Defines a term \(\int^{s_{hi, i}}_{s_{lo, i}} f(X_i(s), s, t) ds\) for
inclusion in an mgcv::gam-formula (or bam or gamm or
gamm4:::gamm) as constructed by pffr. Defaults to a
cubic tensor product B-spline with marginal second differences penalties for
\(f(X_i(s), s, t)\) and integration over the entire range \([s_{lo, i},
s_{hi, i}] = [\min(s_i), \max(s_i)]\). Can't deal with any missing \(X(s)\),
unequal lengths of \(X_i(s)\) not (yet?) possible. Unequal ranges for
different \(X_i(s)\) should work. \(X_i(s)\) is assumed to be numeric.
sff() IS AN EXPERIMENTAL FEATURE AND NOT WELL TESTED YET -- USE AT
YOUR OWN RISK.
sff(X, yind, xind = seq(0, 1, l = ncol(X)), basistype = c("te", "t2", "s"),
integration = c("simpson", "trapezoidal"), L = NULL, limits = NULL,
splinepars = list(bs = "ps", m = c(2, 2, 2)))an n by ncol(xind) matrix of function evaluations
\(X_i(s_{i1}),\dots, X_i(s_{iS})\); \(i=1,\dots,n\).
DEPRECATED matrix (or vector) of indices of evaluations of \(Y_i(t)\); i.e. matrix with rows \((t_{i1},\dots,t_{iT})\); no longer used.
vector of indices of evaluations of \(X_i(s)\), i.e, \((s_{1},\dots,s_{S})\)
method used for numerical integration. Defaults to
"simpson"'s rule. Alternatively and for non-equidistant grids,
"trapezoidal".
optional: an n by ncol(xind) giving the weights for the
numerical integration over \(s\).
defaults to NULL for integration across the entire range of
\(X(s)\), otherwise specifies the integration limits \(s_{hi, i},
s_{lo, i}\): either one of "s<t" or "s<=t" for \((s_{hi,
i}, s_{lo, i}) = (0, t)\) or a function that takes s as the first and
t as the second argument and returns TRUE for combinations of values
(s,t) if s falls into the integration range for the given
t. This is an experimental feature and not well tested yet; use at
your own risk.
a list containing
call a "call" to
te (or s, t2)
using the appropriately constructed covariate and weight matrices (see
linear.functional.terms)
data a list
containing the necessary covariate and weight matrices