diff --git a/NEWS.md b/NEWS.md
index 03f5a1a..20e71d0 100644
--- a/NEWS.md
+++ b/NEWS.md
@@ -2,8 +2,17 @@
 
 ### Enhancements
 
-* Add `pareto_smooth` option to `weight_draws`, to Pareto smooth
+* Add `exclude` option to `subset_draws()`, which can be used to exclude
+  the matched selection.
+* Add `are_log_weights` option to `pareto_smooth()`, which is necessary
+  for correct Pareto smoothing computation if the input vector
+  consists of log weights.
+* Add `pareto_smooth` option to `weight_draws()`, to Pareto smooth
   weights before adding to a draws object.
+* Add individual Pareto diagnostic functions (`pareto_khat()`,
+  `pareto_khat_threshold()`, `pareto_min_ss()`, `pareto_convergence_rate()`)
+* `thin_draws()` now automatically thins draws based on ESS by default,
+  and non-integer thinning is possible.
 * Matrix multiplication of `rvar`s can now be done with the base matrix 
   multiplication operator (`%*%`) instead of `%**%` in R >= 4.3.
 * `variables()`, `variables<-()`, `set_variables()`, and `nvariables()` now
diff --git a/R/pareto_smooth.R b/R/pareto_smooth.R
index e5f1aff..dca53cc 100644
--- a/R/pareto_smooth.R
+++ b/R/pareto_smooth.R
@@ -250,7 +250,7 @@ pareto_smooth.rvar <- function(x, return_k = FALSE, extra_diags = FALSE, ...) {
 #' @export
 pareto_smooth.default <- function(x,
                                   tail = c("both", "right", "left"),
-                                  r_eff = 1,
+                                  r_eff = NULL,
                                   ndraws_tail = NULL,
                                   return_k = FALSE,
                                   extra_diags = FALSE,
diff --git a/R/rvar-.R b/R/rvar-.R
index 33db28f..a74e42c 100755
--- a/R/rvar-.R
+++ b/R/rvar-.R
@@ -800,6 +800,13 @@ drop_chain_dim <- function(x) {
 #' (first one is draws), etc.
 #' @noRd
 cleanup_rvar_draws <- function(x) {
+  assert(
+    check_numeric(x),
+    check_logical(x),
+    check_factor(x),
+    check_character(x)
+  )
+
   if (length(x) == 0) {
     # canonical NULL rvar is at least 1 draw of nothing
     # this ensures that (e.g.) extending a null rvar
diff --git a/man-roxygen/args-pareto.R b/man-roxygen/args-pareto.R
index 92e0937..488e60b 100644
--- a/man-roxygen/args-pareto.R
+++ b/man-roxygen/args-pareto.R
@@ -15,7 +15,7 @@
 #'   al. (2024)).
 #' @param r_eff (numeric) relative effective sample size estimate. If
 #'   `r_eff` is NULL, it will be calculated assuming the draws are
-#'   from MCMC. Default is 1.
+#'   from MCMC. Default is NULL.
 #' @param verbose (logical) Should diagnostic messages be printed? If
 #'   `TRUE`, messages related to Pareto diagnostics will be
 #'   printed. Default is `FALSE`.
diff --git a/man/pareto_diags.Rd b/man/pareto_diags.Rd
index 7e4f1d3..31420b9 100644
--- a/man/pareto_diags.Rd
+++ b/man/pareto_diags.Rd
@@ -68,7 +68,7 @@ The default is \code{"both"}.}
 
 \item{r_eff}{(numeric) relative effective sample size estimate. If
 \code{r_eff} is NULL, it will be calculated assuming the draws are
-from MCMC. Default is 1.}
+from MCMC. Default is NULL.}
 
 \item{ndraws_tail}{(numeric) number of draws for the tail. If
 \code{ndraws_tail} is not specified, it will be calculated as
@@ -134,8 +134,8 @@ pareto_diags(d$Sigma)
 \references{
 Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao and
 Jonah Gabry (2024). Pareto Smoothed Importance Sampling.
-\emph{Journal of Machine Learning Research}. 25(72), 1-58.
-https://jmlr.org/papers/v25/19-556.html
+\emph{Journal of Machine Learning Research}, 25(72):1-58.
+\href{https://jmlr.org/papers/v25/19-556.html}{PDF}
 }
 \seealso{
 \code{\link{pareto_khat}} for only calculating khat, and
diff --git a/man/pareto_khat.Rd b/man/pareto_khat.Rd
index 96d0ad2..9df455d 100644
--- a/man/pareto_khat.Rd
+++ b/man/pareto_khat.Rd
@@ -41,7 +41,7 @@ The default is \code{"both"}.}
 
 \item{r_eff}{(numeric) relative effective sample size estimate. If
 \code{r_eff} is NULL, it will be calculated assuming the draws are
-from MCMC. Default is 1.}
+from MCMC. Default is NULL.}
 
 \item{ndraws_tail}{(numeric) number of draws for the tail. If
 \code{ndraws_tail} is not specified, it will be calculated as
@@ -76,8 +76,8 @@ pareto_khat(d$Sigma)
 \references{
 Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao and
 Jonah Gabry (2024). Pareto Smoothed Importance Sampling.
-\emph{Journal of Machine Learning Research}. 25(72), 1-58.
-https://jmlr.org/papers/v25/19-556.html
+\emph{Journal of Machine Learning Research}, 25(72):1-58.
+\href{https://jmlr.org/papers/v25/19-556.html}{PDF}
 }
 \seealso{
 \code{\link{pareto_diags}} for additional related diagnostics, and
diff --git a/man/pareto_smooth.Rd b/man/pareto_smooth.Rd
index 0f15882..d89b1ab 100644
--- a/man/pareto_smooth.Rd
+++ b/man/pareto_smooth.Rd
@@ -13,7 +13,7 @@ pareto_smooth(x, ...)
 \method{pareto_smooth}{default}(
   x,
   tail = c("both", "right", "left"),
-  r_eff = 1,
+  r_eff = NULL,
   ndraws_tail = NULL,
   return_k = FALSE,
   extra_diags = FALSE,
@@ -53,7 +53,7 @@ The default is \code{"both"}.}
 
 \item{r_eff}{(numeric) relative effective sample size estimate. If
 \code{r_eff} is NULL, it will be calculated assuming the draws are
-from MCMC. Default is 1.}
+from MCMC. Default is NULL.}
 
 \item{ndraws_tail}{(numeric) number of draws for the tail. If
 \code{ndraws_tail} is not specified, it will be calculated as
@@ -94,8 +94,8 @@ pareto_smooth(d$Sigma)
 \references{
 Aki Vehtari, Daniel Simpson, Andrew Gelman, Yuling Yao and
 Jonah Gabry (2024). Pareto Smoothed Importance Sampling.
-\emph{Journal of Machine Learning Research}. 25(72), 1-58.
-https://jmlr.org/papers/v25/19-556.html
+\emph{Journal of Machine Learning Research}, 25(72):1-58.
+\href{https://jmlr.org/papers/v25/19-556.html}{PDF}
 }
 \seealso{
 \code{\link{pareto_khat}} for only calculating khat, and