hcci
Interval Estimation of Linear Models with Heteroskedasticity
Calculates the interval estimates for the parameters of linear models with heteroscedastic regression using bootstrap - (Wild Bootstrap) and double bootstrap-t (Wild Bootstrap). It is also possible to calculate confidence intervals using the percentile bootstrap and percentile bootstrap double. The package can calculate consistent estimates of the covariance matrix of the parameters of linear regression models with heteroscedasticity of unknown form. The package also provides a function to consistently calculate the covariance matrix of the parameters of linear models with heteroscedasticity of unknown form. The bootstrap methods exported by the package are based on the master's thesis of the first author, available at https://raw.githubusercontent.com/prdm0/hcci/master/references/dissertacao_mestrado.pdf. The hcci package in previous versions was cited in the book VINOD, Hrishikesh D. Hands-on Intermediate Econometrics Using R: Templates for Learning Quantitative Methods and R Software. 2022, p. 441, ISBN 978-981-125-617-2 (hardcover). The simple bootstrap schemes are based on the works of Cribari-Neto F and Lima M. G. (2009) doi:10.1080/00949650801935327, while the double bootstrap schemes for the parameters that index the linear models with heteroscedasticity of unknown form are based on the works of Beran (1987) doi:10.2307/2336685. The use of bootstrap for the calculation of interval estimates in regression models with heteroscedasticity of unknown form from a weighting of the residuals was proposed by Wu (1986) doi:10.1214/aos/1176350142. This bootstrap scheme is known as weighted or wild bootstrap.
- Version1.2.0
- R versionunknown
- LicenseGPL (≥ 3)
- Needs compilation?No
- Last release01/21/2025
Documentation
Team
Pedro Rafael Diniz Marinho
MaintainerShow author detailsFrancisco Cribari Neto
Show author detailsRolesAuthor, Contributor
Insights
Last 30 days
This package has been downloaded 251 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.
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Last 365 days
This package has been downloaded 3,101 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jan 27, 2025 with 33 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
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