Estadisticas

Pregunta nº 1

Dependent Variable: G | | |
Method: Least Squares | | |
Date: 06/06/10 Time: 21:34 | | |
Sample (adjusted): 2 40 | | |
Included observations: 39 after adjustments | |
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Variable | Coefficient | Std. Error | t-Statistic | Prob.   |
| | | | |
| | | | |
C | -4.310671 | 3.594495 | -1.199242 | 0.2381 |
V(-1) |0.631164 | 0.060489 | 10.43434 | 0.0000 |
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R-squared | 0.746359 |     Mean dependent var | 32.34559 |
Adjusted R-squared | 0.739504 |     S.D. dependent var | 9.309888 |
S.E. of regression | 4.751659 |     Akaike info criterion | 6.004785 |
Sum squared resid | 835.3957 |     Schwarz criterion | 6.090096 |
Log likelihood | -115.0933 |     Hannan-Quinn criter.| 6.035394 |
F-statistic | 108.8754 |     Durbin-Watson stat | 0.453081 |
Prob(F-statistic) | 0.000000 | | | |
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* Jarque bera tiene una distribución normal de los errores , ya que esta muy por debajo del 5.99 permitido.
* Asimetría cerca de su índice mientras la curtosis aun esta un poco bajo
* Durbin Watson bajo 2, muy cercano a cero.
* Tstadistico de la C bajo el t observado

Modelo ideal para este caso

Dependent Variable: G | | |
Method: Least Squares | | |
Date: 06/07/10 Time: 03:54 | | |
Sample (adjusted): 2 40 | | |
Included observations: 39 after adjustments | |
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| | | | |
Variable | Coefficient | Std. Error | t-Statistic | Prob.   |
| | | | |
| | | | |
C |3.258195 | 1.876044 | 1.736737 | 0.0910 |
V(-1) | 0.053484 | 0.060180 | 0.888735 | 0.3800 |
G(-1) | 0.823109 | 0.074843 | 10.99775 | 0.0000 |
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R-squared | 0.941822 |     Mean dependent var | 32.34559 |
Adjusted R-squared | 0.938590 |     S.D. dependent var | 9.309888 |
S.E. of regression | 2.307091 |     Akaike info criterion | 4.583656 |
Sum squaredresid | 191.6161 |     Schwarz criterion | 4.711622 |
Log likelihood | -86.38129 |     Hannan-Quinn criter. | 4.629569 |
F-statistic | 291.3948 |     Durbin-Watson stat | 2.233758 |
Prob(F-statistic) | 0.000000 | | | |
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* Jarque bera tieneuna tendencia de distribución anormal de los errores , Asimetría cerca de su índice mientras la curtosis aun estaun poco bajo
* Durbin Watson de buena calidad
* T stadistico de la C bajo el t observado.

Dependent Variable: G | | |
Method: Least Squares | | |
Date: 06/06/10 Time: 21:56 | | |
Sample (adjusted): 2 40 | | |
Included observations: 39 after adjustments | |
| | | | |
| | | | |
Variable | Coefficient | Std. Error | t-Statistic | Prob.   |
| | | ||
| | | | |
V(-1) | 0.133326 | 0.039880 | 3.343179 | 0.0019 |
G(-1) | 0.775425 | 0.071497 | 10.84551 | 0.0000 |
| | | | |
| | | | |
R-squared | 0.936947 |     Mean dependent var | 32.34559 |
Adjusted R-squared | 0.935243 |     S.D. dependent var | 9.309888 |
S.E. of regression | 2.369118 |     Akaike info criterion | 4.612833 |
Sum squared resid | 207.6707 |    Schwarz criterion | 4.698144 |
Log likelihood | -87.95024 |     Hannan-Quinn criter. | 4.643442 |
Durbin-Watson stat | 2.030569 | | | |
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* Jarque bera tiende a tener una distribución anormal de sus errores, cerca del pto critico 5.99
* Asimetría y curtosis cerca de sus parámetros
* Durbin Watson de buena calidad (2.03)

Dependent Variable: G | ||
Method: Least Squares | | |
Date: 06/06/10 Time: 22:37 | | |
Sample (adjusted): 2 40 | | |
Included observations: 39 after adjustments | |
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Variable | Coefficient | Std. Error | t-Statistic | Prob.   |
| | | | |
| | | | |
LOG(V(-1)) | -11.80154 | 1.543702 | -7.644959 | 0.0000 |
LOG(G(-1)) | 23.74772 | 1.833909 |...