I’m running a bayesian DCC-mgarch model. Right now its just 2 variables. This is the function call in R for the model.

```
library(bmgarch)
cols = c('Free.Cash.Flow', 'Revenue')
model <- bmgarch(dataset[,cols],
parameterization = "DCC",
iterations = 1000,
P = 1, Q = 1,
chains = 1,
init_r = 1,
enable_random_init = FALSE,
distribution = "Student_t",
meanstructure = "arma")
```

Sample rows of the data…the numbers are quite large if that matters at all.

```
Free.Cash.Flow Revenue
1 331510000 972360000
2 331510000 700356000
3 331510000 667625000
4 331510000 639281000
5 331510000 1115171000
6 331510000 847422000
```

I keep getting these error messages running the basic model.

Chain 1: Rejecting initial value:

Chain 1: Error evaluating the log probability at the initial value.

Chain 1: Exception: validate transformed params: H[i_0__] is not symmetric. H[i_0__][1,2] = 1.15446e+17, but H[i_0__][2,1] = 1.15446e+17 (in ‘model_DCCMGARCH’ at line 62)Chain 1: Rejecting initial value:

Chain 1: Error evaluating the log probability at the initial value.

Chain 1: Exception: validate transformed params: H[i_0__] is not symmetric. H[i_0__][1,2] = -3.59349e+15, but H[i_0__][2,1] = -3.59349e+15 (in ‘model_DCCMGARCH’ at line 62)Chain 1:

Chain 1: Initialization between (-0.05, 0.05) failed after 100 attempts.

Chain 1: Try specifying initial values, reducing ranges of constrained values, or reparameterizing the model.

[1] “Error in sampler$call_sampler(args_list[[i]]) : Initialization failed.”

[1] “error occurred during calling the sampler; sampling not done”

Stan model ‘DCCMGARCH’ does not contain samples.

I have tried fiddling with the function call like setting init_r = 0 but to no avail.

Can someone please help me out?

EDIT: added data