Releases: USCbiostats/LUCIDus
Releases · USCbiostats/LUCIDus
LUCIDus v2.2.1
LUCIDus v2.2
New features
- New function
lucid
: an estimation function integrating model and variable selection. We recommend user to use this new function for estimating LUCID models. It calls the workhorse functionsest_lucid
andtune_lucid
in the back-end.
Major changes
- Rename
est.lucid
andboot.lucid
toest_lucid
andboot_lucid
. - Update vignette accordingly.
- Use
mclust
to choose the optimal geometric model for omics data Z by default.
LUCIDus v2.1.5-1
fix error messages in testing.
LUCIDus v2.1.5
New features
- Add progress bar for
boot.lucid
function to track how many iterations are done. - Add
verbose
parameter inest.lucid
to disable automatic output in R console.
Other changes
- Fix bug for
boot.lucid
- Fix bug for
predict_lucid
LUCIDus v2.1.2
New Features:
- Use log-sum-exponential trick to avoid over/underflow
- Implement the GMM with missing data method (Zhang 2021) for estimating the association X->Z
- Add more checks for data input format
- Add new option -
init_impute
for initializing imputation of missing data - Add new parameter -
seed
to conveniently set random seed for EM algorithm
Other Changes:
- Disable
glmnet
when estimating the association G->X sinceglmnet
is not compatible with single exposure scenario - Delete unused parameters in
boot.lucid
- Deprecate unnecessary parameters in
def.lucd
LUCIDus v2.1.1
- Use Ridge regression to estimate G to X effect in order to stabilize effect estimate
- Fix bugs in estimating binary outcome
LUCIDus 2.1.0
New features
A new variable selection framework is applied to LUCID.
- A lasso type penalty is applied on the mean of biomarkers
- A glasso method is applied on the variance-covariance structure to achieve sparsity covariance matrix
- We apply a new variable selection criteria, which takes both mean and coviarnce matrix of biomarkers into account.
Other changes
- Fix bugs in
pred.lucid()
. Now it can predict both latent cluster and the outcome.
LUCIDus 2.0.0
This is a feature update to the whole package. It rewrite all the codes to make the model fitting procedure much faster (10 to 50 times) than v1.0.0. Also, the grammar of LUCID changed to a more user-friendly version. (Please note, this version is not backward compatible)
New features
est.lucid()
: previously calledest_lucid
. Fit the LUCID mode much faster; use mclust to initialize and produce a more stable estimate of the model; fix the bugs dealing with missing values in biomarker data.summary.lucid()
: previously calledsummary_lucid
. An S3 method function which can directly be called bysummary
; provide with a nice table with detailed interpretation of the model; add option to calculate 95% CI based on result returned byboot.lucid()
.plot.lucid()
: previously calledplot_lucid
. An S3 method function which can be directly called byplot
; change the color palette.predict.lucid()
: previously calledpred_lucid
. An S3 method function which can be directly called bypredict
.boot.lucid()
: previously calledboot_lucid
. Provide with a neat output.
Other changes
- Update the vignette.
- Updated the citation after getting published by the Bioinformatics;
- Minor bug fixes.
Preparation for CRAN submission
add citation, update vignette, spell checking