predict.lpca {logisticPCA} | R Documentation |
Predict Logistic PCA scores or reconstruction on new data
Description
Predict Logistic PCA scores or reconstruction on new data
Usage
## S3 method for class 'lpca'
predict(object, newdata, type = c("PCs", "link", "response"),
...)
Arguments
object |
logistic PCA object |
newdata |
matrix with all binary entries. If missing, will use the
data that |
type |
the type of fitting required. |
... |
Additional arguments |
Examples
# construct a low rank matrices in the logit scale
rows = 100
cols = 10
set.seed(1)
loadings = rnorm(cols)
mat_logit = outer(rnorm(rows), loadings)
mat_logit_new = outer(rnorm(rows), loadings)
# convert to a binary matrix
mat = (matrix(runif(rows * cols), rows, cols) <= inv.logit.mat(mat_logit)) * 1.0
mat_new = (matrix(runif(rows * cols), rows, cols) <= inv.logit.mat(mat_logit_new)) * 1.0
# run logistic PCA on it
lpca = logisticPCA(mat, k = 1, m = 4, main_effects = FALSE)
PCs = predict(lpca, mat_new)
[Package logisticPCA version 0.2 Index]