# bicovWeights: Weights used in biweight midcovariance In WGCNA: Weighted Correlation Network Analysis

 bicovWeights R Documentation

## Weights used in biweight midcovariance

### Description

Calculation of weights and the intermediate weight factors used in the calculation of biweight midcovariance and midcorrelation. The weights are designed such that outliers get smaller weights; the weights become zero for data points more than 9 median absolute deviations from the median.

### Usage

```bicovWeights(
x,
pearsonFallback = TRUE,
maxPOutliers = 1,
outlierReferenceWeight = 0.5625,
defaultWeight = 0)

bicovWeightFactors(
x,
pearsonFallback = TRUE,
maxPOutliers = 1,
outlierReferenceWeight = 0.5625,
defaultFactor = NA)

bicovWeightsFromFactors(
u,
defaultWeight = 0)
```

### Arguments

 `x` A vector or a two-dimensional array (matrix or data frame). If two-dimensional, the weights will be calculated separately on each column. `u` A vector or matrix of weight factors, usually calculated by `bicovWeightFactors`. `pearsonFallback` Logical: if the median absolute deviation is zero, should standard deviation be substituted? `maxPOutliers` Optional specification of the maximum proportion of outliers, i.e., data with weights equal to `outlierReferenceWeight` below. `outlierReferenceWeight` A number between 0 and 1 specifying what is to be considered an outlier when calculating the proportion of outliers. `defaultWeight` Value used for weights that correspond to a finite `x` but the weights themselves would not be finite, for example, when a column in `x` is constant. `defaultFactor` Value used for factors that correspond to a finite `x` but the weights themselves would not be finite, for example, when a column in `x` is constant.

### Details

These functions are based on Equations (1) and (3) in Langfelder and Horvath (2012). The weight factor is denoted `u` in that article.

Langfelder and Horvath (2012) also describe the Pearson fallback and maximum proportion of outliers in detail. For a full discussion of the biweight midcovariance and midcorrelation, see Wilcox (2005).

### Value

A vector or matrix of the same dimensions as the input `x` giving the bisquare weights (`bicovWeights` and `bicovWeightsFromFactors`) or the bisquare factors (`bicovWeightFactors`).

Peter Langfelder

### References

Langfelder P, Horvath S (2012) Fast R Functions for Robust Correlations and Hierarchical Clustering Journal of Statistical Software 46(11) 1-17 PMID: 23050260 PMCID: PMC3465711 Wilcox RR (2005). Introduction to Robust Estimation and Hypothesis Testing. 2nd edition. Academic Press, Section 9.3.8, page 399 as well as Section 3.12.1, page 83.

`bicor`

### Examples

```x = rnorm(100);
x[1] = 10;
plot(x, bicovWeights(x));
```

WGCNA documentation built on Jan. 22, 2023, 1:34 a.m.