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source("install_and_load_INLA.R") |
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kappa = 1 |
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phi_1 = c(1, 1.25) |
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WALS <- read_csv("data/complexity_data_WALS.csv") %>% |
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dplyr::select("Name"=lang, roundComp, logpop2, "ISO_639"=silCode) %>% |
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dplyr::mutate(ISO_639 = str_to_lower(ISO_639)) |
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min_val <- min(WALS$roundComp) |
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max_val <- max(WALS$roundComp) |
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WALS$roundComp <- (WALS$roundComp - min_val) / (max_val - min_val) |
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pop_file_fn <- "data_wrangling/ethnologue_pop_SM_morph_compl_reanalysis.tsv" |
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L1 <- |
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read_tsv(pop_file_fn, show_col_types = F) %>% dplyr::select(ISO_639, L1_log10_scaled) |
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WALS_df <- WALS %>% |
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inner_join(L1, |
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by = c("ISO_639")) |
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formula <- as.formula(paste("roundComp ~", "L1_log10_scaled")) |
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result <- inla(formula, family = "gaussian", |
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data = WALS_df, control.compute = list(waic = TRUE)) |
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summary(result) |
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save(result, file = "output_models/models_WALS_uncontrolled.RData") |
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social_effects_uncontrolled <- c("morphological complexity ~ L1", |
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round(c( |
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result$summary.fixed[2,]$`0.025quant`, |
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result$summary.fixed[2,]$`0.5quant`, |
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result$summary.fixed[2,]$`0.975quant`, nrow(WALS_df)), 2), "default (~10%)") |
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save(social_effects_uncontrolled, file = "output_models/social_effects_uncontrolled.RData") |
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