Homework Help is Here – Start Your Trial Now!
Math
Statistics
Recall the following two criteria for quality of a linear model: AIC = n log ( RSS/n) + 2(k +1) and BIC = n log ( RSS/n ) + (k + 1) log(n). In both cases, a smaller value corresponds to a “better fit". Suppose you perform model selection by adding candidate predictors sequentially, comparing either AIC or BIC at each step. Under what condition is using AIC as opposed to BIC more likely to produce a final model with more predictors? Under what condition is using AIC as opposed to BIC more likely to produce a final model with fewer predictors? %3D

Recall the following two criteria for quality of a linear model: AIC = n log ( RSS/n) + 2(k +1) and BIC = n log ( RSS/n ) + (k + 1) log(n). In both cases, a smaller value corresponds to a “better fit". Suppose you perform model selection by adding candidate predictors sequentially, comparing either AIC or BIC at each step. Under what condition is using AIC as opposed to BIC more likely to produce a final model with more predictors? Under what condition is using AIC as opposed to BIC more likely to produce a final model with fewer predictors? %3D

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
See similar textbooks
icon
Related questions
Question
3
Recall the following two criteria for quality of a linear model: AIC = n log ( RSS/n) + 2(k +1) and BIC = n log ( RSS/n ) + (k + 1) log(n). In both cases, a smaller value corresponds to a "better fit". Suppose you perform model selection by adding candidate predictors sequentially, comparing either AIC or BIC at each step. Under what condition is using AIC as opposed to BIC more likely to produce a final model with more predictors? Under what condition is using AIC as opposed to BlC more likely to produce a final model with fewer predictors?
Transcribed Image Text:Recall the following two criteria for quality of a linear model: AIC = n log ( RSS/n) + 2(k +1) and BIC = n log ( RSS/n ) + (k + 1) log(n). In both cases, a smaller value corresponds to a "better fit". Suppose you perform model selection by adding candidate predictors sequentially, comparing either AIC or BIC at each step. Under what condition is using AIC as opposed to BIC more likely to produce a final model with more predictors? Under what condition is using AIC as opposed to BlC more likely to produce a final model with fewer predictors?
Expert Solution
steps

Step by step

Solved in 2 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
Statistics
ISBN:
9781119256830
Author:
Amos Gilat
Publisher:
John Wiley & Sons Inc
Probability and Statistics for Engineering and th…
Probability and Statistics for Engineering and th…
Statistics
ISBN:
9781305251809
Author:
Jay L. Devore
Publisher:
Cengage Learning
Statistics for The Behavioral Sciences (MindTap C…
Statistics for The Behavioral Sciences (MindTap C…
Statistics
ISBN:
9781305504912
Author:
Frederick J Gravetter, Larry B. Wallnau
Publisher:
Cengage Learning
Elementary Statistics: Picturing the World (7th E…
Elementary Statistics: Picturing the World (7th E…
Statistics
ISBN:
9780134683416
Author:
Ron Larson, Betsy Farber
Publisher:
PEARSON
The Basic Practice of Statistics
The Basic Practice of Statistics
Statistics
ISBN:
9781319042578
Author:
David S. Moore, William I. Notz, Michael A. Fligner
Publisher:
W. H. Freeman
Introduction to the Practice of Statistics
Introduction to the Practice of Statistics
Statistics
ISBN:
9781319013387
Author:
David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:
W. H. Freeman
SEE MORE TEXTBOOKS