Mort2Dsmooth.estimate {MortalitySmooth} | R Documentation |
This is an internal function of package MortalitySmooth
which
estimates coefficients and computes diagnostics for two-dimensional
penalized B-splines for two given smoothing parameters within the
function Mort2Dsmooth
.
Mort2Dsmooth.estimate(x, y, Z, offset, psi2, wei, Bx, By, nbx, nby, RTBx, RTBy, lambdas, Px, Py, a.init, MON, TOL, MAX.IT)
x |
Vector for the abscissa of data. |
y |
Vector for the ordinate of data. |
Z |
Matrix of counts response. |
offset |
Matrix with an a priori known component (optional). |
psi2 |
Overdispersion parameter. |
wei |
An optional matrix of weights to be used in the fitting process. |
Bx |
B-splines basis for the x-axis. |
By |
B-splines basis for the y-axis. |
nbx |
number of B-splines for the x-axis. |
nby |
number of B-splines for the y-axis. |
RTBx |
tensors product of B-splines basis for the x-axis. |
RTBy |
tensors product of B-splines basis for the y-axis. |
lambdas |
Vector with the two smoothing parameters. |
Px |
Penalty factor for the x-axis. |
Py |
Penalty factor for the y-axis. |
a.init |
Matrix with the initial coefficients. |
MON |
Logical switch indicating if monitoring is required. |
TOL |
The tolerance level in the IWLS algorithm. |
MAX.IT |
The maximum number of iterations. |
Internal function used in Mort2Dsmooth
for estimating
coefficients and computing diagnostics.
A list with components:
a |
fitted coefficients (in a matrix). |
h |
diagonal of the hat-matrix. |
df |
effective dimension of used degree of freedom. |
aic |
Akaike's Information Criterion. |
bic |
Bayesian Information Criterion. |
dev |
Poisson deviance. |
tol |
tolerance level. |
Carlo G Camarda
Mort2Dsmooth.update
,
Mort2Dsmooth
.