smooth1d(y, sv2 = 0.1, err = 0.01, verb = TRUE)
df
.sv2
for the variance of the random effects, the routine iteratetively optimizes the fixed and random contributions to the extended likelihood, until the estimate for the variance convergences with tolerance err
. The result is quite stable within a reasonable range of starting values and tolerances, and the function can be used for fairly automatic smoothing ((i.e. withou fixing a bandwidth parameter).
fdr1d
# Stupid dummies, obviously
smooth1d(1:10)
smooth1d(1:10, sv2=1)
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