predict_gam: Modified prediciton function based on predict.gam

In nlraa: Nonlinear Regression for Agricultural Applications

Modified prediciton function based on predict.gam

Description

Largely based on predict.gam, but with some minor modifications to make it compatible with predict_nls

Usage

predict_gam(
  object,
  newdata = NULL,
  type = "link",
  se.fit = TRUE,
  terms = NULL,
  exclude = NULL,
  block.size = NULL,
  newdata.guaranteed = FALSE,
  na.action = na.pass,
  unconditional = FALSE,
  iterms.type = NULL,
  interval = c("none", "confidence", "prediction"),
  level = 0.95,
  tvalue = NULL,
  ...
)

Arguments

object	object of class ‘gam’ or as returned by function ‘gamm’
newdata	see predict.gam
type	see predict.gam
se.fit	see predict.gam. Notice that the default is changed to TRUE.
terms	see predict.gam
exclude	see predict.gam
block.size	see predict.gam
newdata.guaranteed	see predict.gam
na.action	see predict.gam
unconditional	see predict.gam
iterms.type	see predict.gam
interval	either ‘none’, ‘confidence’ or ‘prediction’.
level	probability level for the interval (default 0.95)
tvalue	t-value statistic used for constructing the intervals
...	additional arguments to be passed to predict.gam.

Value

numeric vector of the same length as the fitted object when interval is equal to ‘none’. Otherwise, a data.frame with columns named (for a 0.95 level) ‘Estimate’, ‘Est.Error’, ‘Q2.5’ and ‘Q97.5’

Note

this is a very simple wrapper for predict.gam.

See Also

predict.lm, predict.nls, predict.gam, simulate_nls, simulate_gam

Examples

require(ggplot2)
require(mgcv)
data(barley)

fm.G <- gam(yield ~ s(NF, k = 6), data = barley)

## confidence and prediction intervals
cis <- predict_gam(fm.G, interval = "conf")
pis <- predict_gam(fm.G, interval = "pred")

barleyA.ci <- cbind(barley, cis)
barleyA.pi <- cbind(barley, pis)

ggplot() + 
  geom_point(data = barleyA.ci, aes(x = NF, y = yield)) + 
  geom_line(data = barleyA.ci, aes(x = NF, y = Estimate)) + 
  geom_ribbon(data = barleyA.ci, aes(x = NF, ymin = Q2.5, ymax = Q97.5), 
              color = "red", alpha = 0.3) + 
  geom_ribbon(data = barleyA.pi, aes(x = NF, ymin = Q2.5, ymax = Q97.5), 
              color = "blue", alpha = 0.3) + 
  ggtitle("95% confidence and prediction bands")
  

nlraa documentation built on July 9, 2023, 6:08 p.m.