Model.f1:
lm(formula = net ~ netlag1 + netlag11 + pricelag1 + pricelag11,
data = alldata, na.action = na.omit)
Residuals:
Min 1Q Median 3Q Max
-0.244190 -0.044882 0.005554 0.042514 0.186536
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.55702 0.49136 9.274 2.08e-15 ***
netlag1 0.73812 0.02756 26.782 < 2e-16 ***
netlag11 0.10081 0.01491 6.762 7.24e-10 ***
pricelag1 0.23224 0.02025 11.466 < 2e-16 ***
pricelag11 -0.05139 0.01337 -3.844 0.000205 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.06588 on 108 degrees of freedom
(23 observations deleted due to missingness)
Multiple R-squared: 0.9991, Adjusted R-squared: 0.9991
F-statistic: 3.005e+04 on 4 and 108 DF, p-value: < 2.2e-16
Model.f2:
lm(formula = net ~ netlag2 + netlag11 + pricelag2 + pricelag12,
data = alldata, na.action = na.omit)
Residuals:
Min 1Q Median 3Q Max
-0.32227 -0.05663 0.00767 0.06815 0.18924
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.53685 0.70969 12.029 < 2e-16 ***
netlag2 0.47975 0.04220 11.369 < 2e-16 ***
netlag11 0.21922 0.02571 8.528 1.07e-13 ***
pricelag2 0.43515 0.03025 14.383 < 2e-16 ***
pricelag12 -0.10761 0.02156 -4.991 2.34e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.09841 on 107 degrees of freedom
(24 observations deleted due to missingness)
Multiple R-squared: 0.9979, Adjusted R-squared: 0.9978
F-statistic: 1.256e+04 on 4 and 107 DF, p-value: < 2.2e-16
Model.f3:
lm(formula = net ~ netlag3 + netlag11 + pricelag3 + pricelag9,
data = alldata, na.action = na.omit)
Residuals:
Min 1Q Median 3Q Max
-0.32684 -0.05948 0.00370 0.07135 0.40748
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 8.93382 1.08794 8.212 5.11e-13 ***
netlag3 0.48942 0.06548 7.475 2.15e-11 ***
netlag11 0.19678 0.03235 6.083 1.82e-08 ***
pricelag3 0.52225 0.04226 12.359 < 2e-16 ***
pricelag9 -0.19518 0.02951 -6.613 1.48e-09 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.1349 on 108 degrees of freedom
(23 observations deleted due to missingness)
Multiple R-squared: 0.9962, Adjusted R-squared: 0.9961
F-statistic: 7142 on 4 and 108 DF, p-value: < 2.2e-16
Model.f4:
lm(formula = net ~ netlag4 + netlag11 + pricelag4 + pricelag9,
data = alldata, na.action = na.omit)
Residuals:
Min 1Q Median 3Q Max
-0.38865 -0.11274 -0.00182 0.10096 0.56920
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.29140 1.40845 6.597 1.60e-09 ***
netlag4 0.45075 0.09191 4.904 3.33e-06 ***
netlag11 0.22519 0.04856 4.637 9.95e-06 ***
pricelag4 0.62582 0.05709 10.963 < 2e-16 ***
pricelag9 -0.31562 0.04151 -7.603 1.13e-11 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.1782 on 108 degrees of freedom
(23 observations deleted due to missingness)
Multiple R-squared: 0.9934, Adjusted R-squared: 0.9932
F-statistic: 4084 on 4 and 108 DF, p-value: < 2.2e-16
Canary model:
lm(formula = net.12mo ~ price.12mo + netlag1 + netlag3, data = alldata.12mo,
na.action = na.omit)
Residuals:
Min 1Q Median 3Q Max
-0.112897 -0.025772 0.002283 0.029323 0.105128
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.7050 1.2787 2.897 0.005698 **
price.12mo 0.1368 0.0384 3.563 0.000852 ***
netlag1 0.5316 0.1226 4.337 7.59e-05 ***
netlag3 0.3383 0.1073 3.154 0.002810 **
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.04435 on 47 degrees of freedom
(15 observations deleted due to missingness)
Multiple R-squared: 0.9843, Adjusted R-squared: 0.9833
F-statistic: 980.9 on 3 and 47 DF, p-value: < 2.2e-16
