Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with error
Search options not deleted
user 46228
The error of an estimate or prediction is its deviation from the true value, which may be unobservable (e.g., regression parameters), or observable (e.g., future realizations). Use the [error-message] tag to ask about software errors.
1
vote
0
answers
3k
views
error structure in Generalized linear models when y is continuous data and errors not normal...
Lets say I have continuous y and x variable and I run a linear regression:
mdl1<-lm(y ~ x)
A generalised linear model should also give me the same parameters value if I do not specify the error structure … (i.e. by default it assumes that the error structure is Gaussian)
mdl2<-glm(y ~ x)
Both the above model should give me the same results (since in the mdl2, by default the error structure is gaussian …
- 163