Constructs a set of basis vectors for distances between distributed lag points, and apply as a linear transformation of a concentration matrix.
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a vector of values to construct the basis from. Missing values are not allowed
a covariate matrix (or object that can be coerced to a
arguments to be passed to
These functions are little more than convenient
wrappers to the function
basis and the
SmoothLag class constructor. They are intended to
simplify the task of specifying lag terms in a model
The functions compute a set of basis vectors for
x and applies this basis as a linear transformation
of the covariate/concentration matrix parameter,
Z. For example,
cr is used and
Z is the identity matrix,
the model fit will simply be the natural cubic spline of
Note that other basis extensions should always return an object
that inherits from
An S4 object of class
cr: natural cubic radial basis spline
sm: user-defined smoothing
Rupert D, Wand MP, & Carroll RJ (2003) Semiparametric Regression. New York: Cambridge University Press.
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