- Referenced in 94 articles
- Forecasting functions for time series and linear models , Methods and tools for displaying and analysing...
- Referenced in 358 articles
- slip-interfaces; nonlinear material models such as J2 plasticity with linear, isotropic and kinematic hardening...
- Referenced in 65 articles
- Approach of linear mixed model in longitudinal data analysis using SAS. Linear mixed models ... longitudinal data sets. The analysis of linear mixed model methodology for the analysis of repeated ... summarizes the methodology of the linear mixed model approach for the analysis of repeated measurements...
- Referenced in 112 articles
- package nlme: Linear and Nonlinear Mixed Effects Models , Fit and compare Gaussian linear and nonlinear...
- Referenced in 242 articles
- scripts used in the book ”Generalized Additive Models: An Introduction with R”, Wood ... introduction to linear, generalized linear, generalized additive and mixed models. Moreover, the book contains explanations...
- Referenced in 74 articles
- estimation and analysis of linear and nonlinear models, with cross section, time series and panel ... manipulation of discrete and limited dependent variable models, LIMDEP 10 is now unsurpassed ... estimators for all forms of the linear regression model, and stochastic frontier, discrete choice ... single and multiple equation linear and nonlinear models. LIMDEP is a true state...
- Referenced in 80 articles
- package VGAM: Vector Generalized Linear and Additive Models , Vector generalized linear and additive models...
- Referenced in 48 articles
- limma: Linear Models for Microarray Data. A survey is given of differential expression analyses using ... linear modeling features of the limma package. The chapter starts with the simplest replicated designs ... control spots in conjunction with linear modelling is illustrated on the β7 data...
- Referenced in 72 articles
- problem of sparse selection in linear models. A number of nonconvex penalties have been proposed...
- Referenced in 77 articles
- Solving linear rational expectations models. We describe methods for solving general linear rational expectations models...
- Referenced in 66 articles
- Forecasting functions for time series and linear models Methods and tools for displaying and analysing...
- Referenced in 664 articles
- modeling system for constructing and solving disciplined convex programs (DCPs). CVX supports a number ... standard problem types, including linear and quadratic programs (LPs/QPs), second-order cone programs (SOCPs...
- Referenced in 171 articles
- delay. The performance of three published network models with very different spike patterns exhibits superlinear ... Gene, almost linear speedup was obtained up to 100 processors. Increasing one model from...
- Referenced in 121 articles
- Estimation and inference methods for models of conditional quantiles: Linear and nonlinear parametric...
- Referenced in 27 articles
- Bayesian and Likelihood Analysis of Dynamic Linear Models. Maximum likelihood, Kalman filtering and smoothing ... Space models, also known as Dynamic Linear Models. This book gives an introduction to statistical ... time series analysis by dynamic linear models. It covers the basic notions of dynamic linear ... estimation and forecasting in dynamic linear models with known parameters, and maximum likelihood estimation...
- Referenced in 33 articles
- package tgp: Bayesian treed Gaussian process models. Bayesian nonstationary, semiparametric nonlinear regression and design ... with jumps to the limiting linear model (LLM). Special cases also implemented include Bayesian linear ... models, CART, treed linear models, stationary separable and isotropic GPs, and GP single-index models...
- Referenced in 41 articles
- Hierarchical Linear and Nonlinear Modeling (HLM). In social research and other fields, research data often ... data requires specialized software. Hierarchical linear and nonlinear models (also called multilevel models) have been ... outcome variables that generate a linear model with explanatory variables that account for variations ... each level. HLM not only estimates model coefficients at each level, but it also predicts...
- Referenced in 27 articles
- GENMOD procedure fits generalized linear models, as defined by Nelder and Wedderburn (1972). The class ... generalized linear models is an extension of traditional linear models that allows the mean ... widely used statistical models are generalized linear models. These include classical linear models with normal ... models for binary data, and log-linear models for multinomial data. Many other useful statistical...
- Referenced in 221 articles
- Algorithm 866: IFISS, a Matlab toolbox for modelling incompressible flow. IFISS is a graphical Matlab ... discrete linear equation systems that arise in incompressible flow modelling. A unique feature...
- Referenced in 45 articles
- Summary statistics, two-sample tests, generalised linear models, cumulative link models, Cox models, loglinear models...