jschoeley

#' ---
#' title: Different legend styles for centered ternary color scales
#' author: Jonas Schöley, Ilya Kashnitsky
#' output:
#'   pdf_document
#' ---

#+echo=FALSE
knitr::opts_chunk$set(warning=FALSE, message=FALSE,
                      fig.width = 15, fig.height = 15)

jschoeley

# BUBBLE-GRID-MAPS
# Jonas Schöley (cc-by)

library(eurostat)  # eurostat data
library(tidyverse) # tidy data transformation
library(lubridate) # date and time support
library(sf)        # simple features GIS

# download eurostat data of population counts by NUTS-3 region
euro_pop <-

jschoeley

# Comparing bubble-grid with choropleth map
# Jonas Schöley

# Init --------------------------------------------------------------------

library(eurostat)      # eurostat data
library(rnaturalearth) # worldwide map data
library(tidyverse)     # tidy data transformation
library(lubridate)     # date and time support
library(sf)            # simple features GIS

jschoeley

# Disaggregation of 2D histogram of Poisson-counts with irregular bins
# based upon the penalized composite link mixed model
#
# Jonas Schöley, based on code from
# Deirdre I.R. Douma: The Penalized Composite Link Mixed Model.
# see further references in code

# Given is a matrix of observed counts over 2 dimensions (here
# year and age, i.e. a so-called Lexis surface).
# Each entry in the matrix corresponds to a rectangular region on the

jschoeley

region_iso	sex	age	ex_diff_mean_2020	ex_diff_mean_2021	ex_diff_q0.025_2020	ex_diff_q0.025_2021	ex_diff_q0.975_2020	ex_diff_q0.975_2021	bbi_q0.5_2020	bbi_q0.5_2021	bbi_q0.025_2020	bbi_q0.025_2021	bbi_q0.975_2020	bbi_q0.975_2021	region_position	region_code_iso3166_2_alpha3	region_code_iso3166_1	region_code_iso3166_1_alpha3	region_code_stmf	calendar_stmf	region_code_hmd	region_code_wpp	region_code_coverage	region_name	region_name_short	region_level	country_name	hemisphere	continent	year	death_total_nweeksmiss	as_of	e0avgdiff1619_q0.5	e0avgdiff1619_q0.025	e0avgdiff1619_q0.975
AT	T	0	-0.75726295307785	0.109872939746115	-0.867486087753811	-0.00873775031377946	-0.640273398677998	0.228466890627553	-4.19661664163826	0.14435079615867	-11.6911032794272	-0.0129431229215541	-2.74793040709203	0.287786153797217	14	AUT	AT	AUT	AUT	iso_week_date	AUT	40	Austria	Austria	AUT	0	Austria	n	Europe	2021	0	52	0.169764067500815	0.141474494918143	0.204577126571475
BE	T	0	-1.18765648644931	1.13996997057471	-1.29402467005087	1.034239584327

jschoeley

# ASFR Solver
# Given target fertility parameters determine suitable ASFRs
#
# Jonas Schöley <[email protected]>
#
# This script determines a set of age specific fertility rates under
# the following constraints:
# a) a total fertility rate
# b) a mean age at first birth
# c) a set of proportional deviations from initial (reference) rates