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 covariance-matrix
Search options not deleted
user 23790
A $k\times k$ matrix of covariances between all pairs of $k$ random variables. It is also called variance-covariance matrix or simply the covariance matrix.
1
vote
Variance-covariance matrix of the parameter estimates wrongly calculated?
Seconded to @Jen 's answer. In fact the 5th line in the result of summary(hyperbfitalv) are SE's. They are indeed the square root of the diagonal elements of inverse-hessian solve(hyperbfitalv$hessian …
- 328
2
votes
The vcov function cannot be applied?
The reason that parameters passed to the optimizer are pi, log(zeta), log(delta), mu not zeta and delta is mostly likely to constrain the optimizer in R+ for zeta and delta. If you need the Hessian of …
- 328
1
vote
Accepted
The vcov function cannot be applied?
Actually you already have the S.E. for zeta and delta, calculated from log(zeta) and log(delta), in summary(hyperbfitalv): Variance-covariance matrix of the parameter estimates wrongly calculated?
Le …
- 328