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- conformal predictions: confpred
- warnings (char2num used instead of coersion via as.numeric)
- %++% for function compositon
- New summary.effects methods with mediation proportion in the
output
- New hook: remove.hooks (see example ordinal.lvm)
- constrain methods now handled more robustly in sim.lvm allowing
both vectorized and non-vectorized functions
- Non-linear associations can now be specified with 'nonlinear'
method. Estimation via the 'twostage' function.
- Robust standard errors added to the IV estimator (2SLS)
- New cross-validation function: cv (and csplit function for
creating random sets).
* Version 1.5.0 <2017-03-16 Thu>
- lava.tobit is longer required for ordinal and censored
responses. Default is now to use the implementation in the 'mets' package.
- Composite likelihood method (complik) updated
- weight argument renamed to weights in agreement with lm, glm, coxph, ...
- sim.default: new argument 'arg' passed on to simulation function
- sim.default: new argument 'iter'. If TRUE the iteration number is
passed to function call as first argument (default FALSE)
- estimate.default: Wildcards/global expressions can now be used for specifying
contrasts based on the syntax of the functions 'contr', 'parsedesign'.
See examples on the help-page.
The argument transform.ci has been renamed to back.transform.
- correlation methods for matrices and data.frames (either pairwise or full MLE).
All methods can now return the influence functions.
- revdiag: dimnames are kept
- Combine: output updated
- forestplot: point estimates shown by default
- backdoor now works without conditioning set (yields all possible conditioning sets)
- New formula syntax: y+x~v+z same as c(y,x)~v+z
- spaghetti: trend.formula can now contain a factor statement on the rhs
* Version 1.4.7 <2017-01-26 Wed>
- Maintenance release
- models can now be specified as y1+y2~x1+x2 instead of c(y1,2y)~x1+x2
- sim method now has a seed argument
* Version 1.4.6 <2016-12-14 Wed>
- New backtrace algorithms for Newton-Raphson optimization routine.
- 'diagtest' updated.
* Version 1.4.5 <2016-10-25 Tue>
- New graph functions:
dsep: check for d-separation (conditional independence).
backdoor: check backdoor criterion of a graph (lvm-object).
adjMat: return adjaceny matrix.
edgeList: return edge list.
ancestors: return ancenstors of nodes.
descendants: return descendants of nodes.
- All simple paths in a graph can now be extracted with:
path(...,all=TRUE)
- Covariance parameters are now reference with ~~ instead of ,.
Applies to setting starting values in 'estimate', parameters in
'sim','compare','estimate',...
To use the old syntax set 'lava.options(symbol=c("~",","))'
- 'layout' argument added to lava.options (default 'dot')
- visNetwork support, new 'plot.engine' argument added to plot methods.
- bootstrap.lvmfit now default returns original estimates.
- print, transform methods updated (transform output).
- '+' operator overloaded for lvm and estimate objects (merge).
- New composite likelihood function: complik.
- New functions for simple association measures: riskcomp, rdiff, rratio,...
- New argument 'latent' in simulate method. If FALSE the latent
variables are dropped from the returned data.frame.
- modelsearch by default now shows both directional or undirectional
associations (type='all' vs type='cor').
- sim.default now stores timings. New print functions (data.table
like output).
- lvm model can now be updated with the 'sim' function,
for instance setting parameter values for the simulation only once:
m <- sim(m,p=p,...), with faster subsequent calls sim(m,n=n).
- estimate.default can now simulate p-values ('R' argument). Returns
an object which can also be used as input for 'estimate'.
- Bug fixes: NR optimization with back-tracing; fixed matrices.lvm when called
without variance parameters; fixed a bug in r-square computations.
- Contrast matrix can be specified with the function 'contr'.
* Version 1.4.4 <2016-08-13 Sat>
- estimate.default will now use the id-variable of an 'estimate'
object if the 'id' argument is left unspecified. For
multinomial,gkgamma,kappa additional arguments (...) are now
parsed on the 'estimate.default' (including id).
- Updated print/summary methods for
'estimate.default'. Sample/cluster-size added to output.
- Code clean-up and optimization. Smarter calculations of kronecker
products, and some regular expressions updated.
- New function 'predictlvm' which return jacobian.
- Intercepts can now be specified via parantheses, e.g., y ~ (-2) + x
- 'getoutcome' with sep argument for splitting '|' statements in
formulas.
- Partial gamma, gkgamma, updated (probability interpretation,
homogeneity tests removed)
- 'moments' function now returns conditional mean with multiple rows. Side effect fixed across multiple functions
- twostage function with support for mixture models
- Beta (Beta.lvm) and Finite Gaussian (GM2.lvm,GM3.lvm) Mixtures
added.
- 'sim': parameters can now be specified as part of '...'
- summary.sim: calculate Wald CI if confint=TRUE, otherwise use the
user supplied confidence limits.
- Clopper-pearson intervals and exact binomial tests added to 'diagtest'.
- Interval censoring with 'normal' estimator, which now also works
with 'binary' definitions.
- default plot style updated.
* Version 1.4.3 <2016-04-11 Mon>
- partial gamma coefficients (gkgamma)
- Unit tests works with new testthat version
- Avoid trying to fork new processes on windows (bootstrap,sim.default)
* Version 1.4.2 <2016-04-05 Wed>
- Code optimization and minor bug fixes
- Travis-CI, unit-tests
- glm estimator update (censored regression)
- polychoric correlations (pcor)
- New utility functions: wrapvec, offdiag
- simulation: regression design on parameters (see weibull +
variance hetereogeneity example in help('sim'))
- Byte compile by default
* Version 1.4.1 <2015-06-13 Sat>
- New plot.estimate method
- Documentation and examples updated
* Version 1.4.0 <2015-02-15 Sun>
- Linear measurement error model: 'measurement.error'
- Diagnostic tests: 'diagtest'
- 'plotConf' updated with support for special function terms (I, poly, ns, ...).
Old version is available (not in namespace) as lava:::plotConf0
- Pareto distribution: 'pareto.lvm'
- Code clean-up/optimization: 'EventTime', 'stack'
- 'estimate.default' new syntax for contrast specification (parsedesign)
- 'regression.lvm' with y,x argument (as alias for to,from)
- plot longitudinal data: 'spaghetti'
- Examples updated
* Version 1.3.0 <2014-11-18 Tue>
- New syntax for categorical predictors (method 'categorical' and
argument 'additive=FALSE' with 'regression method)
- Argument 'intervals' added to 'ones.lvm' for piece-wise constant effects
- Argument 'average=TRUE' now needed for empirical averages in estimate.default
- Fixed a bug in score.glm (with weights and offset) introduced in version 1.2.6
- estimate.default:
- small-sample corrections
- Default id from row names in estimate.default (used with merge method)
- iid decompostion also returned for hypothesis contrasts
- keep argument added to estimate.default and merge
- labels argument added to estimate.default
- 'images' function for visualization of tabular data added to namespace
- 'ksmooth' and 'surface' for surface estimation and visualization of bivariate data and functions
- 'dsort': Sort data.frames
- general multivariate distributions in simulations. see example in 'sim'
- 'or2prob', 'tetrachoric' for conversion from OR to probabilities
(and tetrachoric correlations).
'prob.normal': calculates probabilities from threshold model given thresholds and variance
See also mets:::assoc for calculations of kappa, gamma, uncer.coef.
'normal.threshold': returns thresholds,variance,mu from model with
categorical outcomes.
- Multiple testing routines: closed.testing, p.correct, ...
- 'Missing' method updated with a simple 'suffix' argument
- Back-tracing updated in Newton-Raphson routine
* Version 1.2.6 <2014-05-07 Wed>
- New 'stack' function for two-stage estimation (via 'estimate' objects)
- New 'blocksample' function for resampling clustered data.
- New function 'Missing' to generate complex missing data patterns
- Weibull parametrization of 'coxWeibull.lvm' rolled back
(ver. 1.2.4). The function 'weibull.lvm' now leads to Accelerated
Failure Time model (see examples of 'eventTime')
- iid function cleanup (new 'bread' attribute).
iid.glm now gives correct estimated influence functions for
'quasi' link (constant variance)
- Parameter constraints on (co)variance parameters now possible with
the syntax lvm(...,y~~a*x) (corresponding to
covariance(...,y~x)<-"a")
- Some additional utilities: pdfconvert, scheffe, images, click. confband
updated with 'polygon' argument.
- New function getMplus: Import results from Mplus
- New function getSAS: Import SAS ODS
- New 'edgecolor' argument of plot-function
* Version 1.2.5 <2014-03-13 Thu>
- 'merge' method added for combining 'estimate' objects
- Adjustments to starting values
- Function 'categorical' for adding categorical predictors to
simulation model
- Improved flexibility in simulations with 'transform','constrain'
(ex: categorical predictors)
- Added 'dataid' argument to estimate.default allowing different id
for 'data' and i.i.d. decomposition of model parameter estimates.
With the argument 'stack=FALSE' influence functions within
clusters will not be stacked together.
- R-squared values (+ approximate standard
errors/i.i.d. decomposition) via 'rsq(model,TRUE)'
- New infrastructure for adding additional parameters to models (no
user-visible changes).
- multinomial function for calculating influence curves for
multinomial probabilities. 'gammagk' and 'kappa' methods for
calculating Goodman-Kruskals gamma and Cohens kappa coefficients.
- ordreg function for univariate ordinal regression models
- iid methods for data.frames/matrices (empirical mean and variance)
- Support for using 'mets::cluster.index' in GEE-type models (much
faster).
- plotConf updated (vcov argument added and more graphical arguments
parsed to plotting functions)
- Additional unit-tests implemented
- New 'forestplot' and 'Combine' functions
- Covariance structure may now be specified using '~~', e.g.
'lvm(c(y,v)~~z+u)' specifies correlation between residuals of
(y,z),(y,u),(v,z),(v,u).
* Version 1.2.4 <2013-12-01 Sun>
- Avoid estimating IC in 'estimate.default' when 'vcov' argument is
given.
- New default starting values
- Time-varying effects via 'timedep'
- R-squared added to summary
- alias: covariance->variance
- added size argument to binomial.lvm;
* Version 1.2.3 <2013-10-27 Sun>
- 'subset' argument added to estimate.default. Calculates empirical
averages conditional on subsets of data
- Improved output from compare/estimate functions
- Minor bug fixes (plot, predict)
- sim: Piecewise constant rates with coxEponential.lvm. New
aalenExponential.lvm function for additive models. Functions
ones.lvm and sequence.lvm for deterministic variables.
* Version 1.2.2 <2013-07-10 Wed>
- Regression parameters are now by default referenced using '~',
e.g. "y~x" instead of "y<-x". Applies to setting starting values
in 'estimate', parameters in 'sim','compare','estimate',....
To use the old syntax set 'lava.options(symbol=c("<-","<->"))'
- Newton-Raphson/scoring procedure updated
- Search-interval for profile likelihood CI improved (for variance
parameters)
- 'estimate.default' updated (LRT)
- 'iid' updated (variance now obtained as tensor product of the result)
- progress bar for 'bootstrap' and 'modelsearch'
- various minor bug fixes
- new functions: Expand (expand.grid wrapper), By (by wrapper)
* Version 1.2.1 <2013-05-10 Fri>
- Optimization + minor bug fixes
* Version 1.2.0 <2013-03-28 Thu>
- New method 'iid' for extracting i.i.d. decomposition (influence
functions) from model objects (e.g. glm, lvm, ...)
- Method 'estimate' can now be used on model objects to transform
parameters (Delta method) or conduct Wald tests. Average effects,
i.e. averaging functionals over the empirical distribution is also
possible including calculation of standard errors.
- 'curereg' function for estimating mixtures of binary data.
- Instrumental Variable (IV) estimator (two-stage
least-squares) optimized.
- New distributions: Gamma.lvm, coxWeibull.lvm, coxExponential.lvm,
coxGompertz.lvm. New method 'eventTime' (for simulation of
competing risks data)
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