Changes in version 1.2.0                        

The version number now matches the Julia reference implementation
(github.com/reinhardhansen/GFT, tag v1.2.0), which this release ports
function for function.

Changes to inv_gft()

  - inv_gft() now implements the revised GFT-FP+N of the paper (Archakov
    and Hansen, 2026, arXiv:2609.19028): Newton steps for the
    log-diagonal residual (H delta = -D ell instead of H delta = -g),
    forcing tolerance min(1/2, ||ell||) (locally quadratic), exact
    normalization of every evaluated point along the vector of ones, no
    initial fixed-point phase, an adaptive initial Armijo step, and a
    descent test before the untested-step rule. Median
    eigendecomposition counts fall by about 40% on ill-conditioned
    inputs and by two or three on well-conditioned ones; solutions are
    unchanged.
  - The previous algorithm remains available through the new arguments
    residual, forcing, normalize, phase and adaptive (residual =
    "gradient", forcing = "sqrt", normalize = FALSE, phase = TRUE,
    adaptive = FALSE).
  - New argument preconditioner: "quadrature" or "auto" replaces the
    diagonal preconditioner of the conjugate-gradient solve by a
    quadrature model of the Hessian with a certified condition-number
    bound; "auto" applies the paper's selection rule.

New functions

  - inv_gft_anderson(): Anderson acceleration of the fixed point, with a
    guarded option that makes it globally convergent.
  - inv_gft_lbfgs(): limited-memory BFGS on the objective.
  - inv_gft_path() and gft_predict(): sequential inversion with warm
    starts and a tangent predictor.

                 Changes in version 1.0.1 (2026-08-23)                  

Bug fixes

  - inv_gft_newton() gains a safeguard argument, default TRUE. The new
    default fixes the stall described below. safeguard = FALSE
    reproduces the previous behaviour, which is the published comparator
    of Chen, Fei and Yu (2025) with only the Armijo line search added,
    and is the variant benchmarked in the accompanying paper. Set it
    when reproducing those results.

  - With the new default, inv_gft_newton() no longer stalls short of the
    requested tolerance and returns converged = FALSE on a small
    fraction of well conditioned problems. Close to the solution the
    objective f = tr(exp(A)) - sum(x) is flat to within cancellation, so
    the Armijo test carries no information; the line search then
    exhausted all of its halvings at every iteration, the fixed-point
    fallback was taken instead, and the error could lock at a constant
    value several orders of magnitude above the attainable floor until
    maxit was reached. Two safeguards that inv_gft() already used have
    been added: the full Newton step is now taken untested once the
    predicted decrease falls below the floating-point resolution of f,
    and a persistent lack of progress near the rounding floor hands the
    iteration to the (contractive) fixed point.
    
    In a sweep over random correlation matrices at n = 10, the failure
    rate falls from about 5% to 0, and the worst-case cost from 12,375
    eigendecompositions to 6.
    
    The defect was present on all platforms and is not specific to any
    BLAS or LAPACK build; it surfaced on CRAN's ATLAS check because that
    arithmetic moved one test matrix into the affected set.

  - inv_gft(), inv_gft_fp() and inv_gft_broyden() are unchanged. Their
    results are unaffected by this release.

Documentation

  - Removed the single quotes around acronyms and author names in
    DESCRIPTION, as requested by the CRAN reviewer. Single quotes are
    now used only for software names.