Hannan-Quinn information criterion
Okay kiddo, let me tell you about something called the Hannan-Quinn Information Criterion (HQIC). Basically, when we have a bunch of data, we want to find the best way to represent it mathematically. There are many ways to do this, but sometimes we end up with too many equations or too few equations and it's hard to tell which one is the best.
HQIC helps us figure out which mathematical representation is the best by looking at a few different things. It looks at how well the equation fits the data, but it also considers how many equations are in the equation. We don't want too many equations or too few equations - we want the right amount of equations to make the equation fit the data perfectly.
Think of it like a puzzle. We have to find the best pieces that fit together to make the puzzle complete - not too many pieces, not too few pieces, just the right amount of pieces to make the puzzle picture look perfect.
HQIC is a tool that helps us figure out which pieces of the puzzle should be used to make the best picture possible.
HQIC helps us figure out which mathematical representation is the best by looking at a few different things. It looks at how well the equation fits the data, but it also considers how many equations are in the equation. We don't want too many equations or too few equations - we want the right amount of equations to make the equation fit the data perfectly.
Think of it like a puzzle. We have to find the best pieces that fit together to make the puzzle complete - not too many pieces, not too few pieces, just the right amount of pieces to make the puzzle picture look perfect.
HQIC is a tool that helps us figure out which pieces of the puzzle should be used to make the best picture possible.