Many high-level programming languages allow their users to afford the luxury of extending an existing matrix or vector. The question is, how luxury it can be?
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The data.table package supports a powerful syntax to select rows and columns.
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This note explores the use of data.table package to calculate pairwise correlation between columns, with iris data set as example.
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Example 1 - Fair coin
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The package MASS provides a function, fitdistr to fit an observation over discrete distribution using Maximum likelihood.
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String concatenation can be done with paste, paste0, sprintf, or .Internal(sprintf).
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The definition of a(), b(), and sw() below achieve the same effect with different implementations: if else, nested if, and switch
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.Internal(sample()) requires explicitly 4 arguments in order: n, size, replacement, probabilities
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This note compares the performance of 2 methods for calculating Pearson correlation:
R stats::cor function
WGCNA::cor function (or corFast)
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a = matrix(rnorm(10000^2),ncol=10000)
Ns = c(1000, 5000,10000)
times = data.frame(list(N=Ns))
t1 = sapply(Ns, function(n) {system.time(image(a[1:n,1:n],useRaster=T))['elapsed']})
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-nearest neighbor Entropy estimator
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See Lecture by [@gutierrez_kernel].
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This article explores three types of transformations
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An example where recursive indexing failed error is not clear
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Data
This is the value of matrix a
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