How Do the Schechter Function and Maximum Likelihood Method Differ?

  • Thread starter Thread starter jl294
  • Start date Start date
  • Tags Tags
    Function
AI Thread Summary
The Schechter Function is a model that describes the luminosity function of galaxies, while the Maximum Likelihood Method and 1/Vmax method are statistical techniques used to fit functions like the Schechter function to observational data. These methods are not the same as the Schechter function but are tools for analyzing data related to it. The 1/Vmax method may not be suitable for galaxy groups with similar distances, as it relies on varying distances for accurate application. The choice of fitting method can vary based on specific circumstances and data characteristics. Understanding these distinctions is crucial for effective analysis in astrophysics.
jl294
Messages
5
Reaction score
0
Schechter Function...

I''m very confused with what the difference is between the Schechter Function and 'Maximum likelihood method' or 1/Vmax method? Are the later two methods to be applied to the Schechter or are they completely different functions to calculate LF altogether?

Cheers
 
Astronomy news on Phys.org


These are completely different things. The Schechter function describes the luminosity function of galaxies [see: http://en.wikipedia.org/wiki/Luminosity_function_(astronomy ) ]; while the maximum likelihood and 1/vmax methods are statistical methods of fitting a function (e.g. the Schechter function) to a set of data [see: http://en.wikipedia.org/wiki/Maximum_likelihood ]
 
Last edited by a moderator:


OK. What do you think is the best method for fitting Schechter function for Galaxy Groups? The distance is roughly similar for these galaxies, so 1/Vmax method wouldn't be applicable right?

Cheers
 


I'm not sure, I've never done it myself. I'm sure it depends on the situation---and I'm sure you're right, if the distances are comparable, 1/Vmax isn't doing much.
I think there is also a lot of variety on how to implement a maximum likelihood method---I don't think its a specific algorithm.
 

Thread 'How feasible is home radio astronomy?'

Is a homemade radio telescope realistic? There seems to be a confluence of multiple technologies that makes the situation better than when I was a wee lad: software-defined radio (SDR), the easy availability of satellite dishes, surveillance drives, and fast CPUs. Let's take a step back - it is trivial to see the sun in radio. An old analog TV, a set of "rabbit ears" antenna, and you're good to go. Point the antenna at the sun (i.e. the ears are perpendicular to it) and there is...
View full post »

Thread 'Our Beautiful Universe - Photos and Videos'

This thread is dedicated to the beauty and awesomeness of our Universe. If you feel like it, please share video clips and photos (or nice animations) of space and objects in space in this thread. Your posts, clips and photos may by all means include scientific information; that does not make it less beautiful to me (n.b. the posts must of course comply with the PF guidelines, i.e. regarding science, only mainstream science is allowed, fringe/pseudoscience is not allowed). n.b. I start this...
View full post »

Similar threads

A Finding Global Minima in Likelihood Functions
Replies
1
Views
2K
I Gradient descent algorithm and optimizers
Replies
5
Views
2K
MHB Finding MLE for $\theta$ of Statistical Product Model
Replies
6
Views
2K
I Akaike Information Criterion Vs Likelihood Ratio Test
Replies
5
Views
4K
Python Binned Maximum Likelihood fit in python?
Replies
9
Views
3K
A Correlation between parameters in a likelihood fit
Replies
3
Views
1K
I What Does the Likelihood Function Tell Us?
Replies
16
Views
2K
I Why is the maximum likelihood estimation accurate?
Replies
11
Views
3K
A Constructing PDFs for Max Likelihood Density Estimation Problem
Replies
2
Views
2K
I What Are the Key Differences Between OLS and GLM Models in Statistical Analysis?
Replies
3
Views
2K

Hot Threads

Recent Insights

Back
Top