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sum1
2004 Jan 20
1
evaluation of discriminant functions+multivariate homosce dasticity
..., dim=dim(covList[[1]]))
for (k in 1:g)
suma = suma + (n[k] - 1) * covList[[k]]
Sp = suma / deno ## Pooled covariance matrix.
Falta=0
for (k in 1:g)
Falta = Falta + ((n[k] - 1) * log(det(covList[[k]])))
MB = (sum(n) - g) * log(det(Sp)) - Falta ## Box's M statistic.
suma1 = sum(1 / (n[1:g] - 1))
suma2 = sum(1 / ((n[1:g] - 1)^2))
C = (((2 * p^2) + (3 * p) - 1) / (6 * (p + 1) * (g - 1))) *
(suma1 - (1 / deno)) ## Computing of correction factor.
if (bandera == 1) {
X2 = MB * (1 - C) ## Chi-square approximation.
v = as.integer((p * (p +...