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self-consistent region iteration #15

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self-consistent region iteration #15

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20 changes: 20 additions & 0 deletions R/calib.R
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library(cmdstanr)
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@Dashadower Dashadower May 6, 2021

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instead of importing libraries, try to use namespace::func_name.
Additionally, include necessary libraries into Imports in DESCRIPTION and add ROxygen documentation.

library(dplyr)
library(tidyverse)
library(reshape)

iter_gen_inf <- function(sbc_obj, prior_theta, par_names, N, M, data){ #fixed params as prior_phi and add clampedStan
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@Dashadower Dashadower May 6, 2021

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I think we can just receive sampled_y and post_theta as arguments instead of SBCObject and re-fitting.

sampled_y = sbc_obj$sample_y_tilde(prior_theta, data=data)
post_theta = sbc_obj$sample_theta_bar_y(sampled_y, data=data, pars=par_names, fit_iter=M)
NMP_tb <- as_tibble(post_theta)
NMP_G <- NMP_tb %>% gather(variable)
NMP_G$par <- gsub("\\..*","",NMP_G$variable)
NMP_G$prior <- sapply(NMP_G$variable, function(x){prior_theta[as.integer(gsub(".*\\.","",x)), gsub("\\..*","",x)]})
Epost_bar_pri <- NMP_G %>% group_by(par, prior) %>% summarise('mean' = round(mean(value),3))
Varpost_bar_pri<- NMP_G %>% group_by(par, prior) %>% summarise('sd' = sd(value))
postVar <- inner_join(Epost_bar_pri %>% group_by(par) %>% summarise('VE' = sd(mean)), Varpost_bar_pri %>% group_by(par) %>% summarise('EV' = mean(sd^2))) %>%
mutate("postVar" = VE + EV) %>% select(par, postVar)
priVar = NMP_G %>% select(prior, par) %>% group_by(par) %>% summarise('priVar' = sd(prior)^2)
ratioVar = inner_join(postVar, priVar) %>% mutate("ratioVar" = postVar/priVar)
return(ratioVar)
}