Return the model coefficients of a ppDiscSurv object
Arguments
- fit
a
ppDiscSurvobject.- lambda
values of the regularization parameter lambda at which coefficients are requested. For values of lambda not in the sequence of fitted models, linear interpolation is used.
- which
indices of the penalty parameter lambda at which predictions are required. By default, all indices are returned. If lambda is specified, this will override which.
- drop
whether to keep coefficient names
- ...
Examples
data(DiscTime)
data <- DiscTime$data
Event.char <- DiscTime$Event.char
prov.char <- DiscTime$prov.char
Z.char <- DiscTime$Z.char
Time.char <- DiscTime$Time.char
fit <- pp.DiscSurv(data, Event.char, prov.char, Z.char, Time.char)
coef(fit, lambda = fit$lambda)$alpha[, 1:5]
#> 0.1601 0.1458 0.1329 0.1211 0.1103
#> [Time: 0.53] -1.668065 -1.747753 -1.824209 -1.898663 -1.971909
#> [Time: 1.03] -1.480994 -1.526815 -1.571328 -1.615488 -1.659886
#> [Time: 3.92] -1.622145 -1.641556 -1.661848 -1.683563 -1.706991
#> [Time: 6.74] -1.251585 -1.257340 -1.264124 -1.272503 -1.282795
#> [Time: 12.5] -1.781635 -1.780095 -1.780526 -1.783340 -1.788771
coef(fit, lambda = fit$lambda)$gamma[, 1:5]
#> 0.1601 0.1458 0.1329 0.1211 0.1103
#> 1 0.0000000 0.0000000 0.000000 0.0000000 0.0000000
#> 2 -4.5665147 -4.3516946 -4.162992 -3.9945779 -3.8425705
#> 3 -0.7478311 -0.7116142 -0.682481 -0.6580980 -0.6367834
#> 4 1.2412090 1.1456446 1.059286 0.9815198 0.9121089
#> 5 -2.3399410 -2.1966372 -2.070536 -1.9577270 -1.8555876
coef(fit, lambda = fit$lambda)$beta[, 1:5]
#> 0.1601 0.1458 0.1329 0.1211 0.1103
#> Z1 0 -0.1735757 -0.3325774 -0.4793679 -0.6155647
#> Z2 0 0.0000000 0.0000000 0.0000000 0.0000000
#> Z3 0 0.0000000 0.0000000 0.0000000 0.0000000
#> Z4 0 0.0000000 0.0000000 0.0000000 0.0000000
#> Z5 0 0.0000000 0.0000000 0.0000000 0.0000000