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View Code? Open in Web Editor NEWStatistical dimension reduction in Go
Statistical dimension reduction in Go
In sir.go, line 391.
// q3 is a symmetric matrix but not of type Symmetric, would
// be better to use EigenSym here but hard to convert.
var ei mat64.Eigen
ok := ei.Factorize(q3, true)
The Factorize method of mat64.Eigen has changed and now requires three arguments.
See https://godoc.org/github.com/gonum/matrix/mat64#Eigen
moment_stream assumes that the stratifying variable can be used as an index for the within-class means and covariances.
y := cm.Data.GetPos(cm.ypos).([]float64)
var mn [][]float64
var ny []int
// Calculate the sums and sample sizes
for j, xp := range cm.xpos {
x := cm.Data.GetPos(xp).([]float64)
fmt.Printf("current x: %v\n", x)
for i := 0; i < len(y); i++ {
yi := int(y[i])
mn = growf(mn, yi, p)
mn[yi][j] += x[i]
if j == 0 {
ny = growi(ny, yi)
ny[yi]++
}
}
}
It could be useful to allow the class labels / stratifying variable to be more general, like {1, 2, 3} or {"a", "b", "c"}
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