Changes in version 0.1.0.9001                      

spexvb 0.1.0.9001

Output

  - spexvb() now returns sigma, the slab posterior standard deviation of
    each coefficient (length p). The marginal posterior SD of beta_j is
    sqrt(omega*sigma^2 + omega*(1 - omega)*mu^2).

Fixes

  - get.initials() now respects a user-supplied tau_e instead of always
    re-estimating it, so a known error precision is held fixed (as the
    documentation already stated). The algorithm is unchanged.

spexvb 0.1.0.9000

Performance

  - Hoisted iteration-constant computations (sigma, log-odds, sqrt(tau_b
    * tau_e)) out of coordinate-ascent inner loops in all three C++
    backends (fit_linear_alpha_remap, fit_linear_gamma_hierarchy,
    fit_logistic_alpha_remap).
  - Replaced O(np) post-remapping matrix-vector product (W = X *
    approx_mean) with O(n) scalar multiply (W *= alpha).
  - Vectorized entropy(), replaced std::pow(x, 2) with x * x, reused
    precomputed X_2 in the logistic backend, and removed dead
    allocations.
  - R side: direct C++ function calls instead of do.call() string
    lookup, eliminated redundant lapply copy in return list, reduced
    standardization from two scale() passes to one via Var = E[X^2] -
    E[X]^2.
  - Measured 24--33% speedup on moderate to high-p settings with
    identical coefficients (within tolerance 1e-8) and zero iteration
    count changes.

spexvb 0.1.0

  - Initial CRAN release.
  - Implements spexvb() (linear PX-VB), hspvb() (hierarchical Gamma
    prior), and spexvb.logistic() (logistic PX-VB) for high-dimensional
    variable selection with spike-and-slab priors.
  - Cross-validation via cv.spexvb() and cv.spexvb.fit() with parallel
    support through foreach.