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Trailing-Edge - PDP-10 Archives - decus_20tap5_198111 - decus/20-0149/mulreg.inp
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***********************************
*  Example  1  originates from:   *
*  reference [4],  page 472, 479  *
***********************************
"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"

***********************************
*  Example  2  originates from:   *
*  reference [9],  page 475, ff.  *
***********************************
"Model"   available  =  beta0  +  beta1 * inorganic  +  beta2 * organic;
"Input"   18 * [soil sample, available, inorganic, organic];
"Options" Transformed data matrix, Correlation matrix, Residual analysis;

"Data"	 1    64     0.4    53
	 2    60     0.4    23
	 3    71     3.1    19
	 4    61     0.6    34
	 5    54     4.7    24
	 6    77     1.7    65
	 7    81     9.4    44
	 8    93    10.1    31
	 9    93    11.6    29
	10    51    12.6    58
	11    76    10.9    37
	12    96    23.1    46
	13    77    23.1    50
	14    93    21.6    44
	15    95    23.1    56
	16    54     1.9    36
	17   168    26.8    58
	18    99    29.9    51
"Run"

***********************************
*  Example  3  originates from:   *
*  reference [3],  page 228, 339  *
***********************************
"Model"  Ln (Mean surface volume)  =  Lnalpha  +  beta * Ln (Feed rate)
	 +  gamma * Ln (Wheel velocity)  +  delta * Ln (Feed viscosity);
"Input"  35 * [Run number, Feed rate, Wheel velocity,
	       Feed viscosity, Mean surface volume];
"Options" Transformed data matrix, Residual analysis, Process submodels (1);

"Data"      1    0.0174     5300    0.108    25.4
            2    0.0630     5400    0.107    31.6
            3    0.0622     8300    0.107    25.7
            4    0.0118    10800    0.106    17.4
            5    0.1040     4600    0.102    38.2
            6    0.0118    11300    0.105    18.2
            7    0.0122     5800    0.105    26.5
            8    0.0122     8000    0.100    19.3
            9    0.0408    10000    0.106    22.3
           10    0.0408     6600    0.105    26.4
           11    0.0630     8700    0.104    25.8
           12    0.0408     4400    0.104    32.2
           13    0.0415     7600    0.106    25.1
           14    0.1010     4800    0.106    39.7
           15    0.0170     3100    0.106    35.6
           16    0.0412     9300    0.105    23.5
           17    0.0170     7700    0.098    22.1
           18    0.0170     5300    0.099    26.5
           19    0.1010     5700    0.098    39.7
           20    0.0622     6200    0.102    31.5
           21    0.0622     7700    0.102    26.9
           22    0.0170    10200    0.100    18.1
           23    0.0118     4800    0.102    28.4
           24    0.0408     6600    0.102    27.3
           25    0.0622     8300    0.102    25.8
           26    0.0170     7700    0.102    23.1
           27    0.0408     9000    0.613    23.4
           28    0.0170    10100    0.619    18.1
           29    0.0408     5300    0.671    30.9
           30    0.0622     8000    0.624    25.7
           31    0.1010     7300    0.613    29.0
           32    0.0118     6400    0.328    22.0
           33    0.0170     8000    0.341    18.8
           34    0.0118     9700    1.845    17.9
           35    0.0408     6300    1.940    28.4
"Run"

**************************************
*  Example  4  originates from:      *
*  reference [1],  page 88, 93, ff.  *
**************************************
"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"