>
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mean := "Nag_MeanInclude":
n := 20:
m := 6:
x := Matrix([[0, 1125, 232, 7160, 85.90000000000001, 8905], [7, 920, 268, 8804, 86.5, 7388], [15, 835, 271, 8108, 85.2, 5348], [22, 1000, 237, 6370, 83.8, 8056], [29, 1150, 192, 6441, 82.09999999999999, 6960], [37, 990, 202, 5154, 79.2, 5690], [44, 840, 184, 5896, 81.2, 6932], [58, 650, 200, 5336, 80.59999999999999, 5400], [65, 640, 180, 5041, 78.40000000000001, 3177], [72, 583, 165, 5012, 79.3, 4461], [80, 570, 151, 4825, 78.7, 3901], [86, 570, 171, 4391, 78, 5002], [93, 510, 243, 4320, 72.3, 4665], [100, 555, 147, 3709, 74.90000000000001, 4642], [107, 460, 286, 3969, 74.40000000000001, 4840], [122, 275, 198, 3558, 72.5, 4479], [129, 510, 196, 4361, 57.7, 4200], [151, 165, 210, 3301, 71.8, 3410], [171, 244, 327, 2964, 72.5, 3360], [220, 79, 334, 2777, 71.90000000000001, 2599]], datatype=float[8]):
var_names := Vector(["DAY", "BOD", "TKN", "TS", "TVS", "COD"], datatype=string):
sx := Vector([0, 1, 1, 1, 1, 1], datatype=integer[kernelopts('wordsize')/8]):
free_vars := 1:
for j from 1 to m do
if sx[j] = 1 then
free_vars := free_vars*2:
end if:
end do:
y := Vector([1.5563, 0.8976, 0.7482, 0.716, 0.301, 0.3617, 0.1139, 0.1139, -0.2218, -0.1549, 0, 0, -0.0969, -0.2218, -0.3979, -0.1549, -0.2218, -0.3979, -0.5229, -0.0458], datatype=float[8]):
wt := Vector([], datatype=float[8]):
model := Vector(free_vars*m, datatype=string, fill=""):
rss := Vector(free_vars, datatype=float[8]):
nterms := Vector(free_vars, datatype=integer[kernelopts('wordsize')/8]):
mrank := Vector(free_vars, datatype=integer[kernelopts('wordsize')/8]):
NAG:-g02eac(mean, x, var_names, sx, y, nmod, model, rss, nterms, mrank, 'n' = n, 'm' = m, 'wt' = wt):
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