Description Usage Arguments Details Value Author(s) References See Also Examples
Main procedure to calculate PCLM with automated step.
1 2 | pclm.general(x, y, count.type = c("DX", "LX"), out.step = "auto",
exposures = NULL, control = list())
|
x |
Vector with start of the interval for age/time classes. |
y |
Vector with counts, e.g. |
count.type |
Type of the data, deaths( |
out.step |
Age interval length in output aggregated life-table. If set to |
exposures |
Optional exposures to calculate smooth mortality rates.
A vector of the same length as |
control |
List with additional parameters. See |
The function has four major steps:
Calculate interval multiple (pclm.interval.multiple
to remove fractional parts from x
vector.
The removal of fractional parts is necessary to build composition matrix.
Calculate composition matrix using pclm.compmat
.
Fit PCLM model using pclm.opt
.
Calculate aggregated (grouped) life-table using pclm.aggregate
.
More details for PCLM algorithm can be found in reference [1], but see also pclm.fit
and pclm.compmat
.
The output is of "pclm"
class with the components:
|
Life-table based on aggregated PCLM fit and defined by |
|
Life-table based on original (raw) PCLM fit. |
|
PCLM fit used to construct life-tables. |
|
Interval multiple, see |
|
Value of |
|
Interval length of aggregated life-table, see |
|
Used control parameters, see |
|
List with warnings. |
Maciej J. Danko <danko@demogr.mpg.de> <maciej.danko@gmail.com>
Rizzi S, Gampe J, Eilers PHC. Efficient estimation of smooth distributions from coarsely grouped data. Am J Epidemiol. 2015;182:138?47.
Rizzi S, Thinggaard M, Engholm G, et al. Comparison of non-parametric methods for ungrouping coarsely aggregated data. BMC Medical Research Methodology. 2016;16:59. doi:10.1186/s12874-016-0157-8.
pclm.fit
, pclm.compmat
, pclm.interval.multiple
, and pclm.nclasses
.
1 2 | # The examples with use of the \code{pash} object are presented in \link{pclm.fit}.
# Explicit examples of use \code{pclm.general} (especially how to use exposures) are to be written in a next package release.
|
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