TS feature requests

Hi @aa25desh and welcome to MLJ.jl!
Here are some time series forecasting features I find very valuable:
Check out @robjhyndman's free book on forecasting: https://otexts.com/fpp2/

Univariate time-series:

1. naive & seasonal naive models
2. auto.arima model
3. ets model
4. thetam model
5. nnetar model
6. stlm model
7. tbats model
8. their hybrids. Also check out Forecast Benchmarks.
   All the above belong to @robjhyndman's forecast.r which is being refactored in the new fable.r.
   -it is valuable to understand where forecast went wrong & what fable is doing different so we don't make the same mistakes

Multivariate time-series:

1. vector auto regression: @fipelle's TSAnalysis.jl is nice (also ElasticNetVAR.jl).
   PS: I've never seen automated multivariate models (VARIMA) the same way we have automated univariate models (auto.arima() etc).

Volatility models:

1. @s-broda's ARCHModels.jl is very neat!
   Hansen has nice slides on volatility forecasting & a paper that compares 330 ARCH-type models.

Impulse Response Functions:
I usually do this in R.
Two Julia packages: VARmodels.jl & VectorAutoregressions.jl

In general Julia has great libraries in many domains. Unfortunately time series is one of the least well organized.
It also means this is the area w/ the biggest opportunities to make a lasting impact on the worth through open source!

Start by reviewing the repository structure and the Julia time-series packages linked in the issue, including forecast, fable, TSAnalysis.jl, ARCHModels.jl, VARmodels.jl, and VectorAutoregressions.jl. The request spans univariate, multivariate, volatility, and impulse-response models, but names no implementation files or tests; a concrete feature scope and completion criteria are needed before work can begin.