Description Usage Arguments Author(s) See Also Examples
summary.bkpc
produces two sets of summary statistics for each variable: mean and standard deviation (ignoring autocorrelation of the chain) of the sample distribution and quantiles of the sample distribution using the quantiles argument.
1 2 |
object |
an object of class |
quantiles |
a vector of quantiles to evaluate for each variable. |
n.burnin |
number of burn-in iterations to discard from the thinned sample. |
... |
Currently not used. |
K. Domijan
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | set.seed(-88106935)
data(iris)
testset <- sample(1:150,50)
train <- as.matrix(iris[-testset,-5])
test <- as.matrix(iris[testset,-5])
wtr <- iris[-testset, 5]
wte <- iris[testset, 5]
result <- bkpc(train, y = wtr, n.iter = 1000, thin = 10, n.kpc = 2,
intercept = FALSE, rotate = TRUE)
summary(result, n.burnin = 0)
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