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Welcome! fixedCV is an R package that provides robust
statistical inference for time series and other dependent data.
When working with correlated data (like time series), standard statistical methods can give misleading results. This package provides tools for:
The package implements fixed-b critical values and multiple kernel-based estimators to ensure your statistical inferences are valid even when observations are correlated.
You can install fixedCV directly from GitHub using the
devtools package:
# Install devtools if you haven't already
install.packages("devtools")
# Install fixedCV from GitHub
devtools::install_github("rpkgarcia/fixedCV")Alternatively, you can use the remotes package:
# Install remotes if you haven't already
install.packages("remotes")
# Install fixedCV from GitHub
remotes::install_github("rpkgarcia/fixedCV")Once installed, load the package and you’re ready to go:
library(fixedCV)
# Fit a linear model
model <- lm(y ~ x, data = your_data)
# Get robust inference that accounts for autocorrelation
robust_results <- robust_lm(model)The robust_lm() function automatically selects
appropriate bandwidth parameters and provides robust standard errors,
t-statistics, and p-values that are valid under general dependence
structures.
For detailed documentation and examples:
# View package documentation
help(package = "fixedCV")
# See examples for the main function
?robust_lm
# Access the package vignette
vignette("fixedCV-vignette")If you encounter any problems or have questions, please open an issue on the GitHub repository.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.