Skip to content

Explore Courses | Elder Research | Contact | LMS Login

Statistics.com
  • Curriculum
    • Curriculum
    • About Us
    • Testimonials
    • Management Team
    • Faculty Search
    • Teach With Us
    • Credit & Credentialing
  • Courses
    • Explore Courses
    • Course Calendar
    • About Our Courses
    • Course Tour
    • Test Yourself!
  • Mastery Series
    • Mastery Series Program
    • Bayesian Statistics
    • Business Analytics
    • Healthcare Analytics
    • Marketing Analytics
    • Operations Research
    • Predictive Analytics
    • Python for Analytics
    • R Programming
    • Rasch & IRT
    • Spatial Statistics
    • Statistical Modeling
    • Survey Statistics
    • Text Mining and Analytics
  • Certificates
    • Certificate Program
    • Analytics for Data Science
    • Biostatistics
    • Programming for Data Science – R (Novice)
    • Programming for Data Science – R (Experienced)
    • Programming for Data Science – Python (Novice)
    • Programming for Data Science – Python (Experienced)
    • Social Science
  • Degrees
    • Degree Programs
    • Computational Data Analytics Certificate of Graduate Study from Rowan University
    • Health Data Management Certificate of Graduate Study from Rowan University
    • Data Science Analytics Master’s Degree from Thomas Edison State University (TESU)
    • Data Science Analytics Bachelor’s Degree – TESU
    • Mathematics with Predictive Modeling Emphasis BS from Bellevue University
  • Enterprise
    • Organizations
    • Higher Education
  • Resources
    • Blog
    • FAQs & Knowledge Base
    • Glossary
    • Site Map
    • Statistical Symbols
    • Weekly Brief Newsletter Signup
    • Word of the Week
Menu Close
  • Curriculum
    • Curriculum
    • About Us
    • Testimonials
    • Management Team
    • Faculty Search
    • Teach With Us
    • Credit & Credentialing
  • Courses
    • Explore Courses
    • Course Calendar
    • About Our Courses
    • Course Tour
    • Test Yourself!
  • Mastery Series
    • Mastery Series Program
    • Bayesian Statistics
    • Business Analytics
    • Healthcare Analytics
    • Marketing Analytics
    • Operations Research
    • Predictive Analytics
    • Python for Analytics
    • R Programming
    • Rasch & IRT
    • Spatial Statistics
    • Statistical Modeling
    • Survey Statistics
    • Text Mining and Analytics
  • Certificates
    • Certificate Program
    • Analytics for Data Science
    • Biostatistics
    • Programming for Data Science – R (Novice)
    • Programming for Data Science – R (Experienced)
    • Programming for Data Science – Python (Novice)
    • Programming for Data Science – Python (Experienced)
    • Social Science
  • Degrees
    • Degree Programs
    • Computational Data Analytics Certificate of Graduate Study from Rowan University
    • Health Data Management Certificate of Graduate Study from Rowan University
    • Data Science Analytics Master’s Degree from Thomas Edison State University (TESU)
    • Data Science Analytics Bachelor’s Degree – TESU
    • Mathematics with Predictive Modeling Emphasis BS from Bellevue University
  • Enterprise
    • Organizations
    • Higher Education
  • Resources
    • Blog
    • FAQs & Knowledge Base
    • Glossary
    • Site Map
    • Statistical Symbols
    • Weekly Brief Newsletter Signup
    • Word of the Week

Blog

Home » Blog » Blog Type » Word of the Week » Kernel function

Kernel function

  • January 17, 2020
  • , 4:52 pm

In a standard linear regression, a model is fit to a set of data (the training data); the same linear model applies to all the data.  In local regression methods, multiple models are fit to different neighborhoods of the data. A kernel function is used to determine the contribution of the “neighborhood data” to the predicted value.  A simple kernel method is k-nearest neighbors – for a given record with known predictor values and unknown y, the y values for the k closest data records (in terms of their predictor values) are averaged, and that average is the predicted y value for the record being considered.  

Often the kernel function attaches higher weights to closer records, and lower weights to more distant records.  This has the effect of smoothing, so that the regression curve is not “jerky,” as it is with equally-weighted neighbors.  Chapter 6 in The Elements of Statistical Learning, available online here, provides an excellent exposition.

Subscribe to the Blog

You have Successfully Subscribed!

Categories

Recent Posts

  • Dec 14: Statistics in Practice December 11, 2020
  • PUZZLE OF THE WEEK – School in the Pandemic December 11, 2020
  • From Kaggle to Cancel: The Culture of AI December 11, 2020

About Statistics.com

Statistics.com offers academic and professional education in statistics, analytics, and data science at beginner, intermediate, and advanced levels of instruction. Statistics.com is a part of Elder Research, a data science consultancy with 25 years of experience in data analytics.

Latest Blogs

  • Dec 14: Statistics in Practice
    December 11, 2020/
    0 Comments
  • PUZZLE OF THE WEEK – School in the Pandemic
    December 11, 2020/
    0 Comments
  • From Kaggle to Cancel: The Culture of AI
    December 11, 2020/
    0 Comments

Social Networks

Linkedin
Twitter
Facebook
Youtube

Contact

The Institute for Statistics Education
4075 Wilson Blvd, 8th Floor
Arlington, VA 22203
(571) 281-8817

ourcourses@statistics.com

© Copyright 2021 - Statistics.com, LLC | All Rights Reserved | Privacy Policy | Terms of Use

By continuing to use this website, you consent to the use of cookies in accordance with our Cookie Policy.

Accept