Init

library(kirkegaard)
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load_packages(
  
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Simulations

#config
(g_path = sqrt(.80))
## [1] 0.8944272
(e_path = sqrt(1 - g_path^2))
## [1] 0.4472136
n = 10e3

#simulate data
set.seed(1)
d1 = tibble(
  genetics = rnorm(n),
  environment = rnorm(n),
  genetics_effect = genetics * g_path,
  environment_effect = environment * e_path,
  phenotype = genetics_effect + environment_effect,
  deviation_from_mean = phenotype - mean(phenotype),
  genetic_deviation_from_mean = genetics_effect - mean(genetics_effect),
  environment_deviation_from_mean = environment_effect - mean(environment_effect),
  genetic_deviation_prop = genetic_deviation_from_mean / deviation_from_mean,
  environmental_deviation_prop = environment_deviation_from_mean / deviation_from_mean,
  total_prop = genetic_deviation_prop + environmental_deviation_prop
)

describe2(d1)
#proportions of deviations
d1 %>% 
  filter(phenotype > 2) %>% 
  select(genetic_deviation_prop, environmental_deviation_prop) %>%
  pivot_longer(everything()) %>% 
  mutate(
    cause = str_replace(name, "_deviation_prop", "")
  ) %>% 
  GG_denhist("value", group = "cause") +
  scale_fill_discrete("Cause (fraction)") +
  scale_x_continuous("Phenotype score")
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GG_save("figs/2+ sd proportions.png")
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d1 %>% 
  filter(phenotype > 2) %>% 
  describe2()

Meta

write_sessioninfo()
## R version 4.3.2 (2023-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Linux Mint 21.1
## 
## Matrix products: default
## BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
## 
## locale:
##  [1] LC_CTYPE=en_DK.UTF-8       LC_NUMERIC=C              
##  [3] LC_TIME=en_DK.UTF-8        LC_COLLATE=en_DK.UTF-8    
##  [5] LC_MONETARY=en_DK.UTF-8    LC_MESSAGES=en_DK.UTF-8   
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##  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
## [11] LC_MEASUREMENT=en_DK.UTF-8 LC_IDENTIFICATION=C       
## 
## time zone: Europe/Berlin
## tzcode source: system (glibc)
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
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## other attached packages:
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## [69] R6_2.5.1          textshaping_0.3.6 evaluate_0.21     lattice_0.22-5   
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