Description Usage Arguments Details Value Author(s) References See Also
Construct the composition matrix object for automatically recalibrated age classes.
The internal function.
1  pclm.compmat(x, y, exposures = NULL, control = list())

x 
Vector with start of the interval for age/time classes. x * x.div must be an integer.
The appropriate correction for fractional intervals based on the interval multiple ( 
y 
Vector with counts, e.g. 
exposures 
Vector with exposures used to calculate smoothed mortality rates (see reference [1] and 
control 
List with additional parameters. See 
The details of matrix construction can be found in reference [1].
if bs.use == TRUE
then P or B splines are used instead of identity matrix (see pclm.control
).
The dimension of constructed composition matrix can be determined before its computation.
The shorter dimension equals to the length of data vector + 1, whereas the longer dimension is
determined by the function pclm.nclasses
and for zero.class.end == NULL
equals:
(x.div * (max(x)  min(x)) * m) * (1 + zero.class.frac) + 1
or
x.div * (zero.class.end  min(x)) * m + 1
otherwise,
where m
is an interval multiple calculated by pclm.interval.multiple
.
See also pclm.nclasses
.
List with components:

Composition matrix. 

Bspline base, Pspline base, or identity matrix. 

Corrected age/time vector. 

Corrected vector with counts. 

Length of the open interval in age classes. 

Vector with exposures if it was used to construct the composition matrix. 

Used control parameters, see 

List with warnings. 
Maciej J. Danko <[email protected]> <[email protected]>
Rizzi S, Gampe J, Eilers PHC. Efficient estimation of smooth distributions from coarsely grouped data. Am J Epidemiol. 2015;182:138?47.
Camarda, C. G. (2012). MortalitySmooth: An R Package for Smoothing Poisson Counts with PSplines. Journal of Statistical Software. 50, 124.
Hastie, T. J. (1992) Generalized additive models. Chapter 7 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
pclm.general
, pclm.control
, pclm.interval.multiple
, and pclm.nclasses
.
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