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Everything about Linear predictor function
Linear function of explanatory variables used to predict a dependent variable
In statistics and in machine learning, a linear predictor function is a linear function of a set of coefficients and explanatory variables, whose value is used to predict the outcome of a dependent variable. This sort of function usually comes in linear regression, where the coefficients are called regression coefficients. However, they also occur in various types of linear classifiers, as well as in various other models, such as principal component analysis and factor analysis. In many of these models, the coefficients are referred to as "weights". Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Linear predictor functionA 5-minute orientation
- Skim a recent paper: Generalized functional linear model with a point process predictorInfluential work since 2022
- Pick up a classic book: The Elements of Statistical LearningThe most-reprinted book on the subject
- Read the landmark paper: A Predictor-Corrector Algorithm for Linear Optimization Based on a Specific Self-Regular Proximity FunctionCited 20 times
- Go sideways: Logistic regressionA closely related topic
- Go sideways: Ordinary least squaresA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
A Predictor-Corrector Algorithm for Linear Optimization Based on a Specific Self-Regular Proximity Function
Nonlinear function on function additive model with multiple predictor curves
Multicollinearity and Linear Predictor Link Function Problems in Regression Modelling of Longitudinal Data
A Predictor-Corrector Interior-Point Algorithm Using A Special Power Function for $P_*(\kappa)-$weighted Horizontal Linear
A Predictor-Corrector Algorithm for P ∗(κ)-Linear Complementarity Problems Based on a Specific Self-Regular Proximity Function
🆕 Influential since 2022
Generalized functional linear model with a point process predictor
Functional partial linear regression with quadratic regression for the multivariate predictor
Low-rank modeling for functional linear regression with two-way functional predictor
A novel corrector–predictor interior-point algorithm for P * (κ)-weighted linear complementarity problems based on an AET function
📚 Books worth reading
The Elements of Statistical LearningTrevor Hastie, Robert Tibshirani · 2001
Introduction to Probability and StatisticsJ. Susan Milton, Jesse C. Arnold · 1990
Introduction to Multiple Time Series AnalysisHelmut Lütkepohl, Helmut Lutkepohl · 1991
Stochastic processesM. M. Rao · 1995
Staffing organizationsRobert E. Ployhart, Benjamin Schneider · 2005
Empirical LikelihoodArt B. Owen · 2001
Minimax linear predictor under Lipschitz' type conditions for the regression functionKei Takeuchi · 1968- 📕Minimax Linear Predictor under Lipschitz' Type Conditions for the Regression FunctionKei Takeuchi · 2018
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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