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Abstract We introduce a new, open-source, Python-based package,extrabol, for inferring the bolometric light curve evolution of extragalactic thermal transients.extraboluses non-parametric Gaussian Process regression for light curve estimation that requires minimal user interaction.extrabolis available via GitHub.
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This content will become publicly available on March 1, 2026
Binscatter regressions
In this article, we introduce the packagebinsreg, which implements the binscatter methods developed by Cattaneo et al. (2024a, arXiv:2407.15276 [stat.EM]; 2024b,American Economic Review114: 1488–1514). The package comprises seven commands:binsreg, binslogit, binsprobit, binsqreg, binstest binspwc, andbinsregselect. The first four commands implement binscatter plotting, point estimation, and uncertainty quantification (confidence intervals and confidence bands) for least-squares linear binscatter regression (binsreg) and for nonlinear binscatter regression (binslogitfor logit regression,binsprobitfor. probit regression, andbinsqregfor quantile regression). The next two commands focus on pointwise and uniform inference:binstestimplements hypothesis testing procedures for parametric specifications and for nonparametric shape restrictions of the unknown regression function, whilebinspwcimplements multigroup pairwise statistical comparisons. The last command,binsregselect, implements. data-driven number-of-bins selectors. The commands offer binned scatterplots and allow for covariate adjustment, weighting, clustering, and multisample analysis, which is useful when studying treatment-effect heterogeneity in randomizec and observational studies, among many other features.
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- PAR ID:
- 10625548
- Publisher / Repository:
- Sage
- Date Published:
- Journal Name:
- The Stata Journal: Promoting communications on statistics and Stata
- Volume:
- 25
- Issue:
- 1
- ISSN:
- 1536-867X
- Page Range / eLocation ID:
- 3 to 50
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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