#
Linear models (Statistics)
Resource Information
The concept ** Linear models (Statistics)** represents the subject, aboutness, idea or notion of resources found in **University of Oklahoma Libraries**.

The Resource
Linear models (Statistics)
Resource Information

The concept

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

## Context

Context of Linear models (Statistics)#### Subject of

- A course in linear models
- A first course in linear model theory
- A primer on linear models
- ANOVA and ANCOVA : a GLM approach
- Advanced linear modeling : multivariate, time series, and spatial data; nonparametric regression and response surface maximization
- Advanced linear models : theory and applications
- Advances in growth curve models : topics from the Indian Statistical Institute
- Almost linearly optimum combination of unbiased estimates
- An R companion to linear statistical models
- An introduction to generalized linear models
- An introduction to generalized linear models
- Applied linear models with SAS
- Applied linear statistical models
- Applying generalized linear models
- Applying generalized linear models
- Assessing the use of the Akaike information criterion for generalized linear mixed models
- Bayesian analysis of linear models
- Bayesian forecasting and dynamic models
- Bayesian forecasting and dynamic models
- Comparison of regression models for ordinal outcome data
- Conditional and unconditional conservatism : implications for accounting based valuation and risky projects
- Design of experiments : an introduction based on linear models
- Dynamic linear models with R
- Economic data : handle with care
- Essays in linear economic structures
- Experimental design, statistical models, and genetic statistics : essays in honor of Oscar Kempthorne
- Flexible regression and smoothing : using GAMLSS in R
- Foundations of linear and generalized linear 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 Bayesian perspective
- Generalized linear models : an applied approach
- Generalized linear models : with applications in engineering and the sciences
- Generalized linear models : with applications in engineering and the sciences
- Generalized linear models and extensions
- Generalized linear models for categorical and continuous limited dependent variables
- Generalized linear models for insurance data
- Generalized linear models with random effects : unified analysis via h-likelihood
- Generalized linear models with random effects : unified analysis via h-likelihood
- Generalized, linear, and mixed models
- Generalized, linear, and mixed models
- Growth curve models and statistical diagnostics
- Habitat suitability and distribution models : with applications in R
- Hierarchical linear modeling : guide and applications
- Hierarchical linear models : applications and data analysis methods
- Hierarchical linear models : applications and data analysis methods
- Higher-order growth curves and mixture modeling with Mplus : a practical guide
- Hypothesis identification in the case of the missing cell
- Impact of magnetic isolation on pointing system performance in the presence of structural flexibility
- Interpreting probability models : logit, probit, and other generalized linear models
- Introduction to general and generalized linear models
- Introduction to linear models
- Introduction to the statistical analysis of categorical data
- Introduction to the statistical analysis of categorical data
- 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 algebra and linear models
- Linear and generalized linear mixed models and their applications
- Linear and graphical models : for the multivariate complex normal distribution
- Linear mixed models for longitudinal data
- Linear mixed models for longitudinal data
- Linear mixed-effects models using R : a step-by-step approach
- Linear model theory : univariate, multivariate, and mixed models
- Linear models : a mean model approach
- Linear models : an integrated approach
- Linear models : an introduction
- Linear models : least squares and alternatives
- Linear models : least squares and alternatives
- Linear models : least squares and alternatives
- Linear models : the theory and application of analysis of variance
- Linear models and generalizations : least squares and alternatives
- Linear models for multivariate, time series, and spatial data
- Linear models in statistics
- Linear models in the mathematics of uncertainty
- Linear models of optimal test design
- Linear models with correlated disturbances
- Linear statistical models
- Linear statistical models
- Linear statistical models
- Linear statistical models : an applied approach
- Linearization models for complex dynamical systems : topics in univalent functions, functional equations and semigroup theory
- Linearization models for complex dynamical systems : topics in univalent functions, functional equations and semigroup theory
- Matrices with applications in statistics
- Matrix algebra for linear models
- Matrix algebra from a statistician's perspective
- Matrix tricks for linear statistical models : our personal top twenty
- Maximum likelihood estimation of restricted parameters
- Methods and applications of linear models : regression and the analysis of variance
- Modeling a very rare event to estimate sea turtle bycatch : lessons learned
- Modelling binary data
- 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
- Nonlinear regression
- Nonlinear regression analysis and its applications
- Nonparametric methods in general linear models
- On the distribution of linear functions and ratios of linear functions of ordered correlated normal random variables with emphasis on range
- Parameter estimation and hypothesis testing in linear models
- Partially linear models
- Plane answers to complex questions : the theory of linear models
- Plane answers to complex questions : the theory of linear models
- Plane answers to complex questions : the theory of linear models
- Recent advances in linear models and related areas
- Regression modeling strategies : with applications to linear models, logistic regression, and survival analysis
- Semialgebraic statistics and latent tree models
- Sign-based methods in linear statistical models
- Statistical learning with sparsity : the lasso and generalizations
- Statistical modelling and regression structures : festschrift in honour of Ludwig Fahrmeir
- Statistical modelling in GLIM 4
- Statistical models : theory and practice
- Statistical tests for mixed linear models
- Testing the compatibility of a priori constraints on the generalized linear model with sample information
- The Coordinate-Free Approach to Linear Models
- The analysis of categorical data using GLIM
- The analysis of linear models
- The coordinate-free approach to linear models
- The linear model and hypothesis : a general unifying theory
- The microcomputer scientific software series 2 : general linear model, regression
- The microcomputer scientific software series 3 : general linear model, analysis of variance
- The microcomputer scientific software series 4 : testing prediction accuracy
- The statistical analysis of categorical data
- The theory of dispersion models
- The theory of linear models and multivariate analysis
- Using HLM and NAEP data to explore school correlates of 1990 mathematics and geometry achievement in grades 4, 8, and 12 : methodology and results
- Vector generalized linear and additive models : with an implementation in R
- Weighted empirical processes in dynamic nonlinear models
- Weighted empirical processes in dynamic nonlinear models
- 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.libraries.ou.edu/resource/wbRmsoCMNFc/" typeof="CategoryCode http://bibfra.me/vocab/lite/Concept"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.libraries.ou.edu/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.libraries.ou.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.libraries.ou.edu/">University of Oklahoma Libraries</a></span></span></span></span></div>`