Linear models (Statistics)
Partially linear models
... partially linear models in the framework of in- dependent ...partially linear time series models and establish asymptotic results as well as small sample ...
216
Application of Hierarchical Linear Models/Linear Mixed effects Models in School Effectiveness Research
... data. They are the extension of linear models. The application of multilevel analysis for educational hierarchical data has several advantages. First, it enables the researchers to obtain statistically ...
8
glm-ie: Generalised Linear Models Inference & Estimation Toolbox
... Generalised Linear Models (GLMs) are a widely used class of probabilistic graphical models over continuous variables allowing a unified treatment of linear, logistic and Poisson regression and ...
5
Fitting Models of Vulnerability to Toxicity with Generalized Linear Models
... Generalized Linear Models (GLM) of it can be fitted using our proposed ...identify models in GLM that can be used to study toxicity when it is ‘captured’ as count data or Binary Response Variables ...
12
Generalised linear models
... Generalized Linear Models entered the ecological statisticians toolkit with the publication of McCullagh and Nelder’s landmark book in 1989 (McCullagh and Nelder 1989) and slowly gained in popularity among ...
19
Covariance Structures of Linear Models
... Young, Scariano, and Hallum (2005) study two univariate linear regression models, and establish a certain condition for the variances estimates to be equal; however, the condition is in error. They then ...
8
Cross-Validation Optimization for Large Scale Structured Classification Kernel Methods
... generalized linear models in statistics, and that such methods are also routinely used for Gaussian process models (Williams and Barber, 1998; Rasmussen and Williams, 2006), albeit typically ...
32
A Brief Digest on Reproducing Kernel Hilbert Space
... Abstract. Reproducing Kernel Hilbert Space (RKHS) is a common used tool in statistics and machine learning to generalize from linear models to non-linear models. In this paper we will ...
5
Generalized linear models
... As Birch (1963) has shown, the estimation of a set of independent multinomial distributions is equivalent to the estimation of a set of independent Poisson distributions, and in[r] ...
16
On a Class of Probability Distributions With Application Using Rainfall Data of Kashmir Valley Bilal Ahmad Bhat 1, N. A. Rather2 , T. A. Rather 3
... Statistical models describe a phenomenon in the form of mathematical ...statistical models are the latest ...of models e.g., Linear models, Non- linear models, Generalized ...
7
Statistical Modeling for Rice Production in Pakistan
... in Linear and Non-Linear models. Among all the models cubic was found to be best fitted model for rice production in Pakistan as it has exhibited highest Theil’s U-Statistic (model accuracy), ...
7
Dimensionality Reduction via Sparse Support Vector Machines (Kernel Machines Section)
... Generalized Linear Models (GLM) (Miller, ...GLM models were also bagged. Hence 20 different GLM models were generated using Splus 2000 (Venables and Ripley, 1994, McCullagh and Nelder, 1983) ...
15
Tanoak (Notholithocarpus densiflorus) Coarse Root Morphology: Prediction Models for Volume and Biomass of Individual Roots
... taper models were tested with taper rate expressed as the decrease in root diameter, cross-sectional area, or circumference cm −1 of length, expressed as a ...A linear mixed model of taper was used to test ...
13
All Models are Wrong, but Many are Useful: Learning a Variable's Importance by Studying an Entire Class of Prediction Models Simultaneously
... well-fitting models. This set of well-fitting models is identified by repeating an estimation procedure in a series of perturbed samples, using varying levels of regularization (see also Azen et ...systems ...
81
Operationalising ‘safe statistics’: The case of linear regression
... 'safe/unsafe statistics' (Ritchie, 2007 and ...safe statistics has significant resource implications for the researcher and the facility owner, and has proved its effectiveness in a number of settings; ...
12
Three Essays on Risks of Natural Disasters in the U.S. Forest Sector.
... In our analysis, the unit of observation is a county. This choice is dictated by our available data, though the analytical approach is general to any geographic or temporal unit of observation for which suitable data ...
145
Effect of Linear and Non-Linear IVIVC Models on In- Vivo Predictions
... are linear at this level. Although a concern of acceptable non-linear correlation has been addressed, no formal guidance on the non-linear IVIVC has been ...
6
Robust identification for linear in the parameters models
... of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with ...
6
Tree volume and increment models for radiata pine thinnings
... The data to be used in the development of the models had to be extracted from measurements of permanent sample plots. These data are currently held in manilla folders, one for field use and one for office use. The ...
203
Vol 10, No 6 (2019)
... Partially linear model (PLM) is one of the most commonly used semi-parametric regression models, which offers an appealing alternative in that it allows both parametric and nonparametric specifications in ...
9