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2004 Jan 20
1
evaluation of discriminant functions+multivariate homosce dasticity
...(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 + 1) * (g - 1)) / 2) ## Degrees...