predict.nhmm {seqHMM} | R Documentation |
Predictions from Non-homogeneous Hidden Markov Models
Description
This function computes the marginal forward predictions for NHMMs and MNHMMs, where the marginalization is (by default) over individuals and time points, weighted by the latent state probabilities.
Usage
## S3 method for class 'nhmm'
predict(
object,
newdata,
newdata2 = NULL,
condition = NULL,
type = c("state", "response", "transition", "emission"),
probs = c(0.025, 0.975),
boot_idx = FALSE,
...
)
## S3 method for class 'mnhmm'
predict(
object,
newdata,
newdata2 = NULL,
condition = NULL,
type = c("state", "response", "transition", "emission"),
probs = c(0.025, 0.975),
boot_idx = FALSE,
...
)
Arguments
object |
An object of class |
newdata |
A data frame used for computing the predictions. |
newdata2 |
An optional data frame for predictions, in which case the
estimates are differences between predictions using |
condition |
An optional vector of variable names used for conditional predictions. |
type |
A character vector defining the marginal predictions of
interest. Can be one or multiple of |
probs |
A numeric vector of quantiles to compute. |
boot_idx |
Logical indicating whether to use bootstrap samples in
marginalization when computing quantiles. Default is |
... |
Ignored. |