predict.FitResult {BayesGP} | R Documentation |
To predict the GP component in the fitted model, at the locations specified in 'newdata'.
## S3 method for class 'FitResult'
predict(
object,
newdata = NULL,
variable,
deriv = 0,
include.intercept = TRUE,
only.samples = FALSE,
quantiles = c(0.025, 0.5, 0.975),
boundary.condition = "Yes",
...
)
object |
The fitted object from the function 'model_fit'. |
newdata |
The dataset that contains the locations to be predicted for the specified GP. Its column names must include 'variable'. |
variable |
The name of the variable to be predicted, should be in the 'newdata'. |
deriv |
The degree of derivative that the user specifies for inference. Only applicable for a GP in the 'iwp' type. |
include.intercept |
A logical variable specifying whether the intercept should be accounted when doing the prediction. The default is TRUE. For Coxph model, this variable will be forced to FALSE. |
only.samples |
A logical variable indicating whether only the posterior samples are required. The default is FALSE, and the summary of posterior samples will be reported. |
quantiles |
A numeric vector of quantiles that predict.FitResult will produce, the default is c(0.025, 0.5, 0.975). |
boundary.condition |
A string specifies whether the boundary.condition should be considered in the prediction, should be one of c("yes", "no", "only"). The default option is "Yes". |
... |
Other arguments to be passed to the function. |
A data.frame that contains the posterior mean and pointwise intervals (or posterior samples) at the locations specified in 'newdata'.