predict,lnm-method {miniLNM} | R Documentation |
LNM Fitted Probabilities
Description
Given an input dataset, predict the output composition. Specifically, this
outputs \phi^{-1}(Bx)
, for the inverse log ratio transformation
\phi^{-1}
and fitted covariate matrix B
.
Usage
## S4 method for signature 'lnm'
predict(object, newdata = NULL, ...)
Arguments
object |
An object of class lnm with fitted parameters |
newdata |
New samples on which to form predictions. Defaults to NULL, in which case predictions are made at the same design points as those used during the original training. |
... |
Additional keyword arguments, for consistency with R's predict generic (never used). |
Value
A matrix with predictions along rows and outcomes along columns. Rows sum up to one.
Examples
example_data <- lnm_data(N = 50, K = 10)
xy <- dplyr::bind_cols(example_data[c("X", "y")])
fit <- lnm(
starts_with("y") ~ starts_with("x"), xy,
iter = 25, output_samples = 25
)
head(predict(fit))
[Package miniLNM version 0.1.0 Index]