View source: R/spline_functions.R
v_s | R Documentation |
This function estimates splines in vglmer
, similar to s(...)
in
mgcv
albeit with many fewer options than mgcv
. It allows for
truncated (linear) splines (type="tpf"
), O'Sullivan splines
(type="o"
), or kernel ridge regression (type="gKRLS"
). Please
see vglmer for more discussion and examples. For information on kernel
ridge regression, please consult gKRLS.
v_s(
...,
type = "tpf",
knots = NULL,
by = NA,
xt = NULL,
by_re = TRUE,
force_vector = FALSE,
outer_okay = FALSE
)
... |
Variable name, e.g. |
type |
Default ( |
knots |
Default ( |
by |
A categorical or factor covariate to interact the spline with; for
example, |
xt |
Arguments passed to |
by_re |
Default ( |
force_vector |
Force that argument to |
outer_okay |
Default ( |
This function returns a list of class of vglmer_spline
that is
passed to unexported functions. It contains the arguments noted above where
...
is parsed into an argument called term
.
Chang, Qing, and Max Goplerud. 2024. "Generalized Kernel Regularized Least Squares." Political Analysis 32(2):157-171.
Wand, Matt P. and Ormerod, John T. 2008. "On Semiparametric Regression with O'Sullivan Penalized Splines". Australian & New Zealand Journal of Statistics. 50(2): 179-198.
Wood, Simon N. 2017. Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC.
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