However, the term is also used in time series analysis with a different meaning. In each case, the designation "linear" is used to identify a subclass of models for which substantial reduction in the complexity of the related statistical theory is possible. For the regression case, the statistical model is as follows. Alternatively, one may say that the predicted values corresponding to the above model, namely.

An example of a linear time series model is an autoregressive moving average model. In this instance the use of the term "linear model" refers to the structure of the above relationship in representing X t as a linear function of past values of the same time series and of current and past values of the innovations.

There are some other instances where "nonlinear model" is used to contrast with a linearly structured model, although the term "linear model" is not usually applied. One example of this is nonlinear dimensionality reduction. From Wikipedia, the free encyclopedia.

## Linear model - Wikipedia

Not to be confused with linear model of innovation. Main article: Linear regression. Outline Index. Descriptive statistics. Mean arithmetic geometric harmonic Median Mode. Not to be confused with linear model of innovation.

Main article: Linear regression. Outline Index. Descriptive statistics.

## Linear regression

Mean arithmetic geometric harmonic Median Mode. Central limit theorem Moments Skewness Kurtosis L-moments. Index of dispersion. Grouped data Frequency distribution Contingency table. Pearson product-moment correlation Rank correlation Spearman's rho Kendall's tau Partial correlation Scatter plot. Data collection. Sampling stratified cluster Standard error Opinion poll Questionnaire. Scientific control Randomized experiment Randomized controlled trial Random assignment Blocking Interaction Factorial experiment.

Adaptive clinical trial Up-and-Down Designs Stochastic approximation. Cross-sectional study Cohort study Natural experiment Quasi-experiment. Download preview PDF. Skip to main content.

Advertisement Hide. A mixture likelihood approach for generalized linear models. This is a preview of subscription content, log in to check access.

### Linear Model Methodology by AndrĂ© I. Khuri

Google Scholar. BAWA, K. BERK, R. DAY, N. HOPE, A.