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Conditional Auto-Regressive LASSO in R

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Two errors that I've found when running the package are that: 1. **Error: chol(): decomposition failed** ```` CARlasso(Ga0485157_metabat1.059+Ga0485167_maxbin.109+ Ga0485162_maxbin.089+Ga0485161_maxbin.110+Ga0485161_maxbin.075+Ga0485157_metabat1.036+Ga0485165_metabat2_ours.012_sub+Ga0485169_maxbin.201_sub+Ga0485172_maxbin.081_sub+Ga0485168_maxbin.153+ Ga0485172_metabat2_ours.083+ Ga0485162_maxbin.023+ Ga0485160_maxbin.092+ Ga0485158_metabat2_jgi.024+ Ga0485162_metabat1.001+**Ga0485163_metabat1.131**~ depth+wtemp+sp_cond+chlor_rfu+phyco_rfu+fdom_rfu+turb_fnu+do_sat+do_raw+ph, data = data_use, link="log",adaptive =...

I am getting the following warnings and errors. `CARlasso(Didymellaceae + `Cladosporium ramotenellum` + `Didymella sp.`+ Didymosphaeriaceae + Didymellaceae.1 + `Gibberella intricans` + `Colletotrichum spaethianum` + `Alternaria alternata` + `Coniothyrium sp.`...

I've tried to run `bGlasso` with the same binary dataset as `CARlasso` (sans predictors). It runs fine with `CARlasso` and it appears to also be running fine with `bGlasso` when...

For higher dimension cases the formula can be too long to approach, we should have CARlasso allowing matrix input.

enhancement

This can be done by users themselves but can be better done as a function since we generated the network object during `plot` methods anyway.

enhancement