Changes in version 0.1.2 (2026-02-05)                  

  - Bootstrap replicate evaluation backend is now configurable via
    options(nmar.bootstrap_apply = "auto"|"base"|"future"). Default
    bootstrap behavior (nmar.bootstrap_apply = "auto") uses
    base::lapply() unless the current future plan has more than one
    worker; if so, it uses future.apply::future_lapply(future.seed =
    TRUE) when available.
  - Exptilt validation now rejects non-finite values (e.g., Inf, -Inf)
    in covariates (and non-finite observed outcomes).

                 Changes in version 0.1.1 (2026-01-16)                  

  - CRAN release-related fixes

  - Fix return roxygen keyword in S3 Functions
  - Add research doi references to DESCRIPTION file

                        Changes in version 0.1.0                        

Initial CRAN Release

  - First release of the NMAR package for estimating nonignorable
    nonresponse (NMAR) bias in survey data.

Methods

  - Empirical Likelihood (EL): Added el_engine() implementing the
    estimator of Qin, Leung, and Shao (2002). This method uses empirical
    likelihood weights satisfying response mechanism equations and
    auxiliary moment constraints.
  - Exponential Tilting (Parametric & Nonparametric): Included robust
    implementations for both microdata (exptilt_engine) and aggregated
    contingency tables (exptilt_nonparam_engine) based on Riddles, Kim,
    and Im (2016).

Key Features

  - Unified API: All estimators are accessible via a single, consistent
    nmar() interface supporting standard formula syntax (e.g., Y ~ X |
    Z).
  - Complex Survey Support: Seamless integration with the survey
    package. nmar() accepts survey.design objects, automatically
    handling weights and stratification.
  - Variance Estimation: Robust bootstrapping (S3) implementation for
    standard errors and confidence intervals across all engines.
  - Diagnostics: Rich return objects including convergence statistics,
    Jacobian condition numbers, and detailed weight summaries.

Major Changes

  - Refactored Architecture: The exptilt and el engines share a unified
    structural design, ensuring consistent behavior for controls,
    standardization, and error handling.
  - Standardization: Added standardize = TRUE argument to engines to
    improve numerical stability during optimization.