Research any topic before you write.

Find related topics. | Discover entities. | See connections. | Build a topical map.

Local regression

Local regression or local polynomial regression, also known as moving regression, is a generalization of the moving average and polynomial regression. Its most common methods, initially developed for scatterplot smoothing, are LOESS (locally estimated scatterplot smoothing) and LOWESS (locally weighted scatterplot smoothing), both pronounced /ˈloʊɛs/…

History & Products

Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.

Research this topic

Explore the main themes, entities and connections around Local regression. Start with the topic map, then use the sections below for research and deeper semantic analysis.

Explore this topic

Start with a few of the strongest sections from the source topic. These are research directions, not a list of keywords you must use.

Topics to explore

Browse the full topic structure. Each item opens a new analysis centered on that subject.

Overview

History

Model definition

Selection issues: bandwidth, local model, fitting criteria

Disadvantages

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

Map overview Semantic statistics

Local regression

Nodes66
Edges65
Triples80
Avg. degree1.97
Density0.030303
Components1

How this topic connects Entity context

See the strongest relationship patterns around the current topic before diving into the raw triples.

Local regression

Top relations

related to External links · 22
Local regression → Friedman's SuperSmoother, How Opinion, Institute, Local, Local Polynomial Regression Fitting, LOESS, LOESSR, Lowess, Nate Silver, NIST Engineering Statistics Handbook, Quantile, RQuantile LOESS, RR, RThe, Same-Sex Marriage Is Changing, Scatter Plot Smoothing The, Section, Standards, Technology, The Loess
related to Further reading · 19
Local regression → Books, Brunsdon, Charlton, Data, Fan, Fotheringham, Geographically Weighted Regression, Gijbels, Its Applications, Katkovnik, Likelihood, Loader, Local Polynomial Modelling, Macaulay, Nonparametric Identification, Russian, Smoothing, The Smoothing, Time Series
related to history · 7
Local regression → Actuarial, An, Following Henderson, Henderson, Local, Robert Henderson, Specifically
related to Localized subsets of data; Bandwidth · 7
Local regression → Careful, Conversely, If, Mathematical, One, The, This
related to Matrix representation of the local regression estimate · 5
Local regression → As, This, Weighted, With, WX
related to Model definition · 5
Local regression → For, In, Local, Stronger, The
related to Choice of fitting criterion · 4
Local regression → As, These, This, Two
related to Selection issues: bandwidth, local model, fitting criteria · 2
Local regression → Implementation, The
is a · 1
Local regression → general term for the fitting procedure

Important terminology Word statistics

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

local regression displaystyle loess function data methods least squares estimate fitting lowess model used polynomial mu bandwidth criterion mean hat

Entity relationships Subject–Predicate–Object triples

SubjectPredicateObjectConfidenceSrc
Local regressionis ageneral term for the fitting procedure0.90text
cross-validation locally within the smoothing windowinstance ofby applying criteria0.80text
cross-validation can be used to compare the fits obtained with different degrees of polynomial.Weight functionAs mentioned aboveinstance ofmethods0.80text
the weight function gives the most weight to the data points nearest the point of estimationinstance ofmethods0.80text
the least weight to the data points that are furthest awayinstance ofmethods0.80text
iteratively reweighted least squares must be used to compute the estimate.Exampleinstance ofand iterative procedures0.80text
LOWESSinstance ofThis provides robustness to outliers and high-leverage points without the multiple robustness iterations used in methods0.80text
LOESSinstance ofThis provides robustness to outliers and high-leverage points without the multiple robustness iterations used in methods0.80text
cross-validation can be used to compare the fits obtained with different degrees of polynomialinstance ofmethods0.80text
Local regressionrelated to Choice of fitting criterionAs0.60section
Local regressionrelated to Choice of fitting criterionThis0.60section
Local regressionrelated to Choice of fitting criterionThese0.60section

Related concept clusters Concept neighborhoods

These clusters group vocabulary that occurs around closely connected concepts in the source material.

    Connections between topic areas Semantic bridges

    Bridges can reveal useful research angles that are easy to miss in a flat list of related terms.

    Min side: 3
    For writers, content strategists, SEOs, marketers and creators — from quick topic research to advanced semantic analysis.