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confint.gam

Point-wise and simultaneous confidence intervals for smooths

Description

Calculates point-wise confidence or simultaneous intervals for the smooth terms of a fitted GAM.

Usage

## S3 method for class 'gam'
confint(
  object,
  parm,
  level = 0.95,
  newdata = NULL,
  n = 200,
  type = c("confidence", "simultaneous"),
  nsim = 10000,
  shift = FALSE,
  transform = FALSE,
  unconditional = FALSE,
  ncores = 1,
  partial_match = FALSE,
  ...
)

## S3 method for class 'gamm'
confint(object, ...)

## S3 method for class 'list'
confint(object, ...)

Arguments

object

an object of class "gam" or "gamm".
parm

which parameters (smooth terms) are to be given intervals as a vector of terms. If missing, all parameters are considered, although this is not currently implemented.
level

numeric, 0 < level < 1; the confidence level of the point-wise or simultaneous interval. The default is 0.95 for a 95% interval.
newdata

data frame; containing new values of the covariates used in the model fit. The selected smooth(s) wil be evaluated at the supplied values.
n

numeric; the number of points to evaluate smooths at.
type

character; the type of interval to compute. One of "confidence" for point-wise intervals, or "simultaneous" for simultaneous intervals.
nsim

integer; the number of simulations used in computing the simultaneous intervals.
shift

logical; should the constant term be add to the smooth?
transform

logical; should the smooth be evaluated on a transformed scale? For generalised models, this involves applying the inverse of the link function used to fit the model. Alternatively, the name of, or an actual, function can be supplied to transform the smooth and it's confidence interval.
unconditional

logical; if TRUE (and freq == FALSE) then the Bayesian smoothing parameter uncertainty corrected covariance matrix is returned, if available.
ncores

number of cores for generating random variables from a multivariate normal distribution. Passed to mvnfast::rmvn(). Parallelization will take place only if OpenMP is supported (but appears to work on Windows with current R).
partial_match

logical; should matching parm use a partial match or an exact match? Can only be used if length(parm) is 1.
...

additional arguments for methods

Value

a data frame with components:

  1. term; factor indicating to which term each row relates,

  2. x; the vector of values at which the smooth was evaluated,

  3. lower; lower limit of the confidence or simultaneous interval,

  4. est; estimated value of the smooth

  5. upper; upper limit of the confidence or simultaneous interval,

  6. crit; critical value for the 100 * level% confidence interval.

Author(s)

Gavin L. Simpson

Examples

load_mgcv()

dat <- gamSim(1, n = 500, dist = "normal", scale = 2)
mod <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML")

## point-wise interval
ci <- confint(mod, parm = "s(x1)", type = "confidence")
ci

## simultaneous interval for smooth term of x1

si <- confint(mod, parm = "s(x1)", type = "simultaneous", nsim = 100)
si
gratia

Graceful 'ggplot'-Based Graphics and Other Functions for GAMs Fitted Using 'mgcv'

v0.6.0
MIT + file LICENSE
Authors
Gavin L. Simpson [aut, cre] (<https://orcid.org/0000-0002-9084-8413>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>)
Initial release
2021-04-17

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