- minir update, the JSS paper is cited and used in the CITATION file
-
major update, mlogit now depends on dfidx, mlogit.data, mFormula and index are deprecated
-
the name of the coefficients is changed, i.e. air:income is now income:air
- some numerical disperancies were caused by Rout.save files. Some IGNORE tags are introduced to fix that.
- bug in model.frame : indexing by a factor and not a character to get the relevant subset of id in the index
-
a new package version which coincides with the Journal of Statistical Software article
-
some bugs fixed in the vignettes (citet/citep replaced by markdown-like commands), the figure is added in the mixed logit vignette
-
Rout.save files are added in the test directory
-
effects.mlogit now returns a matrix
-
the R files for the vignettes are added (they were note while building the package on RForge)
-
thank's to Mallick Hossain, a bug is fixed in the logsum function
-
the Cracker, Catsup and Car data set are back in mlogit since AER, flexmix and mlogitBMA run examples based on them.
-
the alt vector in the index is now carrefully checked in case of alternative subseting or reference level change.
-
the main vignette is improved, writen in markdown and now and split by sections
-
the Exercises vignette is splited and is now writen in markdown
-
importantly, the Cholesky matrix is now coerced to a vector by rows and note by columns.
-
the mlogit function was checked and improved.
-
implementation of the computation of the standard deviations of the covariance matrix of the random parameters, using the delta method.
-
some data sets are removed
-
zbu and zbt distributions are added : these are one-parameter distributions for which the lower bond is 0,
-
a logsum function is provided to compute the log-sum or the inclusive utility of a random utility model,
-
group-hetheroscedastic model can be estimated by setting the relevant covariates in the 4th part of the formula,
-
the linear predictor is now returned by mlogit,
-
correlation can still be a boolean, but can also be a character vector if one wants that a subset of the random parameters being correlated.
-
the RiskyTransport data set (used in the vignette to illustrate the estimation of the mixed logit model
-
the NOx data set (used in the vignette to illustrate the estimation of the multinomial and group-heteroscedastic logit model),
-
the JapaneseFDI data set (used in the vignette to illustrate the estimation of the nested logit model)
A new vignette called mlogit2 is added ; this is the draft version of an article submitted to the Journal of Statistical Software ; it is less exhaustive, but better writen thant the original mlogit vignette.
-
the id series (one observation per choice situation) was badly constructed, it is now fixed
-
the levels of the choice variable are now equalized to the those of the alt variable, allowing the case were some alternatives are never chosen
-
mlogit is now able to estimate models with singular matrix of covariates. At the end of model.matrix.mformula, the linear dependent columns of X are removed
-
there was a bug in the triangular distribution which is now fixed
-
bug in the effects method fixed
-
the list of primes used to generate halton sequences was too short, its length has been increased
-
halton sequences where used to estimate mixed logit even for the default value of halton (NULL), this has been fixed
-
the contribution of each observation to the gradient is not returned as the 'gradient' element of mlogit objects
-
the distributions are now checked for rpar and an error is returned in case of unknown distribution
- some sys.frame() changed to parent.frame()
-
ranked-order models can be now estimated ; a new argument called 'ranked' is introduced in mlogit.data which performs the relevant transformation of the data.frame. The estimated model is then a standard multinomial logit model
-
multinomial probit model is now estimated by setting the new probit arguments to TRUE
-
for the mixed logit model, different draws are now used for each observation
-
a predict method is now available for mlogit objects
-
a coef method is added which removes the fixed argument
-
constPar can now be a named numeric vector. In this case, default starting values are changed according to constPar
-
the vcov method for mlogit objects is greatly enhanced.
-
mlogit objects now have two elements which indicate the fitted probabilities : fitted is the estimated probability for the outcome and probabilities contains the fitted probabilities for all the alternatives
-
mentions to 'alt' in the names of the effects is canceled ; moreover, the intercepts are now called altname:('intercept')
-
a 'choice' attribute is added to mlogit.data objects
-
an effects method is provided, which computes the marginal effects of a covariate
- all the rda files are now compressed
-
all the models could normally be estimated on unbalanced data
-
the three tests are added, i.e. a new scoretest function and specific methods for waldtest and lrtest from the lmtest package
-
the model.matrix method for mlogit objects is now exported
-
mFormula modified so that models can be updated
-
likelihood has been rewriten for the heteroscedastic logit model, the computation is now much faster
-
nested logit models with overlapping nests are now supported; nests = "pcl" enables the estimation of the pair combinatorial logit model
-
the norm argument is added to rpar
-
the logLik argument is now of class logLik
-
mlogit.data is modified so that an id argument can be used with data in long shape
-
the argument of mlogit.data used to define longitudinal data is now called id.var
-
mlogit.lnls is corrected so that the estimation of multinomial models can handle unbalanced data (pb with Reduce)
-
the three tests are temporary removed
- a bug in mFormula (effects vs variable) is fixed
-
a third part of the formula is added : it concerns alternative specific variables with alternative specific coefficients
-
improved presentation for the Fishing dataset.
-
a bug (forgotten drop = FALSE) corrected in model.matrix.mFormula
-
Electricity and ModeCanada datasets are added
-
if the choice variable is not an ordered factor, use as.factor() instead of class() <- "factor"
-
cov.mlogit, cor.mlogit, rpar , med, rg, stdev, mean functions are added to extract and analyse random coefficients.
-
a panel argument is added to mlogit so that mixed models with repeated observation can be estimated using panel methods or not
-
a problem with the weights argument is fixed
-
the estimation of nested logit models with a unique elasticity is now possible using un.nest.el = TRUE
-
the estimation of nested logit models can now be done with or without normalization depending on the value of the argument unscaled
-
mlogit didn't work when the dependent variable was an ordered factor in a "wide-shaped" data.frame.
-
the reflevel argument didn't work any more in version 0.1-3.
-
major change, most of the package has been rewriten
-
it is now possible to estimate heteroscedastic, nested and mixed effects logit model
-
the package doesn't depend any more on maxLik but a specific optimization function is provided for efficiency reason
-
robust inference is provided with meat and estfunc methods defined for mlogit models.
-
subset argument is added to mlogit so that the model may be estimated on a subset of alternatives.
-
reflevel argument is added to mlogit which defines the base alternative.
-
hmftest implements the Hausman McFadden test for the IIA hypothesis.
-
mlogit.data function has been rewriten. It now use the reshape function.
-
logitform class is provided to describe a logit model: update, model.matrix and model.frame methods are available.