dCenteredPearson: compute pearson correlation distance between two vectors
In donelsonsmith/umap_R: Uniform Manifold Approximation and Projection
Description
Usage
Arguments
Details
Value
Description
Pearson distance is (1-r^2)
Usage
1
dCenteredPearson(x, y)
Arguments
x
numeric vector
y
numeric vector
Details
Important: this function assumes that data has been centered
i.e. that mean(x) = mean(y) = 0
Value
pearson distance between x and y
donelsonsmith/umap_R documentation built on Nov. 4, 2019, 10:58 a.m.
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Description Usage Arguments Details Value
Description
Pearson distance is (1-r^2)
Usage
1 | dCenteredPearson(x, y)
|
Arguments
x |
numeric vector |
y |
numeric vector |
Details
Important: this function assumes that data has been centered i.e. that mean(x) = mean(y) = 0
Value
pearson distance between x and y
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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