psNormal_Deriv | R Documentation |
psNormal_Deriv
provides the derivative
P-spline fit along x
.
psNormal_Deriv(
x,
y,
xl = min(x),
xr = max(x),
nseg = 10,
bdeg = 3,
pord = 2,
lambda = 1,
wts = rep(1, length(y)),
xgrid = x
)
x |
the vector for the continuous regressor of |
y |
the response vector, usually continuous data. |
xl |
the number for the min along |
xr |
the number for the max along |
nseg |
the number of evenly spaced segments between |
bdeg |
the number of the degree of the basis, usually 1, 2, or 3 (defalult). |
pord |
the number of the order of the difference penalty, usually 1, 2 (defalult), or 3. |
lambda |
the positive tuning parameter (default 1). |
wts |
the vector of weights, default is 1; 0/1 allowed. |
xgrid |
a scalar or a vector that gives the |
This is also a
support function needed for sim_psr
and sim_vcpsr
.
SISR (Eilers, Li, Marx, 2009).
coef |
a vector of |
B |
The B-spline matrix of dimensions |
fit |
a vector of |
pred |
a vector of |
d_coef |
a vector of |
B_d |
The first derivative B-spline matrix of dimensions |
d_fit |
a vector of |
d_pred |
a vector of length |
xl |
the number for the min along |
xr |
the number for the max along |
nseg |
the number of evenly spaced segments between |
bdeg |
the number of the degree of the basis, usually 1, 2, or 3 (default). |
pord |
the number of the order of the difference penalty, usually 1, 2 (default), or 3. |
lambda |
the positive tuning parameter (default 1). |
Paul Eilers and Brian Marx
Marx, B. D. (2015). Varying-coefficient single-index signal regression. Chemometrics and Intelligent Laboratory Systems, 143, 111–121.
Eilers, P.H.C., B. Li, B.D. Marx (2009). Multivariate calibration with single-index signal regression, Chemometrics and Intellegent Laboratory Systems, 96(2), 196-202.
Eilers, P.H.C. and Marx, B.D. (2021). Practical Smoothing, The Joys of P-splines. Cambridge University Press.
sim_psr sim_vcpsr
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