| Multiple Linear Regression - Estimated Regression Equation |
| y[t] = + 1.36941919191919 -0.0599810606060606x[t] + 0.0153472222222228M1[t] + 0.0274368686868686M2[t] + 0.0245265151515151M3[t] + 0.0216161616161616M4[t] + 0.0170391414141414M5[t] + 0.0124621212121212M6[t] + 0.0112184343434343M7[t] + 0.0149747474747475M8[t] + 0.0120643939393939M9[t] + 0.0091540404040404M10[t] + 0.00457702020202021M11[t] + 0.0045770202020202t + e[t] |
| Multiple Linear Regression - Ordinary Least Squares | |||||
| Variable | Parameter | S.D. | T-STAT H0: parameter = 0 | 2-tail p-value | 1-tail p-value |
| (Intercept) | 1.36941919191919 | 0.013249 | 103.3606 | 0 | 0 |
| x | -0.0599810606060606 | 0.012359 | -4.8532 | 1e-05 | 5e-06 |
| M1 | 0.0153472222222228 | 0.016304 | 0.9413 | 0.350435 | 0.175218 |
| M2 | 0.0274368686868686 | 0.016251 | 1.6883 | 0.09673 | 0.048365 |
| M3 | 0.0245265151515151 | 0.016204 | 1.5136 | 0.135559 | 0.06778 |
| M4 | 0.0216161616161616 | 0.016162 | 1.3375 | 0.186283 | 0.093142 |
| M5 | 0.0170391414141414 | 0.016124 | 1.0567 | 0.295009 | 0.147505 |
| M6 | 0.0124621212121212 | 0.016092 | 0.7745 | 0.441809 | 0.220905 |
| M7 | 0.0112184343434343 | 0.016064 | 0.6984 | 0.487741 | 0.24387 |
| M8 | 0.0149747474747475 | 0.016041 | 0.9335 | 0.354424 | 0.177212 |
| M9 | 0.0120643939393939 | 0.016024 | 0.7529 | 0.454547 | 0.227273 |
| M10 | 0.0091540404040404 | 0.016011 | 0.5717 | 0.569711 | 0.284855 |
| M11 | 0.00457702020202021 | 0.016003 | 0.286 | 0.775895 | 0.387948 |
| t | 0.0045770202020202 | 0.000284 | 16.1002 | 0 | 0 |
| Multiple Linear Regression - Regression Statistics | |
| Multiple R | 0.946355172757994 |
| R-squared | 0.895588113005812 |
| Adjusted R-squared | 0.872185448679529 |
| F-TEST (value) | 38.2686390113275 |
| F-TEST (DF numerator) | 13 |
| F-TEST (DF denominator) | 58 |
| p-value | 0 |
| Multiple Linear Regression - Residual Statistics | |
| Residual Standard Deviation | 0.0277143454598930 |
| Sum Squared Residuals | 0.0445489267676770 |
| Multiple Linear Regression - Actuals, Interpolation, and Residuals | |||
| Time or Index | Actuals | Interpolation Forecast | Residuals Prediction Error |
| 1 | 1.43 | 1.38934343434343 | 0.0406565656565684 |
| 2 | 1.43 | 1.4060101010101 | 0.0239898989898989 |
| 3 | 1.43 | 1.40767676767677 | 0.0223232323232322 |
| 4 | 1.43 | 1.40934343434343 | 0.0206565656565656 |
| 5 | 1.43 | 1.40934343434343 | 0.0206565656565656 |
| 6 | 1.43 | 1.40934343434343 | 0.0206565656565655 |
| 7 | 1.43 | 1.41267676767677 | 0.0173232323232322 |
| 8 | 1.43 | 1.4210101010101 | 0.00898989898989885 |
| 9 | 1.43 | 1.42267676767677 | 0.00732323232323219 |
| 10 | 1.43 | 1.42434343434343 | 0.00565656565656553 |
| 11 | 1.43 | 1.42434343434343 | 0.00565656565656554 |
| 12 | 1.43 | 1.42434343434343 | 0.00565656565656553 |
| 13 | 1.43 | 1.44426767676768 | -0.0142676767676774 |
| 14 | 1.43 | 1.46093434343434 | -0.0309343434343435 |
| 15 | 1.43 | 1.46260101010101 | -0.0326010101010102 |
| 16 | 1.43 | 1.46426767676768 | -0.0342676767676768 |
| 17 | 1.43 | 1.46426767676768 | -0.0342676767676768 |
| 18 | 1.43 | 1.46426767676768 | -0.0342676767676768 |
| 19 | 1.44 | 1.46760101010101 | -0.0276010101010102 |
| 20 | 1.48 | 1.47593434343434 | 0.00406565656565652 |
| 21 | 1.48 | 1.47760101010101 | 0.00239898989898984 |
| 22 | 1.48 | 1.47926767676768 | 0.000732323232323181 |
| 23 | 1.48 | 1.47926767676768 | 0.000732323232323176 |
| 24 | 1.48 | 1.47926767676768 | 0.000732323232323183 |
| 25 | 1.48 | 1.43921085858586 | 0.0407891414141408 |
| 26 | 1.48 | 1.45587752525253 | 0.0241224747474747 |
| 27 | 1.48 | 1.45754419191919 | 0.0224558080808081 |
| 28 | 1.48 | 1.45921085858586 | 0.0207891414141414 |
| 29 | 1.48 | 1.45921085858586 | 0.0207891414141414 |
| 30 | 1.48 | 1.45921085858586 | 0.0207891414141414 |
| 31 | 1.48 | 1.46254419191919 | 0.0174558080808081 |
| 32 | 1.48 | 1.47087752525253 | 0.00912247474747473 |
| 33 | 1.48 | 1.47254419191919 | 0.00745580808080807 |
| 34 | 1.48 | 1.47421085858586 | 0.0057891414141414 |
| 35 | 1.48 | 1.47421085858586 | 0.00578914141414141 |
| 36 | 1.48 | 1.47421085858586 | 0.00578914141414142 |
| 37 | 1.48 | 1.49413510101010 | -0.0141351010101016 |
| 38 | 1.48 | 1.51080176767677 | -0.0308017676767677 |
| 39 | 1.48 | 1.51246843434343 | -0.0324684343434343 |
| 40 | 1.48 | 1.5141351010101 | -0.034135101010101 |
| 41 | 1.48 | 1.5141351010101 | -0.034135101010101 |
| 42 | 1.48 | 1.5141351010101 | -0.0341351010101010 |
| 43 | 1.48 | 1.51746843434343 | -0.0374684343434343 |
| 44 | 1.48 | 1.52580176767677 | -0.0458017676767676 |
| 45 | 1.48 | 1.52746843434343 | -0.0474684343434343 |
| 46 | 1.48 | 1.5291351010101 | -0.049135101010101 |
| 47 | 1.48 | 1.5291351010101 | -0.049135101010101 |
| 48 | 1.48 | 1.5291351010101 | -0.049135101010101 |
| 49 | 1.48 | 1.54905934343434 | -0.069059343434344 |
| 50 | 1.57 | 1.56572601010101 | 0.00427398989899005 |
| 51 | 1.58 | 1.56739267676768 | 0.0126073232323234 |
| 52 | 1.58 | 1.56905934343434 | 0.0109406565656567 |
| 53 | 1.58 | 1.56905934343434 | 0.0109406565656567 |
| 54 | 1.58 | 1.56905934343434 | 0.0109406565656567 |
| 55 | 1.59 | 1.57239267676768 | 0.0176073232323234 |
| 56 | 1.6 | 1.58072601010101 | 0.0192739898989901 |
| 57 | 1.6 | 1.58239267676768 | 0.0176073232323234 |
| 58 | 1.61 | 1.58405934343434 | 0.0259406565656567 |
| 59 | 1.61 | 1.58405934343434 | 0.0259406565656567 |
| 60 | 1.61 | 1.58405934343434 | 0.0259406565656567 |
| 61 | 1.62 | 1.60398358585859 | 0.0160164141414137 |
| 62 | 1.63 | 1.62065025252525 | 0.00934974747474748 |
| 63 | 1.63 | 1.62231691919192 | 0.00768308080808083 |
| 64 | 1.64 | 1.62398358585859 | 0.0160164141414142 |
| 65 | 1.64 | 1.62398358585859 | 0.0160164141414141 |
| 66 | 1.64 | 1.62398358585859 | 0.0160164141414142 |
| 67 | 1.64 | 1.62731691919192 | 0.0126830808080808 |
| 68 | 1.64 | 1.63565025252525 | 0.00434974747474748 |
| 69 | 1.65 | 1.63731691919192 | 0.0126830808080808 |
| 70 | 1.65 | 1.63898358585859 | 0.0110164141414142 |
| 71 | 1.65 | 1.63898358585859 | 0.0110164141414142 |
| 72 | 1.65 | 1.63898358585859 | 0.0110164141414142 |
