dmudr {assist}R Documentation

Interface of dmudr subroutine in RKPACK


To calculate a spline estimate with multiple smoothing parameters


dmudr(y, q, s, weight = NULL, vmu = "v", theta = NULL, varht = NULL, 
    tol = 0, init = 0, prec = 1e-06, maxit = 30)


y a numerical vector representing the response.
q a list, or an array, of square matrices of the same order as the length of y, which are the reproducing kernels evaluated at the design points.
s the design matrix of the null space H_0 of size (length-of-y,dim(H_0)), with elements equal to the bases of H_0 evaluated at design points.
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".
theta If `init=1', theta includes intial values for smoothing parameters. Default is NULL.
varht needed only when vmu="u", which gives the fixed variance in calculation of the UBR function. Default is NULL.
tol the tolerance for truncation in the tridiagonalization. Default is 0.0.
init an integer of 0 or 1 indicating if initial values are provided for theta. If init=1, initial values are provided using theta. Default is 0.
prec precision requested for the minimum score value, where precision is the weaker of the absolute and relative precisions. Default is 1e-06.
maxit maximum number of iterations allowed. Default is 30.


info an integer that provides error message. info=-1 indicates dimension error, info=-2 indicates F_{2}^{T} Q_{*}^{theta} F_{2} !>= 0, info=-3 indicates tuning parameters are out of scope, info=-4 indicates fails to converge within maxite steps, info=-5 indicates fails to find a reasonable descent direction, 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.
theta estimates of parameters log10(theta).
nlaht the estimate of log10(nobs*λ).
score the minimum GCV/GML/UBR score at the estimated smoothing parameters.
df equavilent degree of freedom.
nobs length(y), number of observations.
nnull dim(H_0), number of bases.
nq length(rk), number of reproducing kernels.
s,q,y changed from the inputs.


Chunlei Ke and Yuedong Wang


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

See Also

dsidr, gdsidr, gdmudr, ssr

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