###### **Linear** **model**

General

**linear****model**Generalized**linear****model****Linear**system Statistical**model**Priestley, M.B. (1988) Non-**linear**and Non- ... An example of a**linear**time series**model**is an autoregressive moving average**model**. Here the**model**for values {Xt} in a time ... Note that here the "**linear**" part of the term "**linear****model**" is not referring to the coefficients φi and θi, as it would be in ... "**linear****model**" refers to the structure of the above relationship in representing Xt as a**linear**function of past values of the ...###### General **linear** **model**

The general

**linear****model**or multivariate regression**model**is a statistical**linear****model**. It may be written as Y = X B + U , {\ ... ordinary**linear**regression, t-test and F-test. The general**linear****model**is a generalization of multiple**linear**regression**model**... generalized**linear****models**may be used to relax assumptions about Y and U. The general**linear****model**incorporates a number of ... Bayesian multivariate**linear**regression Comparison of general and generalized**linear****models**K. V. Mardia, J. T. Kent and J. M. ...###### Generalized **linear** **model**

... two broad statistical

**models**. The general**linear****model**may be viewed as a special case of the generalized**linear****model**with ... very important example of a generalized**linear****model**(also an example of a general**linear****model**) is**linear**regression. In ... Such a**model**is a log-odds or logistic**model**. Generalized**linear****models**cover all these situations by allowing for response ... The term "generalized**linear****model**", and especially its abbreviation GLM, are sometimes confused with general**linear****model**. Co- ...###### Log-**linear** **model**

Log-

**linear**analysis General**linear****model**Generalized**linear****model**Boltzmann distribution. ... A log-**linear****model**is a mathematical**model**that takes the form of a function whose logarithm equals a**linear**combination of the ... Poisson regression for contingency tables, a type of generalized**linear****model**. The specific applications of log-**linear****models**... while c and the wi stand for the**model**parameters. The term may specifically be used for: A log-**linear**plot or graph, which is ...###### Proper **linear** **model**

In statistics, a proper

**linear****model**is a**linear**regression**model**in which the weights given to the predictor variables are ... Unit-weighted regression is the most common example of an improper**linear****model**. Dawes, R. M. (1979). "The robust beauty of ... Simple regression analysis is the most common example of a proper**linear****model**. ... improper**linear****models**in decision making". American Psychologist. 34 (7): 571-582. doi:10.1037/0003-066X.34.7.571. ...###### Hierarchical generalized **linear** **model**

Moreover, the generalized

**linear**mixed**model**(GLMM) is a special case of the hierarchical generalized**linear****model**. In ... There are different techniques to fit a hierarchical generalized**linear****model**. Hierarchical generalized**linear****model**have been ... In statistics, hierarchical generalized**linear****models**(HGLM) extend generalized**linear****models**by relaxing the assumption that ... then we call the**model**Beta conjugate**model**. Moreover, the mixed**linear****model**is in fact the normal conjugate HGLM. A summary ...###### Vector generalized **linear** **model**

For example, in discrete choice

**models**, one has conditional logit**models**, nested logit**models**, generalized logit**models**, and ... In statistics, the class of vector generalized**linear****models**(VGLMs) was proposed to enlarge the scope of**models**catered for by ... and include 3 of the most important statistical regression**models**: the**linear****model**, Poisson regression for counts, and ... therefore this**model**is also called the cumulative probit**model**. In general they are called cumulative link**models**. For ...###### **Linear** **model** of innovation

The

**Linear****Model**of Innovation is an early**model**of innovation that suggests technical change happens in a**linear**fashion from ... The**linear****models**of innovation supported numerous criticisms concerning the linearity of the**models**. These**models**ignore the ... Two versions of the**linear****model**of innovation are often presented: "technology push"**model**"market pull"**model**. From the 1950s ... A history of the**linear****model**of innovation may be found in Godin (2006) Innovation Technological change Science and technology ...###### Generalized functional **linear** **model**

The generalized functional

**linear****model**(GFLM) is an extension of the generalized**linear****model**(GLM) that allows one to regress ... Functional additive**models**Functional data analysis Functional principal component analysis Generalized**linear****model**Karhunen- ... James (2002). "Generalized**linear****models**with functional predictors". Journal of the Royal Statistical Society, Series B. 64 (3 ... truncated**model**i.e. the**linear**predictor trunctated to the summation of the first p {\displaystyle p} components, is a ...###### Comparison of general and generalized **linear** **models**

McCullagh, Peter; Nelder, John (1989). Generalized

**Linear****Models**, Second Edition. Boca Raton: Chapman and Hall/CRC. ISBN 0-412- ... McCullagh, Peter; Nelder, John (1989). Generalized**Linear****Models**, Second Edition. Boca Raton: Chapman and Hall/CRC. ISBN 0-412- ...###### **Linear** probability **model**

... "

**linear**probability**model**", this relationship is a particularly simple one, and allows the**model**to be fitted by simple**linear**... In statistics, a**linear**probability**model**is a special case of a binomial regression**model**. Here the dependent variable for ...**models**such as the logit**model**or the probit**model**are more commonly used. Cox, D. R. (1970). "Simple Regression". Analysis of ... ISBN 0-631-13345-3. Wooldridge, Jeffrey M. (2013). "A Binary Dependent Variable: The**Linear**Probability**Model**". Introductory ...###### Generalized **linear** array **model**

Such

**models**provide a structure and a computational procedure for fitting generalized**linear****models**or GLMs whose**model**matrix ... It based on the generalized**linear****model**with the design matrix written as a Kronecker product. The generalized**linear**array ... Currie, I. D.; Durban, M.; Eilers, P. H. C. (2006). "Generalized**linear**array**models**with applications to multidimensional ... In statistics, the generalized**linear**array**model**(GLAM) is used for analyzing data sets with array structures. ...###### **Linear** transform **model** (MRI)

The

**linear**transform**model**is a common and widespread assumption used in the interpretation of fMRI studies. However, some ... The**linear**transform**model**refers to a fundamental assumption guiding the analysis of functional Magnetic Resonance Imaging ( ... Specifically, the**model**holds that the fMRI signal is approximately proportional to a measure of local neural activity, ...###### Generalized **linear** mixed **model**

Generalized

**Linear**Mixed**Models**, CRC Press Jiang, J. (2007),**Linear**and Generalized**Linear**Mixed**Models**and Their Applications ... a generalized**linear**mixed**model**(GLMM) is an extension to the generalized**linear****model**(GLM) in which the**linear**predictor ... They also inherit from GLMs the idea of extending**linear**mixed**models**to non-normal data. GLMMs provide a broad range of**models**... to fit GLMM**models**. Generalized estimating equation Hierarchical generalized**linear****model**Breslow, N. E.; Clayton, D. G. (1993 ...###### Standard **linear** solid **model**

The standard

**linear**solid (SLS)**model**, also known as the Zener**model**, is a method of**modeling**the behavior of a viscoelastic ... Often, the simpler Maxwell**model**and the Kelvin-Voigt**model**are used. These**models**often prove insufficient, however; the ... The standard**linear**solid**model**combines aspects of the Maxwell and Kelvin-Voigt**models**to accurately describe the overall ... SLS is the simplest**model**that predicts both phenomena. Materials undergoing strain are often**modeled**with mechanical ...###### Non-**linear** sigma **model**

Sigma

**model**Chiral**model**Little Higgs Skyrmion, a soliton in non-**linear**sigma**models**WZW**model**Fubini-Study metric, a metric ... The non-**linear**σ-**model**was introduced by Gell-Mann & Lévy (1960, section 6), who named it after a field corresponding to a ... A nonlinear σ**model**with G/H as the target manifold with a G-invariant Riemannian metric and a zero potential is called a ... These are**modelled**as R^2 with a point at infinity, and hence have the same topology as the O(3) instantons in 1+1 dimensions. ...###### **Linear** no-threshold **model**

The

**linear**no-threshold**model**(LNT) is a**model**used in radiation protection to quantify radiation exposure and set regulatory ... The**linear**-no-threshold**model**was first expressed by John Gofman, and rejected by the Department of Energy, according to Gofman ... The**linear**no-threshold**model**is used to extrapolate the expected number of extra deaths caused by exposure to environmental ... A**linear****model**has long been used in health physics to set maximum acceptable radiation exposures. The United States-based ...###### Standard **linear** solid Q **model** for attenuation and dispersion

Ursin and Toverud compared different Q

**models**including the above**model**(SLS-**model**). In order to compare the different**models**... A standard**linear**solid Q**model**(SLS) for attenuation and dispersion is one of many mathematical Q**models**that gives a ... This**model**was compared with the Kolsky-Futterman**model**. The Kolsky-Futterman**model**was first described in the article ' ... The standard**linear**solid**model**is developed from the stress-strain relation. Using a**linear**combination of springs and ...###### **Linear**-nonlinear-Poisson cascade **model**

The

**linear**-nonlinear-Poisson (LNP) cascade**model**is a simplified functional**model**of neural spike responses. It has been ... There are three stages of the LNP cascade**model**. The first stage consists of a**linear**filter, or**linear**receptive field, which ... If the nonlinearity f {\displaystyle f} is a fixed invertible function, then the LNP**model**is a generalized**linear****model**. In ... the**linear**stage of the LNP**model**can be generalized to a bank of**linear**filters, and the nonlinearity becomes a function of ...###### Regression toward the mean

In other words, if

**linear**regression is the appropriate**model**for a set of data points whose sample correlation coefficient is ... such a line that minimizes the sum of squared residuals of the**linear**regression**model**. In other words, numbers α and β solve ...**Linear****models**". Modern Mathematical Statistics. John Wiley & Sons. ISBN 978-0-471-81472-6. Francis Galton (1886). "Regression ... He quantified this trend, and in doing so invented**linear**regression analysis, thus laying the groundwork for much of modern ...###### Rosemary A. Bailey

She has written books on the design of experiments, on association schemes, and on

**linear****models**in statistics. She is ... Bailey, R. A. (1994). Normal**linear****models**. London: External Advisory Service, University of London. ISBN 0-7187-1176-9. Bailey ... ISBN 978-0-521-68357-9. Speed, T. P.; Bailey, R. A. (1987). "Factorial Dispersion**Models**". International Statistical Review / ...###### Houdini (software)

Houdini covers all the major areas of 3D production, including these:

**Modeling**- All standard geometry entities including ... it enables and encourages non-**linear**development; and new operators can be created in terms of existing operators, a flexible ... a technique which attempts to more accurately**model**the interactions of light. Derivative Inc. is a spin-off of Side Effects ... for procedural**modelling**. POPs - particle operators - used to manipulate particles systems. CHOPs - channel operators - for ...###### John Nelder

In statistical theory, Nelder and Wedderburn proposed the generalized

**linear****model**. Generalized**linear****models**were formulated ... "Generalized**Linear****Models**", J. R. Statist. Soc. A, 135 (1972) 370-384. McCullagh, P. and J.A. Nelder. 1989. Generalized**Linear**... "for their monograph Generalized**Linear****Models**(1983)". As tribute on his eightieth birthday, a festschrift Methods and**Models**... Generalized**Linear****Models**with Random Effects: Unified Analysis via H-likelihood. Chapman & Hall/CRC, Boca Raton, Florida. ISBN ...