Statistics
- Akaike information criterion (AIC), a measure of the goodness fit of an estimated statistical model
- Bayesian information criterion (BIC), also known as the Schwarz information criterion, a statistical criterion for model selection
- Deviance information criterion (DIC), another Bayesian oriented model selection criterion
- Focused information criterion (FIC), a selection criterion sorting statistical models by their effectiveness for a given focus parameter
- Hannan-Quinn information criterion, an alternative to the Akaike and Bayesian criteria
Read more about this topic: Information Criterion
Famous quotes containing the word statistics:
“and Olaf, too
preponderatingly because
unless statistics lie he was
more brave than me: more blond than you.”
—E.E. (Edward Estlin)
“July 4. Statistics show that we lose more fools on this day than in all the other days of the year put together. This proves, by the number left in stock, that one Fourth of July per year is now inadequate, the country has grown so.”
—Mark Twain [Samuel Langhorne Clemens] (1835–1910)
“O for a man who is a man, and, as my neighbor says, has a bone in his back which you cannot pass your hand through! Our statistics are at fault: the population has been returned too large. How many men are there to a square thousand miles in this country? Hardly one.”
—Henry David Thoreau (1817–1862)