What is iid gaussian

Sign up to join this community. The best answers are voted up and rise to the top. Stack Overflow for Teams — Collaborate and share knowledge with a private group. Create a free Team What is Teams? Learn more. What is the difference between normal and IID? Ask Question. Asked 4 years, 11 months ago. Active 4 years, 11 months ago. Viewed 13k times. Improve this question. Identical need not be normal. If everything is e. These are standard terms; it's not really the job of this forum to do basic searches for you.

Add a comment. Active Oldest Votes. In that case, we say that the residuals really the errors should meet the following assumptions: They are independent They have constant variance They are normally distributed If they are independent and identically distributed IID , then they must meet the first two criteria since differing variances constitute non-identical distributions. Thus, whether or not a set of data is IID is unrelated to whether they are normal. Improve this answer.

Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name. Improve this question. Nick Cox Benj Cabalona Jr. What kind of answer are you looking for? Different distributions have different logical substantiations. While approximate normality can often be argued for, there are few examples where it does makes sense to assume exact normality.

I'm actually curious let's say in the domain of machine learning, is there a case where we assume that the errors follows a distribution other than gaussian? For example, for counts you assume a discrete, non-negative error distribution Poisson, negative binomial , for ratios you assume a binomial error distribution, for time between events you assume a non-negative continuous distribution exponential, Weibull.

It means the variables are independent and identically distributed. It doesn't imply any particular form for the distributions Gaussian or otherwise. For example, a series of coin flips would be modeled as a set of i. Bernoulli variables. For example but this is just an example! It depends on the application, and the specific random variable that you are modeling.

Many times, it will just be the empirical evidence to suggest a proxy for the pdf. Show 2 more comments. Active Oldest Votes. Improve this answer. Community Bot 1. Ben Ben Add a comment. Dave Dave This is exactly what i'm curious about. Im going over Stanford's CS Thanks again. Sign up or log in Sign up using Google. Sign up using Facebook. Sign up using Email and Password. Post as a guest Name.