> summary(lm(cli_xts$oecd ~ cli_xts$usa + cli_xts$ea19 + cli_xts$china))
Call:
lm(formula = cli_xts$oecd ~ cli_xts$usa + cli_xts$ea19 + cli_xts$china)
Residuals:
Min 1Q Median 3Q Max
-0.68475 -0.09634 0.03744 0.11972 0.41636
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 9.265072 1.036438 8.939 <2e-16 ***
cli_xts$usa 0.402771 0.013317 30.246 <2e-16 ***
cli_xts$ea19 0.438171 0.012302 35.618 <2e-16 ***
cli_xts$china 0.065993 0.006695 9.857 <2e-16 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 0.1958 on 348 degrees of freedom
(420 observations deleted due to missingness)
Multiple R-squared: 0.9577, Adjusted R-squared: 0.9573
F-statistic: 2624 on 3 and 348 DF, p-value: < 2.2e-16
> last(cli_xts,n=12)
oecd usa china ea19
2018-05-01 100.33250 100.47600 99.29018 100.53100
2018-06-01 100.22810 100.42840 99.13142 100.40680
2018-07-01 100.11390 100.36340 98.96715 100.28170
2018-08-01 99.98618 100.27230 98.80726 100.14970
2018-09-01 99.84174 100.13410 98.67062 100.01150
2018-10-01 99.68746 99.94146 98.57309 99.87226
2018-11-01 99.53398 99.71795 98.51999 99.73539
2018-12-01 99.38741 99.48866 98.50362 99.59542
2019-01-01 99.25877 99.28568 98.52641 99.45764
2019-02-01 99.15687 99.12820 98.58793 99.32590
2019-03-01 99.08728 99.01845 98.69128 99.20160
2019-04-01 99.03429 98.93993 98.80725 99.08523
for future reference.
> last(tmp.predict,n=6)
SP5.Open SP5.High SP5.Low SP5.Close SP5.Volume spline eps
1 2019 2476.96 2708.95 2443.96 2704.10 80391630000 2906.849 2760.208
2 2019 2702.32 2813.49 2681.83 2784.49 70183430000 2929.656 2779.348
3 2019 2798.22 2860.31 2722.27 2834.40 78596280000 2956.669 2804.840
4 2019 2848.63 2949.52 2848.63 2945.83 69604840000 2983.000 2829.000
5 2019 2952.33 2954.13 2750.52 2752.06 76860120000 3010.000 2854.000
6 2019 2751.53 2910.61 2728.81 2886.98 33703630000 3037.000 2879.000
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