diff --git a/DESCRIPTION b/DESCRIPTION
index a6424d87f..0cb6491bd 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: DemoTools
 Type: Package
 Title: Standardize, Evaluate, and Adjust Demographic Data
-Version: 01.10.05
+Version: 01.11.000
 Date: 2021-01-03
 Authors@R: c(
    person("Tim", "Riffe", role = c("aut", "cre"), 
@@ -31,8 +31,7 @@ Suggests:
     knitr,
     rmarkdown,
     DT,
-    ggplot2,
-    bibtex (>= 0.4.2)
+    ggplot2
 RdMacros: Rdpack
 Imports:
     demogR,
diff --git a/NAMESPACE b/NAMESPACE
index 65b810e14..5975afed5 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -5,6 +5,7 @@ export(ADM)
 export(AGEN)
 export(ID)
 export(IRD)
+export(OPAG)
 export(OPAG_fit_stable_standard)
 export(OPAG_nLx_warp_r)
 export(OPAG_r_min)
@@ -35,6 +36,7 @@ export(check_heaping_spoorenberg)
 export(check_heaping_whipple)
 export(dec.date)
 export(downloadSRB)
+export(downloadnLx)
 export(getModelLifeTable)
 export(graduate)
 export(graduate_beers)
@@ -132,6 +134,7 @@ import(Rcpp)
 import(Rdpack)
 import(demogR)
 importFrom(MortalityLaws,MortalityLaw)
+importFrom(Rdpack,reprompt)
 importFrom(demogR,cdmltw)
 importFrom(dplyr,group_by)
 importFrom(dplyr,mutate)
diff --git a/R/DemoTools-package.R b/R/DemoTools-package.R
index 0fe9ce5c9..cc1995855 100644
--- a/R/DemoTools-package.R
+++ b/R/DemoTools-package.R
@@ -6,6 +6,7 @@
 #' @import Rcpp
 #' @importFrom MortalityLaws MortalityLaw
 #' @importFrom stats coef predict
+#' @importFrom Rdpack reprompt
 #' @name DemoTools-package
 #' @docType package
 "_PACKAGE"
diff --git a/R/OPAG.R b/R/OPAG.R
index 0f17ab8ab..1d1afb151 100644
--- a/R/OPAG.R
+++ b/R/OPAG.R
@@ -118,7 +118,7 @@ OPAG_simple    <-
 #' @param Age interger vector of lower bounds of age groups of `nLx`
 #' @param r stable growth rate
 #' @param AgeInt optional integer vector of widths of age groups, inferred if not given.
-#' @param continous logical. If `TRUE` we use the growth adjustment. `e^(-age*r)`. If `FALSE` we assume `r` is geometric growth, and we use `(1+r)^age` for the growth adjustment.
+#' @param continuous logical. If `TRUE` we use the growth adjustment. `e^(-age*r)`. If `FALSE` we assume `r` is geometric growth, and we use `(1+r)^age` for the growth adjustment.
 #' @param method character, graduation method used for intermediate graduation. Default `"uniform"`. Other reasonable choices include `"mono"` or `"pclm"`.
 #' @return numeric vector of the transformed `nLx`. Note, this vector sums to `1`. 
 #' @export
@@ -173,13 +173,13 @@ OPAG_nLx_warp_r <- function(nLx,
 #' @param nLx numeric vector of stable population standard
 #' @param Age_nLx  integer vector of lower bounds for age groups of `nLx`
 #' @param AgeInt_nLx optional integer vector of widths of age groups of `nLx`, inferred if not given. 
-#' @param continous logical. If `TRUE` we use the growth adjustment. `e^(-age*r)`. If `FALSE` we assume `r` is geometric growth, and we use `(1+r)^age` for the growth adjustment.
+#' @param continuous logical. If `TRUE` we use the growth adjustment. `e^(-age*r)`. If `FALSE` we assume `r` is geometric growth, and we use `(1+r)^age` for the growth adjustment.
 #' @param method character. Graduation method, default `"uniform"`. `"mono"` or `"pclm"` would also be good choices.
 #' @return numeric. A residual that you're presumably trying to minimize.
 #' @export
 
 #' @examples
-#' Make up some population data to fit to:
+#' # Make up some population data to fit to:
 #' Pop_fit    <- c(85000,37000)
 #' Age_fit    <- c(70,80)
 #' AgeInt_fit <- c(10,10)
@@ -386,8 +386,11 @@ OPAG_fit_stable_standard <- function(Pop_fit,
 #' @param Pop numeric vector of population counts
 #' @param Age_Pop integer vector of the lower bounds of the population age groups
 #' @param AgeInt_Pop integer vector of the population age group interval widths, using `Inf` for the open age group.
-
-#'India Males, 1991
+#' @param Redistribute_from integer lower age bound that forms the cutoff, above which we redistribute counts using the stable standard.
+#' @param OAnew integer. Desired open age group in the output (must being element of `Age_nLx`)
+#' @export
+#' @examples
+#' # India Males, 1991
 #' Pop            <- smooth_age_5(pop1m_ind,
 #'                          Age = 0:100,
 #'                          method = "Arriaga")
diff --git a/R/basepop.R b/R/basepop.R
index 6b6a006a1..664cf2c2e 100644
--- a/R/basepop.R
+++ b/R/basepop.R
@@ -850,8 +850,17 @@ lt_infer_radix_from_1L0 <- function(L0){
   the_radix
 }
 
-# TR: radix removed, as it seems lx was 1 but nLx was based on 1e5...
-# will use indirect inference.
+#' Extract Lx estimates from WPP2019
+#' @description We use the `FetchLifeTableWpp2019` function of the `fertestr` to extract `Lx` from `wpp2019`, interpolated to an exact date.
+#' @param nLx either `NULL` or a numeric vector of lifetable exposure. If it's the second then we just pass it back.
+#' @param country character country name available UN Pop Div `LocName` set
+#' @param gender `"male"`, `"female"`, or `"both"`
+#' @param nLxDatesIn numeric vector of three decimal dates produced by (or passed through) `basepop_ive()`
+#'
+#' @return numeric matrix of `nLx` with `length(nLxDatesIn)` and abrdiged ages in rows.
+#' @export
+#'
+#' @importFrom rlang .data
 downloadnLx <- function(nLx, country, gender, nLxDatesIn) {
   requireNamespace("fertestr", quietly = TRUE)
   requireNamespace("magrittr", quietly = TRUE)
diff --git a/README.md b/README.md
index 762fcd41f..808bb0681 100644
--- a/README.md
+++ b/README.md
@@ -4,7 +4,7 @@
 
 ![R CMD Check via {tic}](https://github.com/timriffe/DemoTools/workflows/R%20CMD%20Check%20via%20%7Btic%7D/badge.svg)
 [![codecov](https://codecov.io/gh/timriffe/DemoTools/branch/master/graph/badge.svg)](https://codecov.io/gh/timriffe/DemoTools) 
-[![](https://img.shields.io/badge/devel%20version-01.10.05-yellow.svg)](https://github.com/timriffe/DemoTools)
+[![](https://img.shields.io/badge/devel%20version-01.11.000-yellow.svg)](https://github.com/timriffe/DemoTools)
 [![issues](https://img.shields.io/github/issues-raw/timriffe/DemoTools.svg)](https://github.com/timriffe/DemoTools/issues)
 [![lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
 
diff --git a/man/OPAG.Rd b/man/OPAG.Rd
index c95c6aa5b..8066e73ac 100644
--- a/man/OPAG.Rd
+++ b/man/OPAG.Rd
@@ -24,38 +24,7 @@ OPAG(
 
 \item{Age_Pop}{integer vector of the lower bounds of the population age groups}
 
-\item{AgeInt_Pop}{integer vector of the population age group interval widths, using \code{Inf} for the open age group.
-India Males, 1991
-Pop            <- smooth_age_5(pop1m_ind,
-Age = 0:100,
-method = "Arriaga")
-Age_Pop        <- names2age(Pop)
-AgeInt_Pop     <- age2int(Age_Pop, OAvalue = 1)
-
-nLx            <- downloadnLx(NULL, "India","male",1991)
-Age_nLx        <- names2age(nLx)
-AgeInt_nLx     <- age2int(Age_nLx, OAvalue = 1)
-
-Pop_fit <- OPAG(Pop,
-Age_Pop = Age_Pop,
-AgeInt_Pop = AgeInt_Pop,
-nLx = nLx,
-Age_nLx = Age_nLx,
-AgeInt_nLx,
-Age_fit =  c(60,70),
-AgeInt_fit = c(10,10),
-Redistribute_from = 80)
-
-\dontrun{
-# look at 75+
-ind <- Age_Pop >= 75
-plot(Age_Pop[ind], Pop[ind])
-lines(Age_Pop[ind], Pop_fit$Pop_out[ind], col = "blue")
-
-# relative differences in ages 80+
-ind <- Age_Pop >= 80
-plot(Age_Pop[ind],  (Pop_fit$Pop_out[ind] - Pop[ind]) / Pop[ind])
-}}
+\item{AgeInt_Pop}{integer vector of the population age group interval widths, using \code{Inf} for the open age group.}
 
 \item{nLx}{numeric vector of stable population standard}
 
@@ -67,7 +36,13 @@ plot(Age_Pop[ind],  (Pop_fit$Pop_out[ind] - Pop[ind]) / Pop[ind])
 
 \item{AgeInt_fit}{integer vector of widths of age groups of \code{Pop_fit}}
 
+\item{Redistribute_from}{integer lower age bound that forms the cutoff, above which we redistribute counts using the stable standard.}
+
+\item{OAnew}{integer. Desired open age group in the output (must being element of \code{Age_nLx})}
+
 \item{method}{character. Graduation method, default \code{"uniform"}. \code{"mono"} or \code{"pclm"} would also be good choices.}
+
+\item{continuous}{logical. If \code{TRUE} we use the growth adjustment. \code{e^(-age*r)}. If \code{FALSE} we assume \code{r} is geometric growth, and we use \code{(1+r)^age} for the growth adjustment.}
 }
 \description{
 This can be used as an external check of population counts
@@ -96,3 +71,36 @@ it ahead of time. For this, you'd want the \code{nMx} the underly it, and you
 can use \code{lt_abridged()}, specifying a higher open age, and then
 extracting \code{nLx} again from it.
 }
+\examples{
+# India Males, 1991
+Pop            <- smooth_age_5(pop1m_ind,
+                         Age = 0:100,
+                         method = "Arriaga")
+Age_Pop        <- names2age(Pop)
+AgeInt_Pop     <- age2int(Age_Pop, OAvalue = 1) 
+
+nLx            <- downloadnLx(NULL, "India","male",1991)
+Age_nLx        <- names2age(nLx)
+AgeInt_nLx     <- age2int(Age_nLx, OAvalue = 1)
+
+Pop_fit <- OPAG(Pop, 
+    Age_Pop = Age_Pop, 
+    AgeInt_Pop = AgeInt_Pop,
+    nLx = nLx,
+    Age_nLx = Age_nLx,
+    AgeInt_nLx,
+    Age_fit =  c(60,70),
+    AgeInt_fit = c(10,10),
+    Redistribute_from = 80)
+
+\dontrun{
+# look at 75+
+ind <- Age_Pop >= 75
+plot(Age_Pop[ind], Pop[ind])
+lines(Age_Pop[ind], Pop_fit$Pop_out[ind], col = "blue")
+
+# relative differences in ages 80+
+ind <- Age_Pop >= 80
+plot(Age_Pop[ind],  (Pop_fit$Pop_out[ind] - Pop[ind]) / Pop[ind])
+}
+}
diff --git a/man/OPAG_fit_stable_standard.Rd b/man/OPAG_fit_stable_standard.Rd
index 0850762a5..187847e82 100644
--- a/man/OPAG_fit_stable_standard.Rd
+++ b/man/OPAG_fit_stable_standard.Rd
@@ -29,6 +29,8 @@ OPAG_fit_stable_standard(
 \item{AgeInt_nLx}{optional integer vector of widths of age groups of \code{nLx}, inferred if not given.}
 
 \item{method}{character. Graduation method, default \code{"uniform"}. \code{"mono"} or \code{"pclm"} would also be good choices.}
+
+\item{continuous}{logical. If \code{TRUE} we use the growth adjustment. \code{e^(-age*r)}. If \code{FALSE} we assume \code{r} is geometric growth, and we use \code{(1+r)^age} for the growth adjustment.}
 }
 \value{
 list constaining
diff --git a/man/OPAG_nLx_warp_r.Rd b/man/OPAG_nLx_warp_r.Rd
index 064b9349d..f12537911 100644
--- a/man/OPAG_nLx_warp_r.Rd
+++ b/man/OPAG_nLx_warp_r.Rd
@@ -22,9 +22,9 @@ OPAG_nLx_warp_r(
 
 \item{AgeInt}{optional integer vector of widths of age groups, inferred if not given.}
 
-\item{method}{character, graduation method used for intermediate graduation. Default \code{"uniform"}. Other reasonable choices include \code{"mono"} or \code{"pclm"}.}
+\item{continuous}{logical. If \code{TRUE} we use the growth adjustment. \code{e^(-age*r)}. If \code{FALSE} we assume \code{r} is geometric growth, and we use \code{(1+r)^age} for the growth adjustment.}
 
-\item{continous}{logical. If \code{TRUE} we use the growth adjustment. \code{e^(-age*r)}. If \code{FALSE} we assume \code{r} is geometric growth, and we use \code{(1+r)^age} for the growth adjustment.}
+\item{method}{character, graduation method used for intermediate graduation. Default \code{"uniform"}. Other reasonable choices include \code{"mono"} or \code{"pclm"}.}
 }
 \value{
 numeric vector of the transformed \code{nLx}. Note, this vector sums to \code{1}.
diff --git a/man/OPAG_r_min.Rd b/man/OPAG_r_min.Rd
index 0bf35e74a..615f48306 100644
--- a/man/OPAG_r_min.Rd
+++ b/man/OPAG_r_min.Rd
@@ -31,9 +31,9 @@ OPAG_r_min(
 
 \item{AgeInt_nLx}{optional integer vector of widths of age groups of \code{nLx}, inferred if not given.}
 
-\item{method}{character. Graduation method, default \code{"uniform"}. \code{"mono"} or \code{"pclm"} would also be good choices.}
+\item{continuous}{logical. If \code{TRUE} we use the growth adjustment. \code{e^(-age*r)}. If \code{FALSE} we assume \code{r} is geometric growth, and we use \code{(1+r)^age} for the growth adjustment.}
 
-\item{continous}{logical. If \code{TRUE} we use the growth adjustment. \code{e^(-age*r)}. If \code{FALSE} we assume \code{r} is geometric growth, and we use \code{(1+r)^age} for the growth adjustment.}
+\item{method}{character. Graduation method, default \code{"uniform"}. \code{"mono"} or \code{"pclm"} would also be good choices.}
 }
 \value{
 numeric. A residual that you're presumably trying to minimize.
@@ -47,7 +47,7 @@ This is a utiltiy function for \code{OPAG()}, which needs to optimize $r$ for a
 given population vector and stationary standard.
 }
 \examples{
-Make up some population data to fit to:
+# Make up some population data to fit to:
 Pop_fit    <- c(85000,37000)
 Age_fit    <- c(70,80)
 AgeInt_fit <- c(10,10)
diff --git a/man/downloadnLx.Rd b/man/downloadnLx.Rd
new file mode 100644
index 000000000..d1f455696
--- /dev/null
+++ b/man/downloadnLx.Rd
@@ -0,0 +1,23 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/basepop.R
+\name{downloadnLx}
+\alias{downloadnLx}
+\title{Extract Lx estimates from WPP2019}
+\usage{
+downloadnLx(nLx, country, gender, nLxDatesIn)
+}
+\arguments{
+\item{nLx}{either \code{NULL} or a numeric vector of lifetable exposure. If it's the second then we just pass it back.}
+
+\item{country}{character country name available UN Pop Div \code{LocName} set}
+
+\item{gender}{\code{"male"}, \code{"female"}, or \code{"both"}}
+
+\item{nLxDatesIn}{numeric vector of three decimal dates produced by (or passed through) \code{basepop_ive()}}
+}
+\value{
+numeric matrix of \code{nLx} with \code{length(nLxDatesIn)} and abrdiged ages in rows.
+}
+\description{
+We use the \code{FetchLifeTableWpp2019} function of the \code{fertestr} to extract \code{Lx} from \code{wpp2019}, interpolated to an exact date.
+}