File size: 4,136 Bytes
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# installed for running the rest of the scripts in this R project
.libPaths(c("rlib/", .libPaths()))
if (!suppressPackageStartupMessages(require("pacman"))) { install.packages("pacman") }
pacman::p_load(
here,
tidyverse,
reshape2,
broom,
glue,
forcats,
magrittr,
stringr,
purrr,
rcompanion,
naniar,
readr,
tidyr,
dplyr,
openxlsx,
jsonlite,
readxl,
flextable,
officer,
#INLA - related
sp,
scico,
BiocManager,
foreach,
MASS,
matrixStats,
#brms
# brms,
# imputation
missForest,
#plotting graphs
scales,
RColorBrewer,
ggpubr,
ggplot2,
ggrepel,
gplots,
ggtree,
ggridges,
grid,
gridExtra,
scales,
ggmap,
psych, #for scatterplot matrix
viridis,
rlang,
devtools,
patchwork,
ggnewscale,
ggstance,
#making maps
mapdata,
maptools,
maps,
# geoR,
geosphere,
fields,
# phylogenetic packages
ape,
phytools,
nlme,
caper,
MCMCglmm,
# testing
assertthat,
beepr
)
# quiet down, tidyverse:
options(tidyverse.quiet = TRUE)
options(warn.conflicts = FALSE)
options(stringsAsFactors = FALSE)
GRAMBANK_LANGUAGES <- file.path("../..", "cldf", "languages.csv")
GRAMBANK_VALUES <- file.path("../..", "cldf", "values.csv")
GRAMBANK_PARAMETERS <- file.path("../..", "cldf", "parameters.csv")
GRAMBANK_CODES <- file.path("../..", "cldf", "codes.csv")
# The columns specifier for readr to parse ../cldf/values.csv
VALUES_COLSPEC <- c(
ID = col_character(),
Language_ID = col_character(),
Parameter_ID = col_character(),
Value = col_character(),
Code_ID = col_character(),
Comment = col_character(),
Source = col_character()
)
LANGUAGES_COLSPEC = c(
ID = col_character(),
Name = col_character(),
Macroarea = col_character(),
Latitude = col_double(),
Longitude = col_double(),
Glottocode = col_character(),
ISO639P3code = col_character(),
contributed_datapoints = col_character(),
provenance = col_character(),
Family_name = col_character(),
Family_id = col_character()
)
PARAMETERS_COLSPEC = c(
ID = col_character(),
Name = col_character(),
Description = col_character(),
patron = col_character(),
name_in_french = col_character(),
Grambank_ID_desc = col_character(),
bound_morphology = col_character()
)
CODES_COLSPEC = c(
ID = col_character(),
Parameter_ID = col_character(),
Name = col_character(),
Description = col_character()
)
WIDE_COLSPEC = c(
.default = col_integer(),
Language_ID = col_character(),
na_prop = col_double()
)
#creating folders
OUTPUTDIR_models <- here("output_models")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_models)) { dir.create(OUTPUTDIR_models) }
OUTPUTDIR_tables <- here("output_tables")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_tables)) { dir.create(OUTPUTDIR_tables) }
OUTPUTDIR_output <- here("output")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_output)) { dir.create(OUTPUTDIR_output) }
OUTPUTDIR_data_wrangling<- here("data_wrangling")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_data_wrangling)) { dir.create(OUTPUTDIR_data_wrangling) }
OUTPUTDIR_models_reduced <- here("output_models_reduced")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_models_reduced)) { dir.create(OUTPUTDIR_models_reduced) }
OUTPUTDIR_tables_reduced <- here("output_tables_reduced")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_tables_reduced)) { dir.create(OUTPUTDIR_tables_reduced) }
OUTPUTDIR_output_reduced <- here("output_reduced")
# create output dir if it does not exist.
if (!dir.exists(OUTPUTDIR_output_reduced)) { dir.create(OUTPUTDIR_output_reduced) }
#source custom functions to have them at hand
source("varcov.spatial_function.R")
#Adding a prior for modelling with INLA on precision/SD of random effects and likelihood: the probability of SD of each random effect and likelihood being > 1 is equal to 0.1
pcprior_hyper = list(prec =list(prior="pc.prec", param = c(1, 0.1)))
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