Genstat 64-bit Release 18.

1 ( PC/Windows 8) 19 April 2017 20:05:19

Copyright 2015, VSN International Ltd.
Registered to: Uni of Braw

________________________________________

Genstat Eighteenth Edition

Genstat Procedure Library Release PL26.1
________________________________________

1 SET [WORKINGDIRECTORY='C:/Users/lugas/Documents']
2 "Data taken from file: 'D:/Penelitian/Olahan/Titik Kadar Air.xls'"
3 DELETE [REDEFINE=yes] _stitle_: TEXT _stitle_
4 READ [PRINT=*; SETNVALUES=yes] _stitle_
8 PRINT [IPRINT=*] _stitle_; JUST=left

Data imported from Excel file: D:\Penelitian\Olahan\Titik Kadar Air.xls

on: 19-Apr-2017 20:05:33
taken from sheet "KA", cells A2:I31

9 DELETE [REDEFINE=yes] Lokasi,FID,Titik,%KA,NDWI,NDWI2,NDWI3,NDVI,NDSI

10 UNITS [NVALUES=*]
11 TEXT [NVALUES=30] Lokasi
12 READ Lokasi

Identifier Minimum Mean Maximum Values Missing

Lokasi 30 0

16 VARIATE [NVALUES=30] FID

17 READ FID

Identifier Minimum Mean Maximum Values Missing

FID 0.0000 7.833 19.00 30 0

19 VARIATE [NVALUES=30] Titik

20 READ Titik

Identifier Minimum Mean Maximum Values Missing

Titik 1.000 15.50 30.00 30 0

23 VARIATE [NVALUES=30] %KA

24 READ %KA

Identifier Minimum Mean Maximum Values Missing

%KA 14.90 21.22 36.48 30 0

31 VARIATE [NVALUES=30] NDWI

32 READ NDWI

Identifier Minimum Mean Maximum Values Missing

NDWI -0.3622 -0.2625 -0.1417 30 0

37 VARIATE [NVALUES=30] NDWI2

38 READ NDWI2

Identifier Minimum Mean Maximum Values Missing

NDWI2 -0.3240 0.3266 0.5664 30 0
 43 VARIATE [NVALUES=30] NDWI3
44 READ NDWI3

Identifier Minimum Mean Maximum Values Missing

NDWI3 -0.1890 -0.04782 0.09804 30 0

49 VARIATE [NVALUES=30] NDVI

50 READ NDVI

Identifier Minimum Mean Maximum Values Missing

NDVI -0.2358 0.1084 0.3754 30 0

55 VARIATE [NVALUES=30] NDSI

56 READ NDSI

Identifier Minimum Mean Maximum Values Missing

NDSI -0.2590 -0.1002 0.2255 30 0

61
62 %PostMessage 1129; 0; 100001 "Sheet Update Completed"
63 FCORRELATION [PRINT=correlations,test; METHOD=twosided]
%KA,NDSI,NDVI,NDWI,NDWI2,NDWI3

Correlations

%KA 1 -
NDSI 2 -0.6721 -
NDVI 3 0.5561 -0.9458 -
NDWI 4 0.0717 0.2930 -0.5658 -
NDWI2 5 -0.0214 0.2383 -0.4058 0.5699 -
NDWI3 6 0.1333 0.1948 -0.4879 0.9727 0.6018 -
1 2 3 4 5 6

Number of observations: 30

Two-sided test of correlations different from zero

%KA 1 -
NDSI 2 <0.001 -
NDVI 3 0.0014 <0.001 -
NDWI 4 0.7067 0.1161 0.0011 -
NDWI2 5 0.9106 0.2048 0.0261 0.0010 -
NDWI3 6 0.4825 0.3022 0.0062 <0.001 <0.001
1 2 3 4 5

NDWI3 6 -
6
 64 "Multiple Linear Regression"
65 MODEL %KA
66 TERMS [FACT=9] NDSI,NDVI,NDWI3
67 FIT [PRINT=model,summary,estimates; CONSTANT=estimate; FPROB=yes;
TPROB=yes; FACT=9]\
68 NDSI,NDVI,NDWI3
Regression analysis
Response variate: %KA
Fitted terms: Constant, NDSI, NDVI, NDWI3

Summary of analysis
Source d.f. s.s. m.s. v.r. F pr.
Regression 3 273.6 91.205 9.61 <.001
Residual 26 246.8 9.491
Total 29 520.4 17.944

Percentage variance accounted for 47.1

Standard error of observations is estimated to be 3.08.

Message: the following units have large standardized residuals.

Unit Response Residual
16 36.48 3.75
21 17.16 -2.63

Message: the following units have high leverage.

Unit Response Leverage
5 15.80 0.32

Estimates of parameters
Parameter estimate s.e. t(26) t pr.
Constant 20.67 1.67 12.41 <.001
NDSI -9.0 29.6 -0.30 0.764
NDVI 7.1 24.5 0.29 0.774
NDWI3 23.4 26.6 0.88 0.387

Message: the variance of some parameter estimates is seriously inflated, due to near
collinearity or aliasing between the following parameters, listed with their variance
inflation factors.
NDVI 103.73

69 PREDICT [PRINT=description,predictions,se,lsd;
COMBINATIONS=estimable; LSDLEVEL=5]
Predictions from regression model
These predictions are estimated mean values.

The predictions are based on fixed values of some variates:

Variate Fixed value Source of value
NDSI -0.1002 Mean of variate
NDVI 0.1084 Mean of variate
NDWI3 -0.04782 Mean of variate

The standard errors are appropriate for interpretation of the predictions as summaries of the data
rather than as forecasts of new observations.

Response variate: %KA

Prediction s.e.
21.22 0.5625

Least significant differences of predictions (5% level)

1 *
1

70 RCHECK [RMETHOD=deviance] residual; composite

71 UNITS [NVALUES=*]
72 DELETE [REDEFINE=yes] _rest_
73 READ [PRINT=*; SETNVALUES=y] _rest_
75 RESTRICT Lokasi,FID,Titik,%KA,NDWI,NDWI2,NDWI3,NDVI,NDSI; _rest_
76
77 %PostMessage 1129; 0; 100001 "Sheet Update Completed"
78 "Multiple Linear Regression"
79 MODEL %KA
80 TERMS [FACT=9] NDSI,NDVI,NDWI3
81 FIT [PRINT=model,summary,estimates; CONSTANT=estimate; FPROB=yes;
TPROB=yes; FACT=9]\
82 NDSI,NDVI,NDWI3
Regression analysis
Response variate: %KA
Fitted terms: Constant, NDSI, NDVI, NDWI3

Summary of analysis
Source d.f. s.s. m.s. v.r. F pr.
Regression 3 253.4 84.476 8.67 <.001
Residual 24 233.9 9.744
Total 27 487.3 18.048

Percentage variance accounted for 46.0

Standard error of observations is estimated to be 3.12.

Message: the following units have large standardized residuals.

Unit Response Residual
16 36.48 3.64
21 17.16 -2.67

Message: the following units have high leverage.

Unit Response Leverage
4 15.20 0.32

Estimates of parameters
Parameter estimate s.e. t(24) t pr.
Constant 20.31 1.95 10.40 <.001
NDSI -12.2 33.9 -0.36 0.722
NDVI 5.8 27.6 0.21 0.836
NDWI3 22.9 29.2 0.78 0.441

Message: the variance of some parameter estimates is seriously inflated, due to near
collinearity or aliasing between the following parameters, listed with their variance
inflation factors.
NDVI 110.19

83 PREDICT [PRINT=description,predictions,se,lsd;
COMBINATIONS=estimable; LSDLEVEL=5]
Predictions from regression model
These predictions are estimated mean values.

The predictions are based on fixed values of some variates:

Variate Fixed value Source of value
NDSI -0.1214 Mean of variate
NDVI 0.1315 Mean of variate
NDWI3 -0.04718 Mean of variate

The standard errors are appropriate for interpretation of the predictions as summaries of the data
rather than as forecasts of new observations.

Response variate: %KA

Prediction s.e.
21.47 0.5899

Least significant differences of predictions (5% level)

1 *
1

84 UNITS [NVALUES=*]
85 DELETE [REDEFINE=yes] _rest_
86 READ [PRINT=*; SETNVALUES=y] _rest_
88 RESTRICT Lokasi,FID,Titik,%KA,NDWI,NDWI2,NDWI3,NDVI,NDSI; _rest_
89
90 %PostMessage 1129; 0; 100001 "Sheet Update Completed"
91 "Multiple Linear Regression"
92 MODEL %KA
93 TERMS [FACT=9] NDSI,NDVI,NDWI3
94 FIT [PRINT=model,summary,estimates; CONSTANT=estimate; FPROB=yes;
TPROB=yes; FACT=9]\
95 NDSI,NDVI,NDWI3
Regression analysis
Response variate: %KA
Fitted terms: Constant, NDSI, NDVI, NDWI3

Summary of analysis
Source d.f. s.s. m.s. v.r. F pr.
Regression 3 216.5 72.15 7.21 0.001
Residual 23 230.1 10.00
Total 26 446.6 17.18

Percentage variance accounted for 41.8

Standard error of observations is estimated to be 3.16.

Message: the following units have large standardized residuals.

Unit Response Residual
16 36.48 3.55
21 17.16 -2.74

Message: the following units have high leverage.

Unit Response Leverage
3 17.30 0.35

Estimates of parameters
Parameter estimate s.e. t(23) t pr.
Constant 19.96 2.06 9.71 <.001
NDSI -17.0 35.2 -0.48 0.634
NDVI 2.9 28.3 0.10 0.919
NDWI3 21.8 29.6 0.74 0.469

Message: the variance of some parameter estimates is seriously inflated, due to near
collinearity or aliasing between the following parameters, listed with their variance
inflation factors.
NDVI 104.09

96 PREDICT [PRINT=description,predictions,se,lsd;
COMBINATIONS=estimable; LSDLEVEL=5]
Predictions from regression model
These predictions are estimated mean values.

The predictions are based on fixed values of some variates:

Variate Fixed value Source of value
NDSI -0.1342 Mean of variate
NDVI 0.1438 Mean of variate
NDWI3 -0.04438 Mean of variate

The standard errors are appropriate for interpretation of the predictions as summaries of the data
rather than as forecasts of new observations.

Response variate: %KA

Prediction s.e.
21.70 0.6087

Least significant differences of predictions (5% level)

1 *
1

97 UNITS [NVALUES=*]
98 DELETE [REDEFINE=yes] _rest_
99 READ [PRINT=*; SETNVALUES=y] _rest_
101 RESTRICT Lokasi,FID,Titik,%KA,NDWI,NDWI2,NDWI3,NDVI,NDSI; _rest_
102
103 %PostMessage 1129; 0; 100001 "Sheet Update Completed"
104 "Multiple Linear Regression"
105 MODEL %KA
106 TERMS [FACT=9] NDSI,NDVI,NDWI3
107 FIT [PRINT=model,summary,estimates; CONSTANT=estimate; FPROB=yes;
TPROB=yes; FACT=9]\
108 NDSI,NDVI,NDWI3
Regression analysis
Response variate: %KA
Fitted terms: Constant, NDSI, NDVI, NDWI3

Summary of analysis
Source d.f. s.s. m.s. v.r. F pr.
Regression 3 204.1 68.04 6.73 0.002
Residual 22 222.4 10.11
Total 25 426.5 17.06

Percentage variance accounted for 40.8

Standard error of observations is estimated to be 3.18.

Message: the following units have large standardized residuals.

Unit Response Residual
16 36.48 3.44
21 17.16 -2.89

Message: the following units have high leverage.

Unit Response Leverage
7 19.20 0.31

Estimates of parameters
Parameter estimate s.e. t(22) t pr.
Constant 18.98 2.35 8.07 <.001
NDSI -31.0 38.9 -0.80 0.433
NDVI -6.6 30.5 -0.22 0.830
NDWI3 14.0 31.1 0.45 0.656

Message: the variance of some parameter estimates is seriously inflated, due to near
collinearity or aliasing between the following parameters, listed with their variance
inflation factors.
NDVI 107.12

109 PREDICT [PRINT=description,predictions,se,lsd;

COMBINATIONS=estimable; LSDLEVEL=5]
Predictions from regression model
These predictions are estimated mean values.

The predictions are based on fixed values of some variates:

Variate Fixed value Source of value
NDSI -0.1466 Mean of variate
NDVI 0.1576 Mean of variate
NDWI3 -0.04418 Mean of variate

The standard errors are appropriate for interpretation of the predictions as summaries of the data
rather than as forecasts of new observations.

Response variate: %KA

Prediction s.e.
21.87 0.6235

Least significant differences of predictions (5% level)

1 *
1

110 UNITS [NVALUES=*]

111 DELETE [REDEFINE=yes] _rest_
112 READ [PRINT=*; SETNVALUES=y] _rest_
114 RESTRICT Lokasi,FID,Titik,%KA,NDWI,NDWI2,NDWI3,NDVI,NDSI; _rest_
115
116 %PostMessage 1129; 0; 100001 "Sheet Update Completed"
117 "Multiple Linear Regression"
118 MODEL %KA
119 TERMS [FACT=9] NDSI,NDVI,NDWI3
120 FIT [PRINT=model,summary,estimates; CONSTANT=estimate; FPROB=yes;
TPROB=yes; FACT=9]\
121 NDSI,NDVI,NDWI3
Regression analysis
Response variate: %KA
Fitted terms: Constant, NDSI, NDVI, NDWI3

Summary of analysis
Source d.f. s.s. m.s. v.r. F pr.
Regression 3 196.9 65.64 6.20 0.003
Residual 21 222.2 10.58
Total 24 419.1 17.46

Percentage variance accounted for 39.4

Standard error of observations is estimated to be 3.25.

Message: the following units have large standardized residuals.

Unit Response Residual
16 36.48 3.39
21 17.16 -2.84

Estimates of parameters
Parameter estimate s.e. t(21) t pr.
Constant 18.80 2.78 6.75 <.001
NDSI -33.4 43.7 -0.76 0.453
NDVI -8.4 33.9 -0.25 0.808
NDWI3 12.1 35.2 0.34 0.736

Message: the variance of some parameter estimates is seriously inflated, due to near
collinearity or aliasing between the following parameters, listed with their variance
inflation factors.
NDVI 110.81

122 PREDICT [PRINT=description,predictions,se,lsd;

COMBINATIONS=estimable; LSDLEVEL=5]
Predictions from regression model
These predictions are estimated mean values.

The predictions are based on fixed values of some variates:

Variate Fixed value Source of value
NDSI -0.1559 Mean of variate
NDVI 0.1725 Mean of variate
NDWI3 -0.04900 Mean of variate

The standard errors are appropriate for interpretation of the predictions as summaries of the data
rather than as forecasts of new observations.

Response variate: %KA

Prediction s.e.
21.97 0.6505

Least significant differences of predictions (5% level)

1 *
1

123 RCHECK [RMETHOD=deviance] residual; composite

124 SDISCRIMINATE [PRINT=summary,validation,specificity,discrimination;
PLOT=errorrate,\
125 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
126 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
127 NSELECT=3; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(NDSI,\
128 NDVI,NDWI3); GROUPS=5; FORCED=!P(NDSI,NDVI,NDWI3)
Fault 1, code VA 11, statement 1 on line 128
Command: SDISCRIMINATE [PRINT=summary,validation,specificity,discrimination; PLO
Invalid or incompatible type(s).
Structure 5 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)

129 SDISCRIMINATE [PRINT=summary,validation,specificity,discrimination;

PLOT=errorrate,\
130 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
131 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
132 NSELECT=3; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(NDSI,\
133 NDVI,NDWI3); GROUPS=3; FORCED=!P(NDSI,NDVI,NDWI3)
Fault 2, code VA 11, statement 1 on line 133
Command: SDISCRIMINATE [PRINT=summary,validation,specificity,discrimination; PLO
Invalid or incompatible type(s).
Structure 3 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)
 134 SDISCRIMINATE [PRINT=summary,validation,specificity,discrimination;
PLOT=errorrate,\
135 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
136 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
137 NSELECT=4; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(%KA,\
138 NDSI,NDVI,NDWI3); GROUPS=3; FORCED=!P(NDSI,NDVI,NDWI3)
Fault 3, code VA 11, statement 1 on line 138
Command: SDISCRIMINATE [PRINT=summary,validation,specificity,discrimination; PLO
Invalid or incompatible type(s).
Structure 3 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)

139 SDISCRIMINATE
[PRINT=summary,steps,validation,specificity,discrimination;
PLOT=errorrate,\
140 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
141 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
142 NSELECT=4; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(%KA,\
143 NDSI,NDVI,NDWI3); GROUPS=10; FORCED=!P(NDSI,NDVI,NDWI3)
Fault 4, code VA 11, statement 1 on line 143
Command: SDISCRIMINATE [PRINT=summary,steps,validation,specificity,discriminatio
Invalid or incompatible type(s).
Structure 10 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)

144 SDISCRIMINATE
[PRINT=summary,steps,validation,specificity,discrimination;
PLOT=errorrate,\
145 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
146 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
147 NSELECT=4; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(%KA,\
148 NDSI,NDVI,NDWI3); GROUPS=3; FORCED=!P(NDSI,NDVI,NDWI3)
Fault 5, code VA 11, statement 1 on line 148
Command: SDISCRIMINATE [PRINT=summary,steps,validation,specificity,discriminatio
Invalid or incompatible type(s).
Structure 3 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)
 149 SDISCRIMINATE
[PRINT=summary,steps,validation,specificity,discrimination;
PLOT=errorrate,\
150 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
151 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
152 NSELECT=4; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(%KA,\
153 NDSI,NDVI,NDWI3); GROUPS=4; FORCED=!P(NDSI,NDVI,NDWI3)
Fault 6, code VA 11, statement 1 on line 153
Command: SDISCRIMINATE [PRINT=summary,steps,validation,specificity,discriminatio
Invalid or incompatible type(s).
Structure 4 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)

154 SDISCRIMINATE
[PRINT=summary,steps,validation,specificity,discrimination;
PLOT=errorrate,\
155 specificity,steps,discriminant;
DDISCRIMINANT=means,mlabels,scores,confidence; XROOT=1;\
156 YROOT=2; METHOD=forward; CRITERION=wilkslambda; MODELCHOICE=optimal;
VALIDATIONMETHOD=bootstrap;\
157 NSELECT=4; NSIMULATIONS=!(20,50); NCROSSVALIDATIONGROUPS=10; SEED=0]
DATA=!P(%KA,\
158 NDSI,NDVI,NDWI3); GROUPS=4; FORCED=!P(NDSI,NDVI,NDWI3,%KA)
Fault 7, code VA 11, statement 1 on line 158
Command: SDISCRIMINATE [PRINT=summary,steps,validation,specificity,discriminatio
Invalid or incompatible type(s).
Structure 4 of type scalar, should be of type factor.
(See the GROUPS parameter of the statement.)