diff --git a/README.md b/README.md index 91d6e2e..dcb099c 100644 --- a/README.md +++ b/README.md @@ -102,11 +102,6 @@ But issues can sometimes occur when: If you run into any of these issues, it is best to consult with your IT department for support. -## `mvgam` cheatsheet - -[![`mvgam` usage -cheatsheet](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.png)](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.pdf) - ## WORKSHOP MATERIALS [Live questions and code sharing](https://docs.google.com/document/d/1xd3icf1wxGxO3SVt2AmKO8CkeKv1QpsxgqK7rR15U08/edit?usp=sharing)
@@ -115,3 +110,34 @@ cheatsheet](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheats [Live code example 1](https://github.com/nicholasjclark/ESA_2024_timeseries/blob/main/live_code_examples/casestudy1_kestrel.R)
[Live code example 1](https://github.com/nicholasjclark/ESA_2024_timeseries/blob/main/live_code_examples/casestudy2_aphids.R) + +## OTHER `mvgam` RESOURCES + +A series of vignettes cover data formatting, forecasting and several +extended case studies of DGAMs. A number of other examples have also +been compiled: + +- Ecological Forecasting with Dynamic Generalized Additive + Models +- Distributed lags (and hierarchical distributed lags) + using mgcv and mvgam +- State-Space Vector Autoregressions in + mvgam +- Ecological Forecasting with Dynamic GAMs; a tutorial and + detailed case study +- How to interpret and report nonlinear effects from + Generalized Additive Models +- Phylogenetic smoothing using mgcv +- Incorporating time-varying seasonality in forecast + models + +[![`mvgam` usage +cheatsheet](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.png)](https://github.com/nicholasjclark/mvgam/raw/master/misc/mvgam_cheatsheet.pdf)