What does iid

Word in Definition. Wiktionary 5. Suggested Resources 0. How to pronounce IID? Alex US English. David US English. Mark US English. Daniel British. Libby British. Mia British. Karen Australian. Hayley Australian. From: i. Subjects: Science and technology — Mathematics and Computer Science. View all related items in Oxford Reference ». All Rights Reserved. Under the terms of the licence agreement, an individual user may print out a PDF of a single entry from a reference work in OR for personal use for details see Privacy Policy and Legal Notice.

Oxford Reference. Publications Pages Publications Pages. The output of a Markov chain is not IID, because the probability distribution of each variable is dependent upon the previous state of the Markov chain. Already have an account? Login here. Active 11 months ago. Viewed k times. Improve this question. Add a comment. Active Oldest Votes. Improve this answer. Ameer Moaaviah 5 5 bronze badges. Thanks a lot in advance Show 4 more comments.

Dilip Sarwate Dilip Sarwate Whereas "identically distributed" means each event has the same likelihood of heads? Nor are they independent. The events may be defined across tosses as above, or within a single experiment. It is common to describe this by saying "a fair coin" or "a fair dice" or saying things like "A ball is chosen at random from an urn with 3 green balls and 2 red balls" etc.

It is only the purists who will cavil and insist that it should be "a fair die" I understand now, thank you. Is it arguable that " if two events are not independent, they can not be from identical distributions"? Show 5 more comments. If you have two random variables then they are IID independent identically distributed if: If they are independent. As explained above independence means the occurrence of one event does not provide any information about the other event.

For example, if I get heads after flips, the probabilities of getting heads or tails in the next flip are the same. If each random variable shares the same distribution. For example, lets take the random variable from above - X.