dsidr {assist} | R Documentation |
To calculate a spline estimate with a single smoothing parameter
dsidr(y, q, s=NULL, weight=NULL, vmu="v", varht=NULL, limnla=c(-10, 3), job=-1, tol=0)
y |
a numerical vector representing the response. |
q |
a square matrix of the same order as the length of y, with elements equal to the reproducing kernel evaluated at the design points. |
s |
the design matrix of the null space H_0 of size (length(y),dim(H_0)), with elements equal to the bases of H_0 evaluated at design points. Default is NULL, representing an empty NULL space. |
weight |
A weight matrix for penalized weighted least-square: (y-f)'W(y-f)+nλ J(f). Default is NULL for iid random errors. |
vmu |
a character string specifying a method for choosing the smoothing parameter. "v", "m" and "u" represent GCV, GML and UBR respectively. "u~", only used for non-Gaussian family, specifies UBR with estimated variance. Default is "v". |
varht |
needed only when vmu="u", which gives the fixed variance in calculation of the UBR function. Default is NULL. |
limnla |
a vector of length 2, specifying a search range for the n times smoothing parameter on log10 scale. Default is (-10, 3). |
job |
an integer representing the optimization method used to find the smoothing parameter. The options are job=-1: golden-section search on (limnla(1), limnla(2)); job=0: golden-section search with interval specified automatically; job >0: regular grid search on [limnla(1), limnla(2)] with #(grids) = job + 1. Default is -1. |
tol |
tolerance for truncation used in `dsidr'. Default is 0.0, which sets to square of machine precision. |
info |
an integer that provides error message. info=0 indicates normal termination, info=-1 indicates dimension error, info=-2 indicates F_{2}^{T} Q F_{2} !>= 0, info=-3 indicates vmu is out of scope, and info>0 indicates the matrix S is rank deficient with info=rank(S)+1. |
fit |
fitted values. |
c |
estimates of c. |
d |
estimates of d. |
resi |
vector of residuals. |
varht |
estimate of variance. |
nlaht |
the estimate of log10(nobs*lambda). |
limnla |
searching range for nlaht. |
score |
the minimum GCV/GML/UBR score at the estimated smoothing parameter. When job>0, it gives a vector of GCV/GML/UBR functions evaluated at regular grid points. |
df |
equavilent degree of freedom. |
nobs |
length(y), number of observations. |
nnull |
dim(H_0), number of bases. |
s,qraux,jpvt |
QR decomposition of S=FR, as from Linpack `dqrdc'. |
q |
first dim(H_0) columns gives F^{T} Q F_{1}, and its bottom-right corner gives tridiagonalization of F_{2}^{T} Q F_{2}. |
Chunlei Ke chunlei_ke@pstat.ucsb.edu and Yuedong Wang yuedong@pstat.ucsb.edu
Gu, C. (1989). RKPACK and its applications: Fitting smoothing spline models. Proceedings of the Statistical Computing Section, ASA, 42-51.
Wahba, G. (1990). Spline Models for Observational Data. SIAM, Vol. 59.