posum.pop.matrix {posum} | R Documentation |
These two routines find the matrices mapping the model
parameter vector to either the population surface or the total death
rate surface. posum.pop.matrix
also deals with adults. The routines are
primarily designed as internal service routines.
posum.pop.matrix(b,d,t0=0,point.wise=TRUE) posum.death.matrix(b,d,fd)
b |
A fitted gam object for a posum model with at least the extra
variables target.dt and model.type . |
d |
A data frame defining the ages/times at which evaluation is required. It should
contain variables:
The latter two are not always required. |
t0 |
The initial time (posum.pop.matrix only). |
point.wise |
If this is true then the surfaces at each age, time point are
evaluated with spearate calls to predict.gam , which saves memory. If false
then there is just one call to predict.gam with one large data frame: this
is faster, but uses a large amount of memory. (posum.pop.matrix only). |
fd |
finite difference interval to use for obtaining death rates from type 1 models. |
The required matrices are obtained by calls to predict.gam()
which obtain matrices mapping parameters to evaluations of the model at particular
age, time points. Appropriate quadrature formulae are then applied to the matrix
rows.
The functions return the required matrices.
Simon N. Wood snw@st-and.ac.uk
Gu and Wahba (1991) Minimizing GCV/GML scores with multiple smoothing parameters via the Newton method. SIAM J. Sci. Statist. Comput. 12:383-398
Wood (2000) Modelling and Smoothing Parameter Estimation with Multiple Quadratic Penalties. JRSSB 62(2):413-428
Wood (2003) Thin Plate Regression Splines in press JRSSB
http://www.ruwpa.st-and.ac.uk/simon.html
posum
age.max
,
cm.splinefun
,
death.surface
,
hyman.filter
,
pcdr
,
population
,
population.data
,
population.surface
,
posum.atplot
,
posum.check
,
posum.con
,
posum.fit
,
posum.options
,
posum.plot
,
posum.stage
,
posum.stage.plot
,
posum.X
,
rec
,
sim.age.bound
,
spl.coef.conv
,
stage.bound
,
survival
,