Trailing-Edge
-
PDP-10 Archives
-
decus_20tap5_198111
-
decus/20-0149/reduce.pri
There are 2 other files named reduce.pri in the archive. Click here to see a list.
"MODEL" Y = A3 * X3 + A2 * X2 + A1 * X1;
"INPUT" 5 * [Y, X1, X2, X3];
"OPTIONS" 1, 2, 5, 8;
Transformed data matrix
=======================
obs.no. A3 A2 A1 dep.var.
1 4.000 1.000 2.000 8.000
2 1.000 2.000 -1.000 10.000
3 4.000 -3.000 1.000 9.000
4 2.000 1.000 2.000 6.000
5 6.000 4.000 1.000 12.000
Control information
===================
transformed variable
denoted by parameter mean standard deviation minimum maximum
A3 3.400000 1.949359 1.000000 6.000000
A2 1.000000 2.549510 -3.000000 4.000000
A1 1.000000 1.224745 -1.000000 2.000000
dep.var. 9.000000 2.236068 6.000000 12.000000
Number of observations : 5
There is no constant independent variable in the transformed (sub)model (message)
Correlation matrix of the variables
===================================
A3 A2 A1 dep.var.
A3 1.000000
A2 0.150908 1.000000
A1 0.418854 -0.160128 1.000000
dep.var. 0.516185 0.438529 -0.547723 1.000000
Multiple correlation coefficient 0.936662 (adjusted 0.832670)
================================
Proportion of variation explained 0.877336 (adjusted 0.693339)
=================================
Standard deviation of the error term 5.105507
====================================
Regression parameters
=====================
right tail
parameter estimate standard deviation F - ratio probability
A3 2.5446171560 0.9982125895 6.498286 0.125553
A2 0.2665515256 1.0423373169 0.065395 0.822061
A1 -1.3851468048 2.3646149361 0.343140 0.617320
Correlation matrix of the estimates
===================================
A3 A2 A1
A3 1.000000
A2 -0.452873 1.000000
A1 -0.751471 0.244757 1.000000
Analysis of variance
====================
source of right tail
variation df sum of squares mean square F - ratio probability
---------------------------------------------------------------------------------------------------------------
total 5 425.000000
---------------------------------------------------------------------------------------------------------------
regression 3 372.867588 124.289196 4.768212 0.178233
residual 2 52.132412 26.066206
---------------------------------------------------------------------------------------------------------------
regression null hypothesis : A3 = A2 = A1 = 0
Control information - submodel 1
===================
transformed variable
denoted by parameter mean standard deviation minimum maximum
A1 omitted
A3 3.400000 1.949359 1.000000 6.000000
A2 1.000000 2.549510 -3.000000 4.000000
dep.var. 9.000000 2.236068 6.000000 12.000000
Number of observations : 5
There is no constant independent variable in the transformed (sub)model (message)
Multiple correlation coefficient 0.925359 (adjusted 0.872057)
================================
Proportion of variation explained 0.856290 (adjusted 0.760483)
=================================
Standard deviation of the error term 4.512086
====================================
Regression parameters
=====================
right tail
parameter estimate standard deviation F - ratio probability
A3 2.1052066559 0.5820385900 13.082354 0.036325
A2 0.4159957059 0.8931663715 0.216927 0.673122
Analysis of variance
====================
source of right tail
variation df sum of squares mean square F - ratio probability
---------------------------------------------------------------------------------------------------------------
total 5 425.000000
---------------------------------------------------------------------------------------------------------------
regression 2 363.923242 181.961621 8.937686 0.054479
residual 3 61.076758 20.358919
---------------------------------------------------------------------------------------------------------------
reduction 1 8.944346 8.944346 0.343140 0.617320
---------------------------------------------------------------------------------------------------------------
regression null hypothesis : A3 = A2 = 0 (in the reduced model)
reduction null hypothesis : A1 = 0 (in the original model)
Control information - submodel 2
===================
transformed variable
denoted by parameter mean standard deviation minimum maximum
A2 omitted
A1 omitted
A3 3.400000 1.949359 1.000000 6.000000
dep.var. 9.000000 2.236068 6.000000 12.000000
Number of observations : 5
There is no constant independent variable in the transformed (sub)model (message)
Multiple correlation coefficient 0.919727 (adjusted 0.898539)
================================
Proportion of variation explained 0.845898 (adjusted 0.807373)
=================================
Standard deviation of the error term 4.046392
====================================
Regression parameters
=====================
right tail
parameter estimate standard deviation F - ratio probability
A3 2.2191780822 0.4735943538 21.956913 0.009407
Analysis of variance
====================
source of right tail
variation df sum of squares mean square F - ratio probability
---------------------------------------------------------------------------------------------------------------
total 5 425.000000
---------------------------------------------------------------------------------------------------------------
regression 1 359.506849 359.506849 21.956913 0.009407
residual 4 65.493151 16.373288
---------------------------------------------------------------------------------------------------------------
reduction 2 13.360738 6.680369 0.256285 0.795998
---------------------------------------------------------------------------------------------------------------
regression null hypothesis : A3 = 0 (in the reduced model)
reduction null hypothesis : A2 = A1 = 0 (in the original model)
End of job : 1
"MODEL" Y - 4 * X1 = B2 * (X1 + X2) + B3 * X3;
"INPUT" 5 * [Y, X1, X2, X3];
"OPTIONS" 1, 2, 9;
Transformed data matrix
=======================
obs.no. B2 B3 dep.var.
1 3.000 4.000 0.000
2 1.000 1.000 14.000
3 -2.000 4.000 5.000
4 3.000 2.000 -2.000
5 5.000 6.000 8.000
Control information
===================
transformed variable
denoted by parameter mean standard deviation minimum maximum
B2 2.000000 2.645751 -2.000000 5.000000
B3 3.400000 1.949359 1.000000 6.000000
dep.var. 5.000000 6.403124 -2.000000 14.000000
Number of observations : 5
There is no constant independent variable in the transformed (sub)model (message)
Correlation matrix of the variables
===================================
B2 B3 dep.var.
B2 1.000000
B3 0.339310 1.000000
dep.var. -0.177084 -0.140202 1.000000
Proportion of variation explained 0.293057 (adjusted -0.178239)
=================================
Standard deviation of the error term 8.252406
====================================
Regression parameters
=====================
right tail
parameter estimate standard deviation F - ratio probability
B2 -0.2325836533 1.6513864104 0.019836 0.896920
B3 1.1991223258 1.3390842284 0.801883 0.436516
Correlation matrix of the estimates
===================================
B2 B3
B2 1.000000
B3 -0.692631 1.000000
Analysis of variance
====================
source of right tail
variation df sum of squares mean square F - ratio probability
---------------------------------------------------------------------------------------------------------------
total 5 289.000000
---------------------------------------------------------------------------------------------------------------
regression 2 84.693363 42.346681 0.621811 0.594397
residual 3 204.306637 68.102212
---------------------------------------------------------------------------------------------------------------
reduction 1 152.174225 152.174225 5.837989 0.136963
---------------------------------------------------------------------------------------------------------------
regression null hypothesis : B2 = B3 = 0
End of job : 2