*****************************
ROAD ACCIDENTS IN GREAT BRITAIN
*****************************
Ox Professional version 6.10 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2010
STAMP 8.30 (C) S.J. Koopman and A.C. Harvey, 1995-2010
---- STAMP 8.30 session started at 12:00:56 on  7-06-2021 ----

Algebra code for UKdeaths.in7:
Laccidents = log(accidents);

 Estimating....
 Very strong convergence relative to 1e-007
 - likelihood cvg 5.1971e-015
 - gradient cvg 1.49345e-009
 - parameter cvg 5.49712e-008
 - number of bad iterations 0
 Estimation process completed.

UC( 1) Estimation done by Maximum Likelihood (exact score)
	The database used is D:\Google Drive\papers\UCompJSS\submission4\UKdeaths.in7
	The selection sample is: 1969(1) - 1982(12) (T = 168, N = 1)
	The dependent variable Y is: Laccidents
	The model is:  Y = Trend + Seasonal + Irregular
	Steady state........... found without full convergence

Log-Likelihood is 373.243 (-2 LogL = -746.487).
Prediction error variance is 0.00508516

Summary statistics
               Laccidents
 T                 168.00
 p                 3.0000
 std.error       0.071310
 Normality         2.5385
 H(51)            0.83056
 DW                1.9137
 r(1)            0.034417
 q                 24.000
 r(q)            -0.11585
 Q(q,q-p)          37.475
 Rs^2             0.36648

 Variances of disturbances:
                    Value    (q-ratio)
Level         0.000585376  (   0.1581)
Slope            0.000000  (   0.0000)
Seasonal         0.000000  (   0.0000)
Irregular      0.00370291  (    1.000)


State vector analysis at period 1982(12)
                             Value      Prob
Level                      7.40528 [0.00000]
Slope                     -0.00002 [0.99036]
Seasonal chi2 test       391.01686 [0.00000]
Seasonal effects:
                Period       Value      Prob
                     1     0.01386 [0.41475]
                     2    -0.09611 [0.00000]
                     3    -0.06924 [0.00007]
                     4    -0.14471 [0.00000]
                     5    -0.05644 [0.00102]
                     6    -0.08342 [0.00000]
                     7    -0.03648 [0.03196]
                     8    -0.02612 [0.12339]
                     9    -0.00829 [0.62401]
                    10     0.07408 [0.00002]
                    11     0.18668 [0.00000]
                    12     0.24618 [0.00000]

*****************************
RAINFALL IN FORTALEZA
*****************************
Ox Professional version 6.10 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2010
STAMP 8.30 (C) S.J. Koopman and A.C. Harvey, 1995-2010
---- STAMP 8.30 session started at 11:43:18 on  7-06-2021 ----

 Estimating....
 Strong convergence relative to 1e-007
 - likelihood cvg 2.20684e-015
 - gradient cvg 2.35315e-009
 - parameter cvg 1.27585e-007
 - number of bad iterations 0
 Estimation process completed.

UC( 1) Estimation done by Maximum Likelihood (exact score)
	The database used is D:\Google Drive\papers\UCompJSS\submission4\rainfall.in7
	The selection sample is: 1849 - 1979 (T = 131, N = 1)
	The dependent variable Y is: Var1
	The model is:  Y = Irregular + Cycle 2 + Explanatory vars
	Steady state. found

Log-Likelihood is -500.869 (-2 LogL = 1001.74).
Prediction error variance is 2126.2

Summary statistics
                     Var1
 T                 131.00
 p                 3.0000
 std.error         46.111
 Normality         3.6231
 H(43)             1.1341
 DW                1.9510
 r(1)            0.011894
 q                 13.000
 r(q)            -0.11520
 Q(q,q-p)          8.4101
 R^2             0.084714

 Variances of disturbances:
                    Value    (q-ratio)
Cycle             229.456  (   0.1450)
Irregular         1582.78  (    1.000)


Cycle other parameters:

Variance         743.67596
Period            15.62418
Frequency          0.40214
Damping factor     0.83154
Order              1.00000

State vector analysis at period 1979
                        Value      Prob
Cycle 2 amplitude    18.91412 [   .NaN]

Regression effects in final state at time 1979

       Coefficient        RMSE     t-value      Prob
u        142.24256     4.81533    29.53951 [0.00000]


******************************
PURSE SNATCHING IN CHICAGO
******************************
Ox Professional version 6.10 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2010
STAMP 8.30 (C) S.J. Koopman and A.C. Harvey, 1995-2010
---- STAMP 8.30 session started at 11:48:43 on  7-06-2021 ----

 Estimating...
 Very strong convergence relative to 1e-007
 - likelihood cvg 1.35023e-015
 - gradient cvg 1.24256e-008
 - parameter cvg 4.60721e-008
 - number of bad iterations 0
 Estimation process completed.

UC( 1) Estimation done by Maximum Likelihood (exact score)
	The database used is D:\Google Drive\papers\UCompJSS\submission4\purse.in7
	The selection sample is: 1 - 71 (T = 71, N = 1)
	The dependent variable Y is: purse
	The model is:  Y = Level + Irregular
	Steady state. found

Log-Likelihood is -128.435 (-2 LogL = 256.87).
Prediction error variance is 38.3965

Summary statistics
                    purse
 T                 71.000
 p                 1.0000
 std.error         6.1965
 Normality         4.4690
 H(23)            0.42740
 DW                2.0595
 r(1)           -0.033787
 q                 8.0000
 r(q)           -0.073492
 Q(q,q-p)          7.8790
 R^2              0.32050

 Variances of disturbances:
                    Value    (q-ratio)
Level             5.15088  (   0.2079)
Irregular         24.7816  (    1.000)


State vector analysis at period 71
             Value      Prob
Level      7.38658 [0.01635]

******************************
US GNP CYCLES AND TRENDS
******************************
Ox Professional version 6.10 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2010
STAMP 8.30 (C) S.J. Koopman and A.C. Harvey, 1995-2010
---- STAMP 8.30 session started at 11:37:28 on  7-06-2021 ----

 Estimating........
 Very strong convergence relative to 1e-007
 - likelihood cvg 1.58119e-014
 - gradient cvg 2.21552e-008
 - parameter cvg 8.66282e-008
 - number of bad iterations 0
 Estimation process completed.

UC( 1) Estimation done by Maximum Likelihood (exact score)
	The database used is D:\Google Drive\papers\UCompJSS\submission4\USgnp.in7
	The selection sample is: 1910 - 1970 (T = 61, N = 1)
	The dependent variable Y is: LUSgnp
	The model is:  Y = Trend + Irregular + Cycle 1
	Steady state. found

Log-Likelihood is 161.044 (-2 LogL = -322.088).
Prediction error variance is 0.00404814

Summary statistics
                   LUSgnp
 T                 61.000
 p                 5.0000
 std.error       0.063625
 Normality         2.2661
 H(19)            0.25236
 DW                1.8371
 r(1)            0.080342
 q                 11.000
 r(q)             0.14364
 Q(q,q-p)          12.819
 Rd^2            0.043772

 Variances of disturbances:
                    Value    (q-ratio)
Level          0.00173565  (    1.000)
Slope         0.000359881  (   0.2073)
Cycle         0.000385840  (   0.2223)
Irregular        0.000000  (   0.0000)


Cycle other parameters:

Variance           0.00197
Period             7.63842
Frequency          0.82258
Damping factor     0.89668
Order              1.00000

State vector analysis at period 1970
                        Value      Prob
Level                 6.59262 [0.00000]
Slope                 0.04139 [0.22756]
Cycle 1 amplitude     0.00818 [   .NaN]



******************************
QUARTERLY AIRLINE PASSENGERS DATA
******************************
Ox Professional version 6.10 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2010
STAMP 8.30 (C) S.J. Koopman and A.C. Harvey, 1995-2010
---- STAMP 8.30 session started at 11:22:21 on  7-06-2021 ----

 Estimating....
 Very strong convergence relative to 1e-007
 - likelihood cvg 4.93423e-014
 - gradient cvg 4.67007e-008
 - parameter cvg 6.22969e-008
 - number of bad iterations 0
 Estimation process completed.

UC( 1) Estimation done by Maximum Likelihood (exact score)
	The database used is D:\Google Drive\papers\UCompJSS\submission4\qairline.in7
	The selection sample is: 1949(1) - 1960(4) (T = 48, N = 1)
	The dependent variable Y is: Lairline
	The model is:  Y = Trend + Seasonal + Irregular
	Steady state........... found without full convergence

Log-Likelihood is 139.107 (-2 LogL = -278.214).
Prediction error variance is 0.00109751

Summary statistics
                 Lairline
 T                 48.000
 p                 3.0000
 std.error       0.033129
 Normality        0.73153
 H(14)            0.78517
 DW                1.7717
 r(1)             0.11137
 q                 8.0000
 r(q)            0.080038
 Q(q,q-p)          2.5285
 Rs^2             0.39703

 Variances of disturbances:
                    Value    (q-ratio)
Level         0.000627345  (    1.000)
Slope            0.000000  (   0.0000)
Seasonal     2.01038e-005  (  0.03205)
Irregular        0.000000  (   0.0000)


State vector analysis at period 1960(4)
                             Value      Prob
Level                      7.29041 [0.00000]
Slope                      0.02930 [0.00000]
Seasonal chi2 test       277.26636 [0.00000]
Seasonal effects:
                Period       Value      Prob
                     1    -0.09852 [0.00000]
                     2     0.04145 [0.00843]
                     3     0.19051 [0.00000]
                     4    -0.13345 [0.00000]

***********************************
COAL CONSUMPTION IN GREAT BRITAIN
***********************************
Ox Professional version 6.10 (Windows_64/U/MT) (C) J.A. Doornik, 1994-2010
STAMP 8.30 (C) S.J. Koopman and A.C. Harvey, 1995-2010
---- STAMP 8.30 session started at 11:40:40 on  7-06-2021 ----

 Estimating.....
 Weak convergence relative to 1e-007
 - likelihood cvg 3.1224e-012
 - gradient cvg 1.06796e-006
 - parameter cvg 6.10893e-007
 - number of bad iterations 0
 Estimation process completed.

UC( 1) Estimation done by Maximum Likelihood (exact score)
	The database used is D:\Google Drive\papers\UCompJSS\submission4\energy.in7
	The selection sample is: 1960(1) - 1982(4) (T = 92, N = 1)
	The dependent variable Y is: LVar2
	The model is:  Y = Trend + Seasonal + Irregular
	Steady state........... found without full convergence

Log-Likelihood is 165.439 (-2 LogL = -330.877).
Prediction error variance is 0.0170701

Summary statistics
                    LVar2
 T                 92.000
 p                 3.0000
 std.error        0.13065
 Normality         5.6942
 H(29)            0.95600
 DW                1.9351
 r(1)            0.019827
 q                 11.000
 r(q)            -0.21204
 Q(q,q-p)          10.701
 Rs^2             0.37438

 Variances of disturbances:
                    Value    (q-ratio)
Level         0.000473730  (  0.03487)
Slope        7.07279e-006  (0.0005207)
Seasonal         0.000000  (   0.0000)
Irregular       0.0135842  (    1.000)


State vector analysis at period 1982(4)
                             Value      Prob
Level                      4.03911 [0.00000]
Slope                     -0.00335 [0.72253]
Seasonal chi2 test       517.44101 [0.00000]
Seasonal effects:
                Period       Value      Prob
                     1     0.26358 [0.00000]
                     2    -0.10337 [0.00000]
                     3    -0.41014 [0.00000]
                     4     0.24994 [0.00000]
