Obtain the smooth trend for models fitted with a spline component.
Usage
obtainSmoothTrend(
object,
grid = NULL,
newdata = NULL,
deriv = 0,
includeIntercept = FALSE,
which = 1
)Arguments
- object
An object of class LMMsolve.
- grid
A numeric vector having the length of the dimension of the fitted spline component. This represents the number of grid points at which a surface will be computed.
- newdata
A data.frame containing new points for which the smooth trend should be computed. Column names should include the names used when fitting the spline model.
- deriv
Derivative of B-splines, default 0. At the moment only implemented for spl1D.
- includeIntercept
Should the value of the intercept be included in the computed smooth trend? Ignored if deriv > 0.
- which
An integer, for if there are multiple splxD terms in the model. Default value is 1.
Value
A data.frame with predictions for the smooth trend on the specified grid. The standard errors are saved if `deriv` has default value 0.
Examples
## Fit model on john.alpha data from agridat package.
data(john.alpha, package = "agridat")
## Fit a model with a 1-dimensional spline at the plot level.
LMM1_spline <- LMMsolve(fixed = yield ~ rep + gen,
spline = ~spl1D(x = plot, nseg = 20),
data = john.alpha)
## Obtain the smooth trend for the fitted model on a dense grid.
smooth1 <- obtainSmoothTrend(LMM1_spline,
grid = 100)
## Obtain the smooth trend on a new data set - plots 10 to 40.
newdat <- data.frame(plot = 10:40)
smooth2 <- obtainSmoothTrend(LMM1_spline,
newdata = newdat)
## The first derivative of the smooth trend can be obtained by setting deriv = 1.
smooth3 <- obtainSmoothTrend(LMM1_spline,
grid = 100,
deriv = 1)
## For examples of higher order splines see the vignette.