| NEWS | R Documentation |
Add exponential distribution (for Aalen additive hazards models).
Pay attention to model class when computing cumulative hazards.
Add log-cumulative hazards, log-odds, and odds for predictions and plots.
Allow permutations of single variables.
Update citation info.
Try harder to invert Hessians.
Update reference output.
Add support for nloptr (still experimental and thus switched off by default).
Make sure coef() always returns named argument.
Fix problem in as.Surv reported by Balint Tamasi.
Less paranoia in ‘bugfixes.R’.
Return Hessian for fixed parameters if requested.
Fix subsetting problem in R.numeric.
Allow to update offsets.
Add a bread method.
Check response variable against observations in data.
Make sure integers larger zero are handled correctly in R.
Implement resid method, ie the score wrt a constant.
Cox examples with Bernstein polynomials of log-time.
Arguments K and cheat where
ignored by confband when newdata
had multiple rows.
Computation of starting values more robust now.
Order of fixed parameters (fixed argument to mlt)
might have been wrong due to incomplete matching.
Add lty argument to plot.ctm.
update needs free coefficients only.
Internal interface changes.
Make sure transformation functions outside bounds are minus
or plus Inf.
Initial guestimates for ordered responses were incorrect and may potentially have led to nonsense results.
Some smaller improvements in computation of log-likelihoods and scores with respect to accuracy and speed.
print respects options(digits).
estfun, parm = coef(object, fixed = TRUE)) evaluates
scores for all model parameters, including fixed ones.
logLik(..., newdata, w) ignored weights w when
newdata was given. Same problem was also fixed for
estfun.
A paper describing version 1.0-0 of the mlt, basefun, and variables packages was accepted for publication in the Journal of Statistical Software 2018-03-05.
Documentation updates.
Use coneprog for getting the starting values.
logLik and estfun accept matrices as parm
argument for the evalution of log-likelihoods and scores
with subject-specific parameters (for example in transformation
trees or forests and boosting procedures.
q is forwarded to qmlt by predict.ctm now.
p is now prob in qmlt and thus predict.ctm.
Update citation.
Most Likely Transformations will be published in the Scandinavian Journal of Statistics.
Import package alabama.
as.Surv(R(Surv(...))) returns Surv(...),
useful for converting output by simulate
to Surv objects.
Add subset argument to update (for faster transformation
trees and forests).
Sum over score contributions with positive weight only when evaluating the gradient.
Having all response observations being interval-censored is allowed again (too heavy checking was in place).
Don't try to numerically check KKT conditions automatically.
Check for unused arguments in dots where necessary.
Make sure the score doesn't get too large (avoid division by near zero probabilities).
Improve survfit to compute non-parametric unconditional
probabilities for obtaining starting values in the presence of
censoring and truncation.
logLik with newdata argument ignored parm
and weights arguments.
estfun now also has a newdata argument.
Correct axes labelling when plotting quantile functions.
make sure names are correct in coef(model, fixed = FALSE).
check if any exact or interval-censored response with non-zero weight exists before trying to fit the model.
make checks a little more robust against huge diffs under Windows.
Fix two bugs in computation of log-likelihood for possibly
left-truncated responses such as Surv(start, time, status).
Add augmented lagrangian minimization (auglag() from package alabama).
Make optimiation procedure more general and adaptive, allow users to change defaults and even add their own optimiser.
fix bug when calling survfit for computing initial probabilities.
add bysim argument to simulate.
make sure checkGrad is respected by update.
predict computes q with K elements
if not given (as plot always did).
Make sure times are ordered before calling
survival::summary.survfit.
Introduce as.mlt generic.
Introduce a coef slot in ctm objects
and a corresponding coef<- and coef
method for setting and extracting coefficients
to and from unfitted conditional transformation models.
predict, simulate and plot
work on ctm objects (with meaningful coefficients)
now.
Some small improvements wrt run time and memory consumption.
Use theta = coef(object) as default starting parameters in update().
logLik has a new newdata argument.
simulate has a new q argument.
The mlt package was first published on CRAN.