Other packages > Find by keyword >

hcci  

Interval Estimation of Linear Models with Heteroskedasticity
View on CRAN: Click here


Download and install hcci package within the R console
Install from CRAN:
install.packages("hcci")

Install from Github:
library("remotes")
install_github("cran/hcci")

Install by package version:
library("remotes")
install_version("hcci", "1.1.0")



Attach the package and use:
library("hcci")
Maintained by
Pedro Rafael Diniz Marinho
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2014-02-22
Latest Update: 2014-02-22
Description:
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 . 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.
How to cite:
Pedro Rafael Diniz Marinho (2014). hcci: Interval Estimation of Linear Models with Heteroskedasticity. R package version 1.1.0, https://cran.r-project.org/web/packages/hcci. Accessed 06 Jan. 2025.
Previous versions and publish date:
1.0.0 (2014-02-22 16:44)
Other packages that cited hcci R package
View hcci citation profile
Other R packages that hcci depends, imports, suggests or enhances
Complete documentation for hcci
Functions, R codes and Examples using the hcci R package
Some associated functions: HC . Pboot . Tboot . hcci-package . schools . 
Some associated R codes: HC.R . Pboot.R . QT.R . Tboot.R .  Full hcci package functions and examples
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

lmds  
Landmark Multi-Dimensional Scaling
A fast dimensionality reduction method scaleable to large numbers of samples. Landmark Multi-Dime ...
Download / Learn more Package Citations See dependency  
RsqMed  
Total Mediation Effect Size Measure for High-Dimensional Mediators
An implementation of calculating the R-squared measure as a total mediation effect size measure and ...
Download / Learn more Package Citations See dependency  
TBFmultinomial  
TBF Methodology Extension for Multinomial Outcomes
Extends the test-based Bayes factor (TBF) methodology to multinomial regression models and discrete ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
NetSwan  
Network Strengths and Weaknesses Analysis
A set of functions for studying network robustness, resilience and vulnerability. ...
Download / Learn more Package Citations See dependency  
ROI.plugin.deoptim  
'DEoptim' and 'DEoptimR' Plugin for the 'R' Optimization Interface
Enhances the R Optimization Infrastructure ('ROI') package with the 'DEoptim' and 'DEoptimR' packag ...
Download / Learn more Package Citations See dependency  

23,440

R Packages

202,297

Dependencies

63,567

Author Associations

23,434

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA