Log-linear analysis is a technique used in statistics to examine the relationship between more than two categorical variables. The technique is used for...

A log-linear model is a mathematical model that takes the form of a function whose logarithm equals a linear combination of the parameters of the model...

Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant...

median or some other quantile is used. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of the...

Local regression Log-Cauchy distribution Log-Laplace distribution Log-normal distribution Log-linear analysis Log-linear model Log-linear modeling – redirects...

The most common form of regression analysis is linear regression, in which one finds the line (or a more complex linear combination) that most closely fits...

k log ⁡ x + log ⁡ a . {\displaystyle \log y=k\log x+\log a.} Setting X = log ⁡ x {\displaystyle X=\log x} and Y = log ⁡ y , {\displaystyle Y=\log y,}...

theorem Hopfield network Interacting particle system Ising model Log-linear analysis Markov chain Markov logic network Maximum entropy method Stochastic...

model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression (or...

log(μ) be a linear model. This produces the "cloglog" transformation log ⁡ ( − log ⁡ ( 1 − p ) ) = log ⁡ ( μ ) . {\displaystyle \log(-\log(1-p))=\log(\mu...

Feature selection Freedman's paradox Grid search Identifiability Analysis Log-linear analysis Model identification Occam's razor Optimal design Parameter identification...

The general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models...

In statistics, Poisson regression is a generalized linear model form of regression analysis used to model count data and contingency tables. Poisson regression...

Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...

in log probability. Similar to multiplication operations in linear-scale becoming simple additions in log-scale, an addition operation in linear-scale...

Bayesian linear regression is a type of conditional modeling in which the mean of one variable is described by a linear combination of other variables...

simple linear regression). Bivariate analysis can be contrasted with univariate analysis in which only one variable is analysed. Like univariate analysis, bivariate...

effect, and "a large number of cases could be coded and subjected to log-linear analysis to identify patterns." (Coombs, 2006, p. 191-192) Coca-Cola and Pepsi's...

In computer science, the analysis of algorithms is the process of finding the computational complexity of algorithms—the amount of time, storage, or other...

Laird and Donald Olivier (1981). "Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques". Journal of the American Statistical...

pp. 1855–1863. Petitjean F, Webb GI, Nicholson AE (2013). Scaling log-linear analysis to high-dimensional data (PDF). International Conference on Data...

results. Common methods include Linear Analysis, Semi-log Analysis and Log-Log Analysis The Linear Method is the analysis of the function N(r), where N...

extended to survival estimation. The DeepSurv model proposes to replace the log-linear parameterization of the CoxPH model with a multi-layer perceptron. Further...

Non-linear least squares is the form of least squares analysis used to fit a set of m observations with a model that is non-linear in n unknown parameters...

standard HyperLogLog estimator E {\textstyle E} above. Otherwise, use Linear Counting: E ⋆ = m log ⁡ ( m V ) {\textstyle E^{\star }=m\log \left({\frac...

quasilinear time (also referred to as log-linear time) if T ( n ) = O ( n log k ⁡ n ) {\displaystyle T(n)=O(n\log ^{k}n)} for some positive constant k;...

function. Popular loss functions include the hinge loss (for linear SVMs) and the log loss (for linear logistic regression). If the regularization function R...

leadership (e.g., cross-tabulations, ANOVAs, regression analysis, log-linear analysis, factor analysis, etc.). From a qualitative orientation, leadership research...

Analysis of covariance (ANCOVA) is a general linear model that blends ANOVA and regression. ANCOVA evaluates whether the means of a dependent variable...

Explained variation Linear trend estimation Mixed-design analysis of variance Multivariate analysis of covariance (MANCOVA) Permutational analysis of variance...