predict.LaMa_matrices: Build the prediction design matrix based on new data and...

In LaMa: Fast Numerical Maximum Likelihood Estimation for Latent Markov Models

Build the prediction design matrix based on new data and model_matrices object created by make_matrices

Description

Build the prediction design matrix based on new data and model_matrices object created by make_matrices

Usage

## S3 method for class 'LaMa_matrices'
predict(object, newdata, what = NULL, ...)

Arguments

object	model matrices object as returned from make_matrices
newdata	data frame containing the variables in the formula and new data for which to evaluate the basis
what	optional character string specifying which formula to use for prediction, if object contains multiple formulas. If NULL, the first formula is used.
...	needs to be a newdata data frame containing the variables in the formula and new data for which to evaluate the basis

Value

prediction design matrix for newdata with the same basis as used for model_matrices

See Also

make_matrices for creating objects of class LaMa_matrices which can be used for prediction by this function.

Examples

# single formula
modmat = make_matrices(~ s(x), data.frame(x = 1:10))
Z_p = predict(modmat, data.frame(x = 1:10 - 0.5))
# with multiple formulas
modmat = make_matrices(list(mu ~ s(x), sigma ~ s(x, bs = "ps")), data = data.frame(x = 1:10))
Z_p = predict(modmat, data.frame(x = 1:10 - 0.5), what = "mu")
# nested formula list
form = list(stream1 = list(mu ~ s(x), sigma ~ s(x, bs = "ps")))
modmat = make_matrices(form, data = data.frame(x = 1:10))
Z_p = predict(modmat, data.frame(x = 1:10 - 0.5), what = c("stream1", "mu"))

LaMa documentation built on Nov. 5, 2025, 6:42 p.m.