Predict Next-State Probabilities from a Context Tree
Arguments
- object
A
transitiontrees.- newdata
Either (i) a list of character vectors (each is the "history" leading up to the prediction point), (ii) a wide data.frame / matrix whose rows are histories, or (iii) a single character vector treated as one history.
- type
One of
"prob"(default; named numeric matrix of next-state probabilities) or"class"(character vector of modal predictions).- ...
Ignored.
Value
If type = "prob": a matrix with one row per history
and one column per state. A list/data.frame/matrix newdata
always returns a matrix (1 x k for a single-history container);
a bare character vector returns a named vector for interactive
convenience. If type = "class": a character vector of
modal predictions.
Examples
# \donttest{
seqs <- replicate(50, sample(c("A","B","C"), 12, replace = TRUE),
simplify = FALSE)
tree <- context_tree(seqs, max_depth = 3)
predict(tree, newdata = list(c("A","B"), c("C","C","B")))
#> A B C
#> [1,] 0.3333333 0.3518519 0.3148148
#> [2,] 0.4117647 0.2941176 0.2941176
predict(tree, newdata = list(c("A","B")), type = "class")
#> [1] "B"
predict(tree, newdata = c("A","B")) # bare vector → named vector
#> A B C
#> 0.3333333 0.3518519 0.3148148
# }