gdmudr {assist}  R Documentation 
To calculate a spline estimate with multiple smoothing parameters for nonGaussian data
gdmudr(y, q, s, family, vmu = "v", varht = NULL,
init = 0, theta = NULL, tol1 = 0, tol2 = 0, prec1 = 1e06,
maxit1 = 30, prec2 = 1e06, maxit2 = 30)
y 
a numerical vector representing the response, or a matrix of two columns for binomial data with the first column as the largest possible counts and the second column as the counts actually obsered. 
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 
family 
a string specifying the family of distribution. Families supported are "binary", "binomial", "poisson" and "gamma" for Bernoulli, binomial, poisson, and gamma distributions respectively. Canonical links are used except for Gamma family where log link is used. 
vmu 
a character string specifying a method for choosing the smoothing parameter. "v", "m" and "u" represent GCV, GML and UBR respectively.
"u 
varht 
needed only when vmu="u", which gives the fixed variance in calculation of the UBR function. Default is 1.0. 
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. 
theta 
If ‘init=1’, theta includes intial values for smoothing parameters. Default is NULL. 
tol1 
the tolerance for elements of w's. Default is 0.0 which sets to square of machine precision. 
tol2 
tolerance for truncation used in ‘dsidr’. Default is 0.0 which sets to square of machine precision. 
prec1 
precision requested for the minimum score value, where precision is the weaker of the absolute and relative precisions. Default is 1e06. 
maxit1 
maximum number of iterations allowed for DMUDR subroutine. Default is 30. 
prec2 
precision requested for stopping the iteration. Default is 
maxit2 
maximum number of iterations allowed for the iteration in GRKPACK. Default is 30. 
info 
an integer that provides error message. info=1 indicates dimension error,
info=2 idicates 
fit 
estimate of the function at design points. 
c 
estimates of c. 
d 
estimates of d. 
resi 
vector of working residuals. 
varht 
estimate of dispersion parameter. 
theta 
estimates of parameters 
nlaht 
the estimate of 
score 
the minimum GCV/GML/UBR score at the estimated smoothing parameters. 
df 
equavilent degree of freedom. 
nobs 
lengthofy, number of observations. 
nnull 

nq 
length(rk), number of reproducing kernels. 
s , q , y , init , maxit2 
changed from the inputs. 
Chunlei Ke chunlei_ke@yahoo.com and Yuedong Wang yuedong@pstat.ucsb.edu
Wahba, G. (1990). Spline Models for Observational Data. SIAM, Vol. 59.
Wang, Y. (1997). GRKPACK: Fitting Smoothing Spline ANOVA Models for Exponential Families. Communications in Statistics: Simulation and Computation, 24: 10371059.