Changelog
Source:NEWS.md
nestedLogit 0.3.2
CRAN release: 2023-06-22
- new
Effect
method for"nestedLogit"
objects to create effect displays. - add Effect example to vignette
nestedLogit 0.3.1
- correct buglet in
as.data.frame
method whennewdata
has one column -
predict.nestedLogit()
now includes thenewdata
data frame as an additional component (.data
) in its result. Consequently, thenewdata
argument is no longer required in theas.data.frame
method.
nestedLogit 0.3.0
CRAN release: 2023-05-30
This is a major enhancement to the package, adding computations of standard errors and confidence intervals to predicted probabilities and logits.
Enhancements
- The
predict()
method now computes standard errors for probabilities and logits using the delta method. These can be obtained for either the response probabilities (and equivalent logits) or for the predicted log odds of the individual dichotomies. - A
confint()
method for the result ofpredict()
generates the corresponding confidence intervals. -
as.data.frame()
methods for predicted values, either for the nested logit model or for the separate dichotomies converts these to a data frame in long format, handy for usingggplot()
. - Added a
confint()
method for predicted probabilities and logits - The
plot()
method for"nestedLogit"
objects now plots confidence intervals for predicted probabilities. - A new vignette, “standard-errors”, describes the mathematics behind the standard error calculations.
- An old vignette on plotting methods was completely re-written using the new
predict()
methods and focusing exclusively on `ggplot2().
Other
- Added an example of
lobstr::tree()
to print nested lists - Now use
fig.show="hold"
to keeppar(op)
with the code.
nestedLogit 0.2.0
- Now allow dichotomies to be specified by a nested (recursive) of binary splits of the categories [suggestion of Achim Zeileis]
- The model object is now of class “nestedLogit” for uniformity.
- A basic
plot()
method now operational - Added a
linearHypothesis()
method to give Wald tests for hypotheses about coefficients or their linear combinations. - Expanded vignette to illustrate some other methods.
- Added a
models()
generic and method to extract separate models from the"nestedLogit"
object - Added a
logLike()
method, and through it, getsAIC()
andBIC()
- Reorganized documentation to separate nested hypothesis methods.