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Initial native R port of EDGAR.
cr_eq, cr_uneq, rcb,
rcb_uneq, two_factor_rcb, latin,
split_plot, variable_blocks,
alpha.list_designs(),
generate_design(type, ..., seed = 0L),
validate_design(type, ...), plus design-specific
convenience functions (design_cr(),
design_rcb(), design_alpha(), and so on).edgar_design class with print,
as.data.frame, total_units,
has_layout, and as_layout_frames methods.write_edgar_csv() (no extra
dependencies), write_edgar_json() (requires
jsonlite), write_edgar_xlsx() (requires
openxlsx).propose_alpha_structures() helper for alpha
design feasibility checks. choose_design() is provided as
an alias matching the upstream Python API.random.Random Mersenne Twister seeding and Fisher-Yates
shuffle, giving byte-identical cross-language reproducibility for the
same integer seed..Random.seed.testthat test suite covering structural
invariants, validation failures, determinism, and byte-identical parity
against the upstream Python edgar-design package.EDGAR was originally developed by the Biometrics team at Rothamsted
Research as Excel workbooks (http://www.edgarweb.org.uk/). The
algorithms were subsequently re-implemented in the Python project
rotsl/edgar, documented at https://rotsl.github.io/edgar/
and distributed as edgar-design on PyPI. This R package is
a native R port of that Python implementation. Alpha designs follow
Patterson and Williams (1976), doi:10.1093/biomet/63.1.83.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.