Hello World!

I have read the description to gogarch package, but i don't understand the function of external.regression option in that package.. How it is working ? could you give an example?

```
us=ugarchspec(variance.model=list(model="iGARCH", garchOrder=c(1,1)),
mean.model=list(armaOrder=c(1,0), include.mean=F),distribution.model="norm", fixed.pars=list(omega=0))
usgarch=ugarchfit(spec = us,data = Data)
#This gives us parameters estimations
#but lets say my mean and variance parts in the second equation:
us2=ugarchspec(**variance.model=list(model="iGARCH", garchOrder=c(1,1)),
mean.model=list(armaOrder=c(1,0),** include.mean=F),distribution.model="norm", fixed.pars=list(omega=0))
usgarch=ugarchfit(spec = us2,data = Data2)
# are dependent form first equation (us2 has its own AR1 garch1,1 process, plus the mean and variance innovations from "us" which are included into equation of "us2").
#Can I use the " external.regression" function for this instances? how will I include ?
#To write all calculation steps with ML, for parameters is very tedious work,
#I have data with 16 variables meaning i have to otherwise to write to each of them the calculation scripts
```

Did I explain it well? in case it is not clear please write a comment i will respond immediately.