weighted.rank {cNORM} | R Documentation

## Weighted rank estimation

### Description

Conducts weighted ranking on the basis of either the weighted Harrell-Davis quantile estimator or an adaption of the type 7 quantile estimator of the generic quantile function in the base package. Please provide a vector with raw values and an additional vector with the weight of each observation. In case the weight vector is NULL, a normal ranking is done. The vectors may not include NAs and the weights should be positive non-zero values.

### Usage

    weighted.rank(x, weights = NULL, n = 1000, type = "Type7")

### Arguments

`x` | A numerical vector
`weights` | A numerical vector with weights; should have the same length as x
`n` | Granularity for approximation
`type` | Type of estimator, can either be "Harrell-Davis" using a beta function to approximate the weighted percentiles (Harrell & Davis, 1982) or "Type7" (default; Hyndman & Fan, 1996), an adaption of the generic quantile function in R, including weighting. All code based on the work of Akinshin (2020).

### Value

the weighted ranks

### References

1. Harrell, F.E. & Davis, C.E. (1982). A new distribution-free quantile estimator. Biometrika, 69(3), 635-640.

2. Hyndman, R. J. & Fan, Y. 1996. Sample quantiles in statistical packages, American Statistician 50, 361–365.

3. Akinshin, A. (2020). Weighted quantile estimators. https://aakinshin.net/posts/weighted-quantiles/

[Package cNORM version 2.0.3 Index]