minor changes all over to pass checks

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,

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)

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"

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")

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)

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)