[WIP] feat(edm): integrate EDM prediction framework into FIMS#1620
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aman-raj-srivastva wants to merge 39 commits into
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[WIP] feat(edm): integrate EDM prediction framework into FIMS#1620aman-raj-srivastva wants to merge 39 commits into
aman-raj-srivastva wants to merge 39 commits into
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added the comments to the following files: modified: R/distribution_formulas.R modified: R/fimsfit.R modified: R/initialize_modules.R modified: inst/include/common/information.hpp modified: inst/include/common/model.hpp modified: inst/include/distributions/functors/density_components_base.hpp modified: inst/include/distributions/functors/normal_lpdf.hpp modified: inst/include/interface/rcpp/rcpp_objects/rcpp_distribution.hpp modified: src/FIMS.cpp
- Created rcpp_edm.hpp defining EDMInterfaceBase and DelayEmbeddingInterface wrapper classes. - Exposed the construct(), construct_drop_missing(), and at() methods to R. - Exposed fields/metadata (such as embedding_dimension, time_lag, n_rows, n_cols, values, and target_indices) to R. - Registered the DelayEmbedding class in the RCPP_MODULE(fims) block within fims_modules.hpp.
- Add edm_embeddings list slot to the FIMSFrame S4 class to store delay-embedding results produced by create_edm_embedding() - Add create_edm_embedding() helper that pulls a named time series from the data slot, calls the Rcpp DelayEmbedding module, and returns a new FIMSFrame with the result stored by name - Add get_edm_embeddings() accessor following the existing get_*() pattern in fimsframe.R - Add model_edm_matrix() accessor that returns a numeric matrix (n_rows x E) ready to pass to an EDM prediction module, following the existing model_*() pattern - Register 'edm' as a valid FIMSFrame input type in data-raw/fims_input_types.R and regenerate data/fims_input_types.rda - Add tests/testthat/test-edm-fimsframe.R with 6 test blocks covering default empty slot, error handling, input validation, metadata correctness, matrix shape, and chaining multiple embeddings This completes proposal deliverable: 'Create structures in FIMSFrame for embedded matrices' (Weeks 1-3).
…r review feedback
…rget
Per mentor feedback (nathanvaughan-NOAA, stevemunch):
1. Selectable weighting kernel (SMapKernel enum):
- kExponential (default): w = exp(-theta * d / d_mean) [rEDM / Sugihara 1994]
- kGaussian: w = exp(-theta^2 * (d/D)^2) [Esguerra & Munch 2024]
Both reduce to global OLS when theta=0. Kernel field exposed on
SMapProjection<Type> so users can compare formulations.
2. One-step-ahead target alignment in MakeDelayEmbedding:
Added forecast_horizon parameter (default=1). target_values[row] now
points to series[target_index + h], matching the standard EDM
formulation: predict x_{t+h} from the embedding state x_t.
n_rows reduced by forecast_horizon to keep all target pointers in bounds.
MakeDelayEmbeddingDropMissing forwards the parameter unchanged.
3. Tests: 12 S-Map + 9 Simplex = 21 passing GoogleTests.
- edm.hpp: remove stale 'S-map will be added' note; SMapProjection
is already included
- delay_embedding.hpp: correct target_values struct description from
'x_t' to 'x_{t+h}'; fix target_uncertainty comment to say
sigma_{target_index + forecast_horizon} not sigma_t
…-marginal likelihood
… and GPEdmProjection with to_matrix helper
…rojection, and GPEdmProjection Rcpp interfaces
…oses predictions in variable_map
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…IMSFrame rebase rename
…in create_edm_embedding()
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Summary
This PR integrates the EDM prediction framework into the FIMS statistical modeling pipeline.
Building on the standalone delay embedding infrastructure (#1528) and prediction framework (#1561), this PR incrementally connects EDM prediction algorithms to the FIMS objective function so that their predictions can participate in the joint negative log-likelihood alongside existing FIMS model components.
Target Branch:
main-edmCurrent Progress
This PR currently introduces the
EDMModel<Type>module.Implemented:
EDMModel<Type>as a new FIMS moduleEDMModel<Type>inherits fromFIMSObject<Type>edm.hppto expose the new modulePlanned Work
The following components will be added in subsequent commits:
EDMModelinInformation<Type>Model::Evaluate()add_to_fims_tmb_internal()interfacesfinalize()Related
Instructions for code reviewer
👋Hello reviewer👋, thank you for taking the time to review this PR!
nit:(for nitpicking) as the comment type. For example,nit:I prefer using adata.frame()instead of amatrixbecause ...This PR is now ready to be merged.Checklist