Computes an R^2 measure for a splinetree based on the projected sum of squared errors. Returns 1-SSE/SST. SSE is the sum of projection squared errors between individual smoothed trajectories and predicted smoothed trajectories evaluated on a fixed grid. SST is the sum of projection squared errors between individual smoothed trajectories and the overall population mean trajectory, evaluated on the same fixed grid. If model\$intercept==TRUE, then there is the option to ignore the intercept coefficient when computing this metric. When the intercept is ignored, the metric captures how well the model explains variation in shape, and ignores any variation in intercept explained by the model.

projectedR2(model, includeIntercept = FALSE)

## Arguments

model a model created with splineTree() If FALSE and if the model was built with an intercept, the projected squared errors are computed while ignoring the intercept. If the model was built without an intercept, this parameter does not do anything.

## Value

The percentage of variation in projected trajectory explained by the model. Computed as 1-SSE/SST. See description.

## Examples

r2 <- projectedR2(tree)