# Goodness-of-fit

Is the data agree with the model?

- distance between data and model predictions
- likelihood function: likelihood of observing the data if we assume the model; the results will be a set of fitting parameters.

Why don’t we always use goodness-of-fit as a measure of the goodness of a model?

- overfitting
- not intuitive

This is why we would like to balance it with parsimony using some measures of generalizability.

Published:
by Lei Ma;

## Table of Contents

**Current Ref:**

- wiki/model-selection/goodness-of-fit.md

**Links from:**

###### Akaike Information Criterion

Suppose we have a model that describes the data generation process behind a dataset. The …

###### Bayesian Information Criterion

BIC is Bayesian information criterion, it replaced the $+2k$ term in AIC with $k\ln n$ $$ …

###### Model Comparison

The parsimony model comes from the idea of Occam’s razor: We choose the simple model that has …

###### Parsimony of Models

For models with a lot of parameters, the goodness-of-fit is very likely to be very high. However, it …