R/predictive_error.R
predictive_error.RdGeneric function and default method for computing predictive errors y−yrep (in-sample, for observed y) or y−˜y (out-of-sample, for new or held-out y). See predictive_error.stanreg() in the rstanarm package for an example.
predictive_error(object, ...)
# S3 method for default
predictive_error(object, y, ...)The object to use.
Arguments passed to methods. See the methods in the rstanarm package for examples.
For the default method, a vector of y values the same length as
the number of columns in the matrix used as object.
predictive_error() methods should return a D by N
matrix, where D is the number of draws from the posterior predictive distribution and N is the number of data points being predicted per draw.
The default method just takes object to be a matrix and y to be a
vector.
The rstanarm package (mc-stan.org/rstanarm) for example methods (CRAN, GitHub).
Guidelines and recommendations for developers of R packages interfacing with Stan and a demonstration getting a simple package working can be found in the vignettes included with rstantools and at mc-stan.org/rstantools/articles.
# default method
y <- rnorm(10)
ypred <- matrix(rnorm(500), 50, 10)
pred_errors <- predictive_error(ypred, y)
dim(pred_errors)
#> [1] 50 10
head(pred_errors)
#> [,1] [,2] [,3] [,4] [,5] [,6]
#> [1,] 0.5273861 0.07515823 1.513581 1.4204596 -3.4765209 -0.40151181
#> [2,] -3.3664225 0.81258188 2.744778 -0.8234573 -1.3396243 -1.43882134
#> [3,] -0.5546069 2.37300064 1.780391 -0.2672072 0.7954730 -0.41251601
#> [4,] -0.2880340 -0.76885376 0.723278 -0.5925147 -0.7830652 1.52582725
#> [5,] -0.5131371 3.30739106 1.233684 0.3282228 -0.8251587 0.01187749
#> [6,] 0.1832783 1.69463620 0.412581 1.1282433 -2.4243409 -0.55389915
#> [,7] [,8] [,9] [,10]
#> [1,] 0.3291168 0.7518855 1.0182404 2.1367075
#> [2,] -0.9216418 1.3862216 0.6818612 1.1718269
#> [3,] -0.7428718 2.1940964 0.7415774 -1.0785962
#> [4,] 1.6353221 1.0977800 2.3479025 0.9887451
#> [5,] -0.3287231 2.4549490 0.3920619 2.0133653
#> [6,] 0.6492479 0.7439346 0.9827939 2.3187384
# Also see help("predictive_error", package = "rstanarm")