Migrate parallel computing in as.sir() from parallel:: to future/future.apply

Replace parallel::mclapply() and parallel::parLapply() with
future.apply::future_lapply(), enabling transparent support for any
future backend (multisession, multicore, mirai_multisession, cluster)
on all platforms including Windows.

When parallel = TRUE the function now: (1) respects an active
future::plan() set by the user without overriding it on exit, or
(2) sets a temporary multisession plan with parallelly::availableCores()
and tears it down on exit. The max_cores argument controls worker count
only when no user plan is active.

future and future.apply are added to Suggests in DESCRIPTION.

https://claude.ai/code/session_01M1Jvf2Miu6JL4TQrEh1wS8

man/g.test.Rd

@@ -45,9 +45,8 @@ A list with class \code{"htest"} containing the following
   \item{residuals}{the Pearson residuals,
     \code{(observed - expected) / sqrt(expected)}.}
   \item{stdres}{standardized residuals,
-    \code{(observed - expected) / sqrt(V)}, where \code{V} is the
-    residual cell variance (Agresti, 2007, section 2.4.5
-    for the case where \code{x} is a matrix, \code{n * p * (1 - p)} otherwise).}
+    \code{(observed - expected) / sqrt(V)}, where \code{V} is the residual cell variance (Agresti, 2007,
+    section 2.4.5 for the case where \code{x} is a matrix, \code{n * p * (1 - p)} otherwise).}
 }
 \description{
 \code{\link[=g.test]{g.test()}} performs chi-squared contingency table tests and goodness-of-fit tests, just like \code{\link[=chisq.test]{chisq.test()}} but is more reliable (1). A \emph{G}-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a \strong{\emph{G}-test of goodness-of-fit}), or to see whether the proportions of one variable are different for different values of the other variable (called a \strong{\emph{G}-test of independence}).