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Merge pull request #36 from jhelvy/rc-v0.7.0
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Rc v0.7.0
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jhelvy authored Jun 16, 2022
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2 changes: 2 additions & 0 deletions CRAN-RELEASE
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This package was submitted to CRAN on 2022-06-16.
Once it is accepted, delete this file and tag the release (commit f56b55c).
2 changes: 1 addition & 1 deletion DESCRIPTION
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Package: logitr
Title: Logit Models w/Preference & WTP Space Utility Parameterizations
Version: 0.6.1
Version: 0.7.0
Authors@R: c(
person(given = "John",
family = "Helveston",
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10 changes: 10 additions & 0 deletions NEWS.md
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# logitr 0.7.0

- A new vignette on benchmarking was added which tests the package speed against other similar packages.
- A new data set, `runtimes`, was included, which is exported from the colab notebook used for benchmarking here: https://colab.research.google.com/drive/1vYlBdJd4xCV43UwJ33XXpO3Ys8xWkuxx?usp=sharing
- Sobol draws are supported via a new `drawType` argument.
- A warning is displayed against using Halton draws after 5 random variables have been specified in a mixed logit model. Users are encouraged to switch to using Sobol draws and increasing the number of draws to at least 200.
- Changed the argument name `price` to `scalePar` to be more general.
- Changed the argument name `randPrice` to `randScale` to be more general.
- The `modelSpace` argument is no longer required for specifying a WTP space model as it is redundant. Including a `scalePar` argument is enough to determine that it is a WTP space model.

# logitr 0.6.1

- Fixes error on some of the gradient tests from 0.6.0 release. The gradient tests were sensitive to the random starting parameters, so I modified how the starting parameters were set for the first iteration of a multistart loop such that they would be more consistent.
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12 changes: 2 additions & 10 deletions README.md
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Expand Up @@ -66,14 +66,6 @@ View the [basic
usage](https://jhelvy.github.io/logitr/articles/basic_usage.html) page
for details on how to use **logitr** to estimate models.

## Related software

If you are a Python user, [`xlogit`](https://github.com/arteagac/xlogit)
is a similar package built in Python. It has a similar user interface
for defining models, and it is even faster than logitr as it uses
GPU-accelerated estimation for mixed logit models. It is a good resource
for comparing results with those from logitr.

## Author, Version, and License Information

- Author: *John Paul Helveston* <https://www.jhelvy.com/>
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#>
#> John Paul Helveston (2022). logitr: Fast Estimation of Multinomial
#> and Mixed Logit Models with Preference Space and Willingness to Pay
#> Space Utility Parameterizations. R package version 0.6.1
#> Space Utility Parameterizations.
#>
#> A BibTeX entry for LaTeX users is
#>
#> @Manual{,
#> title = {logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations},
#> author = {John Paul Helveston},
#> year = {2022},
#> note = {R package version 0.6.1},
#> note = {R package},
#> url = {https://jhelvy.github.io/logitr/},
#> }
```
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0 errors | 0 warnings | 0 notes

## Notes
* This is a new release
* This is a new release.
* Apologies for another release so soon (it's been a productive week) - this will be the last for at least a month or longer.
4 changes: 2 additions & 2 deletions inst/CITATION
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Expand Up @@ -5,7 +5,7 @@ citEntry(
title = "logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations",
author = "John Paul Helveston",
year = "2022",
note = "R package version 0.6.1",
note = "R package",
url = "https://jhelvy.github.io/logitr/",
textVersion = "John Paul Helveston (2022). logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations. R package version 0.6.1"
textVersion = "John Paul Helveston (2022). logitr: Fast Estimation of Multinomial and Mixed Logit Models with Preference Space and Willingness to Pay Space Utility Parameterizations."
)

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