to generalized linear models
- An introduction to generalized linear models
- An introduction to generalized linear models
- An introduction to generalized linear models
- Applied linear models with SAS
- Applied linear statistical models: regression, analysis of variance, and experimental designs
- Applied regression analysis and generalized linear models
- Applying generalized linear models
- Bayesian analysis of linear models
- Bayesian forecasting and dynamic models
- Beginner's guide to spatial, temporal, and spatial-temporal ecological data analysis with R-INLA , Volume I, Using GLM and GLMM
- Blind deconvolution : theory, regularization and applications
- Conditional and unconditional conservatism : implications for accounting based valuation and risky projects
- Design of experiments : an introduction based on linear models
- Distributions for modelling location, scale, and shape : using GAMLSS in R
- Dynamic linear models with R
- Flexible regression and smoothing : using GAMLSS in R
- Foundations of linear and generalized linear models
- Generalized additive models
- Generalized additive models
- Generalized additive models : an introduction with R
- Generalized linear mixed models : modern concepts, methods and applications
- Generalized linear models
- Generalized linear models
- Generalized linear models : a unified approach
- Generalized linear models : with applications in engineering and the sciences
- Generalized linear models for insurance data
- Generalized linear models with examples in R
- Habitat suitability and distribution models : with applications in R
- Handbook of nonlinear regression models
- Hierarchical linear modeling : guide and applications
- Hierarchical linear models : applications and data analysis methods
- Higher-order growth curves and mixture modeling with Mplus : a practical guide
- Interpreting probability models : logit, probit and other generalized linear models
- Interpreting probablity models: logit, probit, and other generalized linear models
- Introduction to general and generalized linear models
- Introduction to linear models
- Introduction to statistical modelling
- Introduction to statistical modelling
- L1-norm and L[infinity symbol]-norm estimation : an introduction to the least absolute residuals, the minimax absolute residual and related fitting procedures
- Linear algebra and linear models
- Linear and generalized linear mixed models and their applications
- Linear mixed-effects models using R : a step-by-step approach
- Linear models
- Linear models
- Linear models : a mean model approach
- Linear models : an integrated approach
- Linear models and generalizations : least squares and alternatives
- Linear models for optimal test design
- Linear models for unbalanced data
- Linear models in the mathematics of uncertainty
- Linear models of optimal test design
- Linear models: least squares and alternative methods
- Linear statistical models and related methods: with applications to social research
- Linearization models for complex dynamical systems : topics in univalent functions, functional equations and semigroup theory
- Matrix algebra for linear models
- Matrix algebra from a statistician's perspective
- Matrix tricks for linear statistical models : our personal top twenty
- Methods and applications of linear models : regression and the analysis of variance
- Modeling count data
- Modelling binary data
- Modelling survival data in medical research
- Modello Lineare : Teoria e Applicazioni con R
- Multilevel and longitudinal modeling using Stata
- Multilevel and longitudinal modeling using Stata
- Multilevel modelling of health statistics
- Multivariate models and dependence concepts
- Multivariate statistical modelling based on generalized linear models
- Multivariate time series with linear state space structure
- Non-life insurance pricing with generalized linear models
- Nonlinear regression
- Parameter estimation and hypothesis testing in linear models
- Plane answers to complex questions : the theory of linear models
- Plane answers to complex questions : the theory of linear models
- Power estimation on electronic system level using linear power models
- Prior information in linear models
- Recent advances in linear models and related areas
- Regression analysis : statistical modeling of a response variable
- Regression modeling strategies : with applications to linear models, logistic regression, and survival analysis
- Statistical analysis of categorical data
- Statistical methods for overdispersed count data
- Statistical modelling and regression structures : festschrift in honour of Ludwig Fahrmeir
- Statistical models : theory and practice
- Statistical models and causal inference : a dialogue with the social sciences
- Statistics for high-dimensional data : methods, theory and applications
- Statistics for high-dimensional data : methods, theory and applications
- The coordinate-free approach to linear models
- The linear model and hypothesis : a general unifying theory
- The theory of linear models and multivariate analysis
- Theoretical foundations of functional data analysis, with an introduction to linear operations
- Vector generalized linear and additive models : with an implementation in R
- Weighted empiricals and linear models

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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/resource/wbRmsoCMNFc/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/resource/wbRmsoCMNFc/">Linear models (Statistics)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>

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`<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.liverpool.ac.uk/resource/wbRmsoCMNFc/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.liverpool.ac.uk/resource/wbRmsoCMNFc/">Linear models (Statistics)</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.liverpool.ac.uk/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.liverpool.ac.uk/">University of Liverpool</a></span></span></span></span></div>`