ds.qlspline.RdThis function is based on the native R function qlspline from the
lspline package. This function computes the basis of piecewise-linear spline
such that, depending on the argument marginal, the coefficients can be interpreted as
(1) slopes of consecutive spline segments, or (2) slope change at consecutive knots.
ds.qlspline(
x,
q,
na.rm = TRUE,
marginal = FALSE,
names = NULL,
newobj = NULL,
datasources = NULL
)the name of the input numeric variable
numeric, a single scalar greater or equal to 2 for a number of equal-frequency intervals along x or a vector of numbers in (0; 1) specifying the quantiles explicitly.
logical, whether NA should be removed when calculating quantiles, passed to na.rm of quantile. Default set to TRUE
logical, how to parametrize the spline, see Details
character, vector of names for constructed variables
a character string that provides the name for the output
variable that is stored on the data servers. Default qlspline.newobj.
a list of DSConnection-class
objects obtained after login. If the datasources argument is not specified
the default set of connections will be used: see datashield.connections_default.
an object of class "lspline" and "matrix", which its name is specified by the
newobj argument (or its default name "qlspline.newobj"), is assigned on the serverside.
If marginal is FALSE (default) the coefficients of the spline correspond to slopes of the consecutive segments. If it is TRUE the first coefficient correspond to the slope of the first segment. The consecutive coefficients correspond to the change in slope as compared to the previous segment. Function qlspline wraps lspline and calculates the knot positions to be at quantiles of x. If q is a numerical scalar greater or equal to 2, the quantiles are computed at seq(0, 1, length.out = q + 1)[-c(1, q+1)], i.e. knots are at q-tiles of the distribution of x. Alternatively, q can be a vector of values in [0; 1] specifying the quantile probabilities directly (the vector is passed to argument probs of quantile).