nlist
is an R package to create and manipulate numeric list (nlist
) objects.
An nlist
is an S3 class list of uniquely named numeric objects. An numeric object is an integer or double vector, matrix or array. nlist
objects are the raw data inputs for analytic engines such as JAGS, STAN and TMB.
An nlists
object is a S3 class list of nlist
objects with the same names, dimensionalities and typeofs. nlists
objects are useful for storing multiple realizations of simulated data sets. They can be converted to coda::mcmc
and coda::mcmc.list
objects.
To install the latest release from CRAN
To install the developmental version from GitHub
nlist
An nlist
is an S3 class list of uniquely named numeric objects.
It is straightforward to create an new nlist
object.
nlists
An nlists
object is a S3 class list of nlist
objects with the same names, dimensionalities and typeofs.
The nchains attribute is used to keep track of the number of chains.
nlists <- nlists(
nlist(x = 1, y = matrix(1:9, 3)),
nlist(x = -2, y = matrix(2:10, 3)),
nlist(x = 10, y = matrix(22:30, 3)),
nlist(x = -100, y = matrix(-2:-10, 3))
)
print(nlists)
#> $x
#> [1] -0.5
#>
#> $y
#> [,1] [,2] [,3]
#> [1,] 1.5 4.5 7.5
#> [2,] 2.5 5.5 8.5
#> [3,] 3.5 6.5 9.5
#>
#> an nlists object of 4 nlist objects each with 2 numeric elements
A data.frame can be coerced to an nlist
object
data <- data.frame(
lgl = c(TRUE, NA),
dte = as.Date(c("2001-01-02", "2001-01-01")),
fac = factor(c("b", "a"))
)
as_nlist(data)
#> $lgl
#> [1] 1 NA
#>
#> $dte
#> [1] 11324 11323
#>
#> $fac
#> [1] 2 1
#>
#> an nlist object with 3 numeric elements
And an nlist
objects can be converted to an mcmc
or term_frame
objects (and converted back again)
as_mcmc(nlist)
#> Markov Chain Monte Carlo (MCMC) output:
#> Start = 1
#> End = 1
#> Thinning interval = 1
#> x y[1,1] y[2,1] y[3,1] y[1,2] y[2,2] y[3,2] y[1,3] y[2,3] y[3,3]
#> [1,] 1 1 2 3 4 5 6 7 8 9
as_term_frame(nlist)
#> term value
#> 1 x 1
#> 2 y[1,1] 1
#> 3 y[2,1] 2
#> 4 y[3,1] 3
#> 5 y[1,2] 4
#> 6 y[2,2] 5
#> 7 y[3,2] 6
#> 8 y[1,3] 7
#> 9 y[2,3] 8
#> 10 y[3,3] 9
The estimates()
function can be used to aggregate an nlists
object to an nlist
object.
estimates(nlists, fun = mean)
#> $x
#> [1] -22.75
#>
#> $y
#> [,1] [,2] [,3]
#> [1,] 5.75 7.25 8.75
#> [2,] 6.25 7.75 9.25
#> [3,] 6.75 8.25 9.75
#>
#> an nlist object with 2 numeric elements
while the tidy()
function treats the values as if they are MCMC samples and summarises the terms as a tidy tibble.
tidy(nlists, simplify = TRUE)
#> # A tibble: 10 × 5
#> term estimate lower upper svalue
#> <term> <dbl> <dbl> <dbl> <dbl>
#> 1 x -0.5 -92.6 9.32 0
#> 2 y[1,1] 1.5 -1.77 20.5 0.737
#> 3 y[2,1] 2.5 -2.62 21.5 0.737
#> 4 y[3,1] 3.5 -3.47 22.5 0.737
#> 5 y[1,2] 4.5 -4.32 23.5 0.737
#> 6 y[2,2] 5.5 -5.17 24.5 0.737
#> 7 y[3,2] 6.5 -6.02 25.5 0.737
#> 8 y[1,3] 7.5 -6.87 26.5 0.737
#> 9 y[2,3] 8.5 -7.72 27.5 0.737
#> 10 y[3,3] 9.5 -8.57 28.5 0.737
An nlists
object can be converted to an mcmc.list
object and a term_frame
.
as_mcmc_list(nlists)
#> [[1]]
#> Markov Chain Monte Carlo (MCMC) output:
#> Start = 1
#> End = 4
#> Thinning interval = 1
#> x y[1,1] y[2,1] y[3,1] y[1,2] y[2,2] y[3,2] y[1,3] y[2,3] y[3,3]
#> [1,] 1 1 2 3 4 5 6 7 8 9
#> [2,] -2 2 3 4 5 6 7 8 9 10
#> [3,] 10 22 23 24 25 26 27 28 29 30
#> [4,] -100 -2 -3 -4 -5 -6 -7 -8 -9 -10
#>
#> attr(,"class")
#> [1] "mcmc.list"
as_term_frame(nlists)
#> term sample value
#> 1 x 1 1
#> 2 y[1,1] 1 1
#> 3 y[2,1] 1 2
#> 4 y[3,1] 1 3
#> 5 y[1,2] 1 4
#> 6 y[2,2] 1 5
#> 7 y[3,2] 1 6
#> 8 y[1,3] 1 7
#> 9 y[2,3] 1 8
#> 10 y[3,3] 1 9
#> 11 x 2 -2
#> 12 y[1,1] 2 2
#> 13 y[2,1] 2 3
#> 14 y[3,1] 2 4
#> 15 y[1,2] 2 5
#> 16 y[2,2] 2 6
#> 17 y[3,2] 2 7
#> 18 y[1,3] 2 8
#> 19 y[2,3] 2 9
#> 20 y[3,3] 2 10
#> 21 x 3 10
#> 22 y[1,1] 3 22
#> 23 y[2,1] 3 23
#> 24 y[3,1] 3 24
#> 25 y[1,2] 3 25
#> 26 y[2,2] 3 26
#> 27 y[3,2] 3 27
#> 28 y[1,3] 3 28
#> 29 y[2,3] 3 29
#> 30 y[3,3] 3 30
#> 31 x 4 -100
#> 32 y[1,1] 4 -2
#> 33 y[2,1] 4 -3
#> 34 y[3,1] 4 -4
#> 35 y[1,2] 4 -5
#> 36 y[2,2] 4 -6
#> 37 y[3,2] 4 -7
#> 38 y[1,3] 4 -8
#> 39 y[2,3] 4 -9
#> 40 y[3,3] 4 -10
An nlists
object can have its chains split or collapsed.
Please note that the nlist project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.