obtainSmoothTrend function

Obtain Smooth Trend.

Obtain the smooth trend for models fitted with a spline component.

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.

Returns

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.