predict.mfp | R Documentation |
Obtains predictions from an "mfp" object
## S3 method for class 'mfp'
predict(object, newdata,
type = c("link", "response", "lp", "risk", "expected", "terms"), terms,
ref = NULL, seq = NULL, se.fit = FALSE, dispersion = NULL,
na.action = na.pass, collapse, safe = FALSE, ...)
object |
an "mfp" object. |
newdata |
optionally, a data frame in which to look for variables with which to predict. If omitted, the fitted linear predictors are used. |
type |
the type of prediction required. The default is on the scale of the linear predictors; the alternative "response" is on the scale of the response variable. The "terms" option returns fitted values of each term on the linear predictor scale. This is useful for visualizing the effects for fractional polynomials. |
terms |
A character vector specifiying the variables for which to return fitted values. The default is all non-factor selected terms. Only relevant if |
ref |
a list of reference values for each term. This is the value relative to which contrasts are computed. Defaults to the mean value of the variable. |
seq |
a list of numeric vectors for each term specifiying the input values for which contrasts should be computed. |
se.fit |
logical switch indicating if standard errors are required. |
dispersion |
the dispersion of the GLM fit to be assumed in computing the standard errors. If omitted, that returned by summary applied to the object is used. |
na.action |
function determining what should be done with missing values in newdata. The default is to predict NA. |
collapse |
optional vector of subject identifiers. If specified, the output will contain one entry per subject rather than one entry per observation. |
safe |
unused. |
... |
further arguments used by |
If type = "terms"
, a list with term predictions for each variable including the contrast to the reference value, standard errors, and contrasts of the first and second derivative.
Otherwise, a prediction object based on predict.glm
or predict.coxph
.
predict.glm
, predict.coxph
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