Changes in version 1.2-0                        

Bug fixes (vs the unreleased 1.2-0 RC1 from earlier in this development cycle)

  - synth_inference() and generate_placebos() previously classified any
    plot-horizon year not in time.optimize.ssr as post-treatment. This
    silently mixed pre-treatment plot years before the SSR window
    (e.g. 1955-1959 in the Basque example with time.optimize.ssr
    = 1960:1969) into the post-period denominator, inflating post_mspe,
    mspe_ratio, and the mspe_test() p-value. Both now classify post as
    time.plot >= treatment_time, with the default treatment_time =
    max(time.optimize.ssr) + 1. A new treatment_time argument lets users
    override.

  - synth_inference(method = "conformal") now uses the order statistic
    at rank k = ceiling((n + 1) * (1 - alpha)) instead of quantile(.., 1
    - alpha, type = 1). The former is the rank that delivers exact
    finite-sample (1 - alpha) coverage under exchangeability; the latter
    selects rank ceiling(n * (1 - alpha)) and slightly under-covers.
    When n is too small for the requested coverage, the function now
    warns and returns Inf for conformal_q instead of silently using the
    maximum residual.

New arguments wired through synth() and generate_placebos()

  - synth() now accepts cvxr_pars and torch_pars lists for tuning the
    quadopt = "cvxr" and quadopt = "torch" backends (e.g. torch_pars =
    list(device = "mps") for Apple Silicon GPU). These were supported
    internally by .solve_w() but were not previously exposed at the
    public API.

  - generate_placebos() now exposes genoud, cvxr_pars, torch_pars, and
    treatment_time. Match these to the configuration that produced the
    real fit so placebos use the same optimizer and the same post-period
    definition.

New: post-period inference

  - synth_inference() returns a prediction band around the synthetic
    counterfactual. Two methods are available:
    
      - method = "conformal" (default) — split-conformal intervals
        (Chernozhukov, Wuthrich, Zhu 2021), finite-sample valid under
        exchangeability of pre-period residuals. Half-width is the (1 -
        alpha)-quantile of |gap_pre|.
      - method = "parametric" — Gaussian-residual intervals. Half-width
        is qnorm(1 - alpha/2) * sd(gap_pre).
    
    Output is an S3 object of class c("synth_<method>",
    "synth_inference") with print() and plot() methods. The plot()
    method overlays the band on the treated and synthetic series.

  - generate_placebos(), mspe_test(), mspe_plot(), plot_placebos()
    implement the in-space placebo workflow from Abadie, Diamond, and
    Hainmueller (2010). generate_placebos() swaps each donor into the
    treated slot, refits synth(), and returns a synth_placebos object.
    mspe_test() returns a one-sided p-value via the empirical rank of
    the treated unit's post/pre MSPE ratio. The function names match
    those in the SCtools package by design — migration is a verbatim
    rename and you can namespace-qualify (e.g.,
    Synth::generate_placebos) if both packages are loaded.

  - No new package dependencies. Optional parallel = TRUE in
    generate_placebos() uses parallel::mclapply on non-Windows.

Validity caveats

  - Both prediction-interval methods produce constant-width bands and do
    not separately quantify in-sample uncertainty about the synthetic
    weights. Users who need period-varying intervals or in-sample/
    out-of-sample uncertainty decomposition should see the scpi package
    (Cattaneo, Feng, Palomba, Titiunik).
  - Conformal validity is exact under exchangeability of pre-period
    residuals; parametric validity assumes i.i.d. Gaussian residuals.
    Both are approximate when outcomes are autocorrelated.

Optional alternative QP backends

  - synth() and fn.V() gain two new opt-in values for quadopt:
    
      - quadopt = "cvxr" solves the W-step via the CVXR package (default
        solver: OSQP, a hard Imports of CVXR and therefore always
        available; alternative solvers "SCS", "ECOS", or "MOSEK" can be
        selected via cvxr_pars). Adds no required dependency; CVXR lives
        in Suggests: and is loaded only when requested.
      - quadopt = "torch" solves the W-step via Frank-Wolfe simplex
        least squares using the torch package, with optional GPU/MPS
        support (torch_pars = list(device = "cuda") or "mps"). Also in
        Suggests:. The first use of torch in a session may require
        torch::install_torch() to download libtorch.
    
    quadopt = "ipop" remains the default and produces output identical
    to <= 1.1-10. The new backends agree with ipop on the canonical
    examples to within solver tolerance and exist for users with larger
    panels who prefer modern convex-optimization solvers (CVXR) or
    autodiff/GPU machinery (torch). See the ?synth Details section and
    the inference vignette for guidance on choosing a backend.

  - New quadopt_inner and quadopt_outer arguments on synth() and
    generate_placebos() let users pick different backends for the two QP
    stages. The V-search calls fn.V() hundreds of times via optimx;
    running CVXR or torch on every call is much slower than ipop.
    Setting quadopt_outer = "cvxr" (or "torch") with quadopt left at
    "ipop" gives ipop's speed for the V-search and uses the modern
    solver only for the single final W solve. Existing scripts that pass
    quadopt = ... are unchanged: it now sets both quadopt_inner and
    quadopt_outer.

First S3 dispatch in the package

  - This release introduces S3 method dispatch (print, plot) for the new
    synth_inference and synth_placebos classes. Existing functions
    (synth, dataprep, path.plot, gaps.plot, synth.tab, etc.) are
    unchanged in behavior and signature.

                 Changes in version 1.1-10 (2026-04-29)                 

Bug fixes

  - synth() and fn.V(): quadopt = "LowRankQP" no longer falls through to
    undefined-variable code. The deprecation message is now raised via
    stop() rather than cat(), which matches the user's expectation that
    the function fails fast on an unsupported option.

  - dataprep(): the missing-data warning loop in the X0 (control
    predictors) section now iterates over nrow(X0) instead of nrow(X1).
    Previously it covered only the first length(time.predictors.prior)
    rows, missing roughly (n_controls - 1) / n_controls of the cells.

  - synth(): the error message for ncol(Z0) < 2 no longer mentions
    "specify only one treated unit" (it is checking for at least two
    control units).

  - path.plot(): Ylim is now padded by a fraction of the data range, not
    by 0.3 * Y.min. The old formula gave 0.7 * Y.min for negative Y.min,
    which moved the lower bound toward zero and cropped the bottom of
    negative-valued series.

Quiet by default

  - synth(): messages such as "X1, X0, Z1, Z0 all come directly from
    dataprep object", "searching for synthetic control unit", and the
    final summary block printing MSPE (LOSS V) and the solution vectors
    are now gated by verbose = TRUE. With the default verbose = FALSE,
    synth() runs silently. Set verbose = TRUE to restore the previous
    chatter.

Documentation / cleanup (no user-visible change)

  - Removed dead commented-out collinearity check in synth.R.
  - Removed an unreachable is.vector(X0.scaled) defensive branch in
    synth.R (ncol(X0) < 2 errors out earlier).
  - Several typos fixed in error messages: "\ Please..." → "\n
    Please...", "specificy" → "specify", "on time period" → "one time
    period", "at least on predictor" → "at least one predictor",
    "variabale" → "variable", "mispecified" → "misspecified",
    "supoorted" → "supported", "synthtic" → "synthetic".
  - synth() and fn.V(): cleaned up the unsupported-quadopt branch (also
    clarifies error messages).