# qq.burrX: Quantile versus quantile (QQ) plot for the BurrX distribution In reliaR: Package for some probability distributions.

## Description

The function `qq.burrX()` produces a QQ plot for the BurrX based on their MLE or any other estimate. Also, a line going through the first and the third quartile can be sketched.

## Usage

 `1` ```qq.burrX(x, alpha.est, lambda.est, main = " ", line.qt = FALSE, ...) ```

## Arguments

 `x` vector of observations `alpha.est` estimate of the parameter alpha `lambda.est` estimate of the parameter lambda `main` the title for the plot `line.qt` logical; if TRUE, a line going by the first and third quartile is sketched. `...` additional arguments to be passed to the underlying plot function.

## Value

The function `qq.burrX()` carries out a QQ plot for the BurrX.

## References

Kundu, D., and Raqab, M.Z. (2005). Generalized Rayleigh Distribution: Different Methods of Estimation, Computational Statistics and Data Analysis, 49, 187-200.

Surles, J.G., and Padgett, W.J. (2005). Some properties of a scaled Burr type X distribution, Journal of Statistical Planning and Inference, 128, 271-280.

Raqab, M.Z., and Kundu, D. (2006). Burr Type X distribution: revisited, Journal of Probability and Statistical Sciences, 4(2), 179-193.

`pp.burrX` for `PP` plot and `ks.burrX` function
 ```1 2 3 4 5 6 7``` ```## Load data sets data(bearings) ## Maximum Likelihood(ML) Estimates of alpha & lambda for the data(bearings) ## Estimates of alpha & lambda using 'maxLik' package ## alpha.est = 1.1989515, lambda.est = 0.0130847 qq.burrX(bearings, 1.1989515, 0.0130847, main = " ", line.qt = FALSE) ```