scaleFreeFitIndex: Calculation of fitting statistics for evaluating scale free...
In WGCNA: Weighted Correlation Network Analysis
scaleFreeFitIndex R Documentation
Calculation of fitting statistics for evaluating scale free topology fit.
Description
The function scaleFreeFitIndex calculates several indices (fitting statistics) for evaluating scale free
topology fit. The input is a vector (of connectivities) k. Next k is discretized into nBreaks number of
equal-width bins. Let's denote the resulting vector dk. The relative frequency for each bin is denoted
p.dk.
Usage
scaleFreeFitIndex(k, nBreaks = 10, removeFirst = FALSE)
Arguments
k
numeric vector whose components contain non-negative values
nBreaks
positive integer. This determines the number of equal width bins.
removeFirst
logical. If TRUE then the first bin will be removed.
Value
Data frame with columns
Rsquared.SFT
the model fitting index (R.squared) from the following model lm(log.p.dk ~ log.dk)
slope.SFT
the slope estimate from model lm(log(p(k))~log(k))
truncatedExponentialAdjRsquared
the adjusted R.squared measure from the truncated exponential model
given by lm2 = lm(log.p.dk ~ log.dk + dk).
Author(s)
Steve Horvath
WGCNA documentation built on Sept. 18, 2024, 5:08 p.m.
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| scaleFreeFitIndex | R Documentation |
Calculation of fitting statistics for evaluating scale free topology fit.
Description
The function scaleFreeFitIndex calculates several indices (fitting statistics) for evaluating scale free topology fit. The input is a vector (of connectivities) k. Next k is discretized into nBreaks number of equal-width bins. Let's denote the resulting vector dk. The relative frequency for each bin is denoted p.dk.
Usage
scaleFreeFitIndex(k, nBreaks = 10, removeFirst = FALSE)
Arguments
k |
numeric vector whose components contain non-negative values |
nBreaks |
positive integer. This determines the number of equal width bins. |
removeFirst |
logical. If TRUE then the first bin will be removed. |
Value
Data frame with columns
Rsquared.SFT |
the model fitting index (R.squared) from the following model lm(log.p.dk ~ log.dk) |
slope.SFT |
the slope estimate from model lm(log(p(k))~log(k)) |
truncatedExponentialAdjRsquared |
the adjusted R.squared measure from the truncated exponential model given by lm2 = lm(log.p.dk ~ log.dk + dk). |
Author(s)
Steve Horvath
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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