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decuslib20-05
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decus/20-0149/mulexa.hlp
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Multiple Linear Regression Analysis
EXAMPLES
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* Example 1 originates from: *
* DE JONGE [4], pp. 472 & 479. *
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"Model" y = c * Log (x) + a + b * x;
"Input" 5 * ([x], 10 * [y]);
"Options" Transformed data matrix, Correlation matrix,
Residual analysis, Process submodels (1, 2);
"Data" 25 0.67 0.70 0.75 0.76 0.78 0.80 0.83 0.84 0.88 0.89
50 0.88 0.92 0.93 0.96 0.98 1.00 1.01 1.03 1.06 1.07
80 0.96 0.98 0.99 1.03 1.05 1.06 1.08 1.11 1.15 1.17
130 1.07 1.09 1.11 1.13 1.14 1.14 1.19 1.22 1.25 1.29
180 1.10 1.13 1.17 1.19 1.20 1.21 1.23 1.25 1.28 1.33
"Run"
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* Example 2 originates from: *
* SEARLE [11], pp. 121-123 *
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"Input" 5 * [y, x1, x2, x3];
"Data" 8 2 1 4
10 -1 2 1
9 1 -3 4
6 2 1 2
12 1 4 6
"Model 1" y = a3 * x3 + a2 * x2 + a1 * x1;
"Options" Save original model, Process submodels (1);
"Run"
"Model 2" y - 4 * x1 = b2 * (x1 + x2) + b3 * x3; (eqn. 118, p. 121)
"Options" Test reduced model, Transformed data matrix;
"Run"
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* Example 3 originates from: *
* AFIFI & AZEN [1], pp. 88 & 93-100. *
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"Model" y = alfa0 + alfa1 * x;
"Input" 5 * ([x], n, n * [y]);
"Option" Transformed data matrix, Print input data;
"Data" 1 4 1.1 0.7 1.8 0.4
3 5 3.0 1.4 4.9 4.4 4.5
5 3 7.3 8.2 6.2
10 4 12.0 13.1 12.6 13.2
15 4 18.7 19.7 17.4 17.1
"Run"
*** Marten van Gelderen; Mathematisch Centrum ***
"Exit"