2022-04-01 version 1.11.0 JosephPark@IEEE.org
Simplex, SMap, CCM, Embed, Multiview, EmbedDimension, PredictInterval, PredictNonlinear, ComputeError instead of the legacy version 0.7 signatures. See Version 1.3 notes.SMap linear system solver regularization: The R glmnet package does not seperate the model from the data. This prevents integration in rEDM. Users requiring SMap regularization are referred to the pyEDM wrapper.nan from SMap columns and target. Warning generated.generateSteps parameter to Simplex and SMap implementing generative feedback prediction.parameterList argument to Simplex, SMap, CCM and Multiview.pathOut, predictFile are removed from SMap, Multiview to accomodate the Rcpp 20 parameter limit.parameterList values to numerics.Tp < 1 in generative mode.SMap dgelss error message. CCM libSize limits Tp < 0.validLib parameter to Simplex and SMap. validLib is a boolean vector with the same number of elements as input data rows. For validLib elements that are false, the correspoding data row will not be included in the state-space library.CCM parameter validation with tau > 0.CCM parameter validation with Tp < -1.deletePartial argument to MakeBlock.SMap, CMM includeData, and, the use of disjoint libraries.SMap coefficients with names from the columns and target parameters.CCM.A major rewrite of the ‘rEDM’ package as an Rcpp wrapper for the cppEDM library providing a unified computation engine for EDM algorithms across C++, Python and R implementations. The revised package provides improved alignment between observed and forecast data rows, handling of date time vectors, and, strict exclusion of partial data vectors.
To align with cppEDM and pyEDM, function names and signatures have changed from versions 0.7 and earlier. It is recommended to use the new functions: Simplex, SMap, CCM, Embed, Multiview, EmbedDimension, PredictInterval, PredictNonlinear, ComputeError. See EDM Documentation or the package documentation.
A legacy function interface is provided to emulate function signatures of rEDM 0.7, but does not have complete coverage. It also has slightly different return values since nested data.frames are not returned. Return values are either a data.frame, or, a named list of data.frames, as noted in the man pages. Implemented functions’ include: simplex, s_map, block_lnlp, ccm, multiview, make_block, compute_stats and make_surrogate_data. Functions ccm_means, tde_gp, block_gp and test_nonlinearity are deprecated.