File size: 1,322 Bytes
2f8aa81 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 |
source("install_and_load_INLA.R")
#parameters
kappa = 1
phi_1 = c(1, 1.25) # "Local" version: (sigma, phi) First value is not used
WALS <- read_csv("data/complexity_data_WALS.csv") %>%
dplyr::select("Name"=lang, roundComp, logpop2, "ISO_639"=silCode) %>%
dplyr::mutate(ISO_639 = str_to_lower(ISO_639))
min_val <- min(WALS$roundComp)
max_val <- max(WALS$roundComp)
# Perform the rescaling
WALS$roundComp <- (WALS$roundComp - min_val) / (max_val - min_val)
pop_file_fn <- "data_wrangling/ethnologue_pop_SM_morph_compl_reanalysis.tsv"
L1 <-
read_tsv(pop_file_fn, show_col_types = F) %>% dplyr::select(ISO_639, L1_log10_scaled)
WALS_df <- WALS %>%
inner_join(L1,
by = c("ISO_639"))
formula <- as.formula(paste("roundComp ~", "L1_log10_scaled"))
result <- inla(formula, family = "gaussian",
data = WALS_df, control.compute = list(waic = TRUE))
summary(result)
save(result, file = "output_models/models_WALS_uncontrolled.RData")
social_effects_uncontrolled <- c("morphological complexity ~ L1",
round(c(
result$summary.fixed[2,]$`0.025quant`,
result$summary.fixed[2,]$`0.5quant`,
result$summary.fixed[2,]$`0.975quant`, nrow(WALS_df)), 2), "default (~10%)")
save(social_effects_uncontrolled, file = "output_models/social_effects_uncontrolled.RData")
|