tidy_marginals {eratosthenes} | R Documentation |
Convert Marginals to Tidy (Molten) Data Frame
Description
Takes the results of gibbs_ad
or gibbs_ad_use
and "melts" the list
into a tidy data frame (Wickham 2014). Each row of the molten data frame will contain the index of the Monte Carlo sample, the sample itself, and then the event name.
Usage
tidy_marginals(input)
## S3 method for class 'marginals'
tidy_marginals(input)
## S3 method for class 'use_marginals'
tidy_marginals(input)
Arguments
input |
An object of class |
Value
A data frame giving the MC sampling index (idx
), the sample (year
), and the event (event
).
References
Wickham H (2014). “Tidy Data.” Journal of Statistical Software, 59, 1–23. doi:10.18637/jss.v059.i10.
Examples
x <- c("A", "B", "C", "D", "E", "F", "G", "H", "I", "J")
y <- c("B", "D", "G", "H", "K")
z <- c("F", "K", "L", "M")
contexts <- list(x, y, z)
f1 <- list(id = "find01", assoc = "D", type = c("type1", "form1"))
f2 <- list(id = "find02", assoc = "E", type = c("type1", "form2"))
f3 <- list(id = "find03", assoc = "G", type = c("type1", "form1"))
f4 <- list(id = "find04", assoc = "H", type = c("type2", "form1"))
f5 <- list(id = "find05", assoc = "I", type = "type2")
f6 <- list(id = "find06", assoc = "H", type = NULL)
artifacts <- list(f1, f2, f3, f4, f5, f6)
# external constraints
coin1 <- list(id = "coin1", assoc = "B", type = NULL, samples = runif(100,-320,-300))
coin2 <- list(id = "coin2", assoc = "G", type = NULL, samples = seq(37, 41, length = 100))
destr <- list(id = "destr", assoc = "J", type = NULL, samples = 79)
tpq_info <- list(coin1, coin2)
taq_info <- list(destr)
result <- gibbs_ad(contexts, finds = artifacts, tpq = tpq_info, taq = taq_info)
tidy_marginals(result)
[Package eratosthenes version 0.0.9 Index]