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) , 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) . 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) . This bootstrap scheme is known as weighted or wild bootstrap.


hcci: Interval estimation for the parameters of linear models with heteroskedasticity (Wild Bootstrap)

See package website: https://prdm0.github.io/hcci/.

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This package calculates the interval estimates for the parameters of linear models 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. It is possible to calculate consistent estimates of the covariance matrix of the parameters of linear regression models with heteroskedasticity of unknown form. The package also provides function to calculate consistently the covariance matrix of the parameters of linear models with heteroskedasticity of unknown form.

Installation

install.packages("hcci")


A package manual may be found at: https://cran.r-project.org/web/packages/hcci/hcci.pdf. The versions of the hcci package are separated by tags.

CRAN Project: https://CRAN.R-project.org/package=hcci.

Reference manual

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install.packages("hcci")

1.2.0 by Pedro Rafael Diniz Marinho, 2 years ago


https://github.com/prdm0/hcci


Report a bug at https://github.com/prdm0/hcci/issues


Browse source code at https://github.com/cran/hcci


Authors: Pedro Rafael Diniz Marinho [aut, cre] , Francisco Cribari Neto [aut, ctb]


Documentation:   PDF Manual  


GPL (>= 3) license



Suggested by BioStatR.


See at CRAN