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spEDM 1.5

new

  • Enable parallel.level parameter to specify parallel granularity in gccm R API (#310).

  • Implement the multiview function for multiview embedding forecasting (MVE) method (#221).

enhancements

  • Integrate lib parameter in gccm R API for library units selection (#278).

  • Set the default k to E+2 in the gccm R API (#261).

  • Eliminate redundant computations at the source C++ code level (#233).

  • Add trend.rm option in the R API for embedded, simplex, and smap methods to align with gccm behavior (#191).

  • Refactor indexing of lag values and embedding vector generation for spatial lattice (#186,#184) and grid data (#183,#181).

  • Centered around example cases in the gccm vignette (#170).

breaking changes

  • Default plotting method places the legend in the top-left corner of the plot now (#325).

  • Refine simplex & smap output on the R side (#263).

bug fixes

  • Fix bug in R functions embedded, simplex, smap when input data contains only one attribute column (#246).

spEDM 1.4

enhancements

  • Improve default spatial neighbors list generation for spatial lattice data with support from the sdsfun package (#159).

breaking changes

  • Adjust the behavior of the tau parameter in the C++ source code and update the R side API (#154).

spEDM 1.3

new

  • Implement the smap function to enable the selection of the optimal theta parameter (#128).

  • Add simplex function to support selecting the optimal embedding dimension for variables (#98).

  • Provide an R-level API for generating embeddings (#97).

enhancements

  • Now bidirectional mapping in the gccm result uses a full join structure when organized on the R side (#118).

  • Support for calculating unidirectional mappings in the gccm function (#117).

  • Relax gccm C++ source code libsizes minimum value constraint of E+2 (#109).

  • Provide a complete GCCM workflow for spatial lattice and grid data in the gccm vignette (#100).

  • Support testing causal links in GCCM with different E and k for cause and effect variables (#96).

  • Add thread settings for gccm (#94).

  • Add S-maps cross-prediction support to gccm (#81).

bug fixes

  • Resolve r crash caused by invalid E #90 and k #89 parameter settings in gccm.

  • Fix incorrect Pearson correlation calculation in C++ code when input contains NA (#83).

spEDM 1.2

enhancements

  • Encapsulate the gccm function using the S4 class (#72).

  • Add options for tau, k, and progressbar in gccm (#69).

  • Add print and plot s3 methods for gccm result (#64).

bug fixes

  • Fix the bug where the gccm function returns empty results when input grid data contains NA values (#61).

spEDM 1.1

bug fixes

  • Resolve CRAN auto check issues, no significant API changes.

spEDM 1.0

new

  • Implementing the GCCM method for spatial lattice and grid data using pure C++11.