PROC HAZARD's outhaz= dataset stores the converged estimates and the
asymptotic variance-covariance matrix at full double precision, where the
printed .lst carries about seven significant figures. For any quantity the
dataset holds, it is the better parity reference: print precision stops
being the binding constraint and optimizer convergence takes over.
Value
An hzr_outhaz object: a list with estimates (named numeric),
status (named integer, 1 free / 0 fixed), vcov (matrix over free
parameters, dimnames set) and flags (named numeric of model-structure
flags). When no parameter is free, vcov is a 0x0 matrix rather than
NULL, so check its dimensions rather than is.null().
Experimental
This function is experimental and its return shape is expected to change.
The result carries the fitted model, so predict.hzr_outhaz() predicts
from it – that is what the hzr_translate_sas(librefs = ) path emits –
but it is not a hazard object and none of the other hazard methods
apply to it. The _STATUS_ coding is asserted against a synthetic fixture,
so a real OUTHAZ= file using a different convention would yield an empty
vcov alongside a fully populated estimates.
Examples
f <- system.file("extdata", "outhaz-fixture.rds", package = "TemporalHazard")
if (nzchar(f)) str(hzr_read_outhaz(f))
#> List of 4
#> $ estimates: Named num [1:11] 0 0.0314 1.4142 0 0 ...
#> ..- attr(*, "names")= chr [1:11] "DELTA" "THALF" "NU" "M" ...
#> $ status : Named int [1:11] 0 1 1 0 0 0 0 0 1 1 ...
#> ..- attr(*, "names")= chr [1:11] "DELTA" "THALF" "NU" "M" ...
#> $ vcov : num [1:4, 1:4] 0.1013 0.0245 -0.0187 0.0138 0.0245 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:4] "THALF" "NU" "E0" "C0"
#> .. ..$ : chr [1:4] "THALF" "NU" "E0" "C0"
#> $ flags : Named num [1:6] 2 1 0 0 0 0
#> ..- attr(*, "names")= chr [1:6] "G1FLAG" "FIXDEL0" "FIXMNU1" "G3FLAG" ...
#> - attr(*, "class")= chr "hzr_outhaz"