Timeline for MLE with unbalanced system of regressions
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 16, 2018 at 13:45 | vote | accept | Jean-Paul | ||
| Jul 16, 2018 at 13:37 | answer | added | Heteroskedastic Jim | timeline score: 2 | |
| Jul 11, 2018 at 12:32 | comment | added | Heteroskedastic Jim |
Ben Bolker's suggestion is easy to implement in R. You can use the glmmTMB package to specify a model for the error variance. Alternatively, the weights = option with varIdent() under gls() in nlme is an option. Also, mle() in stats4 or mle2() in bbmle can handle this if you specify a model for the standard deviation. All these methods are equivalent, say except gls() which uses REML by default.
|
|
| Jul 10, 2018 at 16:35 | comment | added | Jean-Paul | @BenBolker In that case the error variances would be assumed equal, an assumption I can’t make. | |
| Jul 10, 2018 at 16:26 | comment | added | Ben Bolker | combine the data sets and use dummy variables to control which parameters/predictor variables are used for each response type? | |
| Jul 10, 2018 at 16:10 | history | asked | Jean-Paul | CC BY-SA 4.0 |