# gfilinreg: Fiducial sampler for linear regression model In gfilinreg: Generalized Fiducial Inference for Low-Dimensional Robust Linear Regression

## Description

Weighted samples of the fiducial distribution of the parameters of a linear regression model with normal, Student, Cauchy, or logistic error terms.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10``` ```gfilinreg( formula, data = NULL, distr = "student", df = Inf, L = 30L, Kmax = 50L, nthreads = parallel::detectCores(), stopifbig = TRUE ) ```

## Arguments

 `formula` two-sided formula defining the model `data` dataframe containing the data `distr` the distribution of the error terms, `"normal"`, `"student"`, `"cauchy"`, or `"logistic"` `df` degrees of freedom of the Student distribution if `distr = "student"` `L` number of subdivisions of each axis of the hypercube `(0,1)^(p+1)` `Kmax` maximal number of combinations of indices to use `nthreads` number of threads for parallel computations `stopifbig` logical, whether to stop if the algorithm requires huge matrices

## Value

A `gfilinreg` object, list with the fiducial samples and the weights.

## References

Jan Hannig, Randy C.S. Lai, Thomas C.M. Lee. Computational issues of generalized fiducial inference. Computational Statistics and Data Analysis 71 (2014), 849–858. <doi:10.1016/j.csda.2013.03.003>

## Examples

 ```1 2 3 4 5``` ```set.seed(666L) x <- c(1, 2, 3, 4) y <- x + 3 * rcauchy(4L) gfi <- gfilinreg(y ~ x, distr = "cauchy", L = 30L, nthreads = 2L) gfiSummary(gfi) ```

gfilinreg documentation built on March 17, 2021, 1:06 a.m.