gratia (version 0.9.0)

confint.fderiv: Point-wise and simultaneous confidence intervals for derivatives of smooths

Description

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

Usage

# S3 method for fderiv
confint(
  object,
  parm,
  level = 0.95,
  type = c("confidence", "simultaneous"),
  nsim = 10000,
  ncores = 1L,
  ...
)

Value

a data frame with components:

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

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

3. est; estimated derivative

4. upper; upper limit of the confidence or simultaneous interval.

Arguments

object

an object of class "fderiv" containing the estimated derivatives.

parm

which parameters (smooth terms) are to be given intervals as a vector of terms. If missing, all parameters are considered.

level

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

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.

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).

...

additional arguments for methods

Author

Gavin L. Simpson

Examples

load_mgcv()
# \dontshow{
op <- options(pillar.sigfig = 2, cli.unicode = FALSE)
# }
dat <- data_sim("eg1", n = 1000, dist = "normal", scale = 2, seed = 2)
mod <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = dat, method = "REML")

# new data to evaluate the derivatives at, say over the middle 50% of range
# of each covariate
middle <- function(x, n = 25, coverage = 0.5) {
  v <- (1 - coverage) / 2
  q <- quantile(x, prob = c(0 + v, 1 - v), type = 8)
  seq(q[1], q[2], length = n)
}
new_data <- sapply(dat[c("x0", "x1", "x2", "x3")], middle)
new_data <- data.frame(new_data)
## first derivatives of all smooths...
fd <- fderiv(mod, newdata = new_data)

## point-wise interval
ci <- confint(fd, type = "confidence")
ci

## simultaneous interval for smooth term of x2
# \dontshow{
set.seed(42)
# }
x2_sint <- confint(fd,
  parm = "x2", type = "simultaneous",
  nsim = 10000, ncores = 2
)
# \donttest{
x2_sint
# }
# \dontshow{
options(op)
# }