surveycore 1.0.0

First stable release

surveycore 1.0.0 is the first stable API release. The full set of survey
design types (Taylor series linearization, replicate weights, two-phase,
non-probability), variance estimators, analysis functions (means, totals,
frequencies, quantiles, ratios, correlations, regression, t-tests, ANOVA,
effective sample size), the metadata system, and calibration-adjusted variance
are now complete and stable.

New features

• as_survey_nonprob() now accepts jackknife replicate schemes via
  type = "JK1", "JK2", and "JKn". All get_*() estimation functions
  dispatch to jackknife variance when a survey_nonprob design carries
  jackknife replicate weights. print() displays the replicate type and count
  for jackknife designs. (#133–#136)

• survey_glm() now routes survey_nonprob designs that carry bootstrap
  replicate weights through the replicate-weight variance estimator, matching
  the behaviour of all other get_*() functions for such designs. (#138)

• New dataset ca_api_2000: the 2000 California Academic Performance Index
  (API) survey, structured as a simple random sample from California schools.
  Used as a primary example for survey_taylor SRS designs throughout the
  documentation and vignettes. (#146)

Bug fixes

• get_diffs(): fixed a regex metacharacter injection when variable names
  contained special characters (., *, ?, etc.), and fixed pct_change
  returning NA for some group configurations. (#145)

• Fixed six print/dispatch/error bugs (B1–B6) uncovered during a documentation
  audit: print.survey_nonprob no longer errors on designs with no repweights
  set; dispatch errors now surface the correct class name in message text; three
  error classes that were raised but never registered have been registered.
  (#143)

Documentation

• Corrected roxygen text, stale cross-references, contradictory @tags, and
  mismatched @section headings across 40+ R files (D1–D75). (#143–#144)

• The non-probability estimation vignette section has been rewritten with a
  complete bootstrap variance example using as_survey_nonprob() with
  repweights.