Analysis
[1] "景気動向指数個別系列:一致系列:寄与度:商業販売額(卸売業)(前年同月比):内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 0.03
2000 -0.02 0.17 -0.22 0.02 0.27 -0.01 -0.24 0.28 -0.30 0.31 -0.05 0.18
2001 -0.07 -0.24 -0.04 0.07 0.00 -0.06 -0.04 -0.12 -0.12 0.11 -0.08 -0.05
2002 0.01 -0.02 -0.07 0.32 -0.01 -0.15 0.21 -0.09 0.07 0.11 0.09 -0.09
2003 0.13 0.07 0.01 -0.04 0.02 0.10 -0.18 0.06 0.12 0.18 -0.41 0.35
2004 0.05 -0.07 -0.01 0.21 -0.32 0.45 0.07 -0.07 -0.24 -0.08 0.36 -0.28
2005 -0.02 -0.07 -0.26 0.16 0.01 -0.10 -0.12 0.38 -0.25 0.09 0.17 0.04
2006 0.15 -0.02 -0.21 0.11 0.27 -0.20 0.05 0.06 -0.21 0.30 -0.21 -0.13
2007 0.04 0.04 -0.16 0.32 0.18 -0.13 0.08 -0.13 -0.14 0.34 -0.04 -0.11
2008 0.15 0.15 -0.32 0.26 -0.05 0.00 0.37 -0.52 0.04 -0.37 -0.60 -0.23
2009 -0.37 -0.34 -0.15 0.04 -0.08 0.08 -0.08 0.09 0.03 0.16 0.32 0.25
2010 0.51 0.22 0.24 0.10 -0.15 -0.01 -0.03 0.08 0.02 -0.07 0.37 -0.06
2011 -0.07 0.17 -0.39 -0.17 0.22 0.09 -0.06 0.13 -0.27 0.01 -0.20 0.01
2012 -0.12 0.17 0.15 -0.04 0.14 -0.41 -0.03 -0.03 -0.05 0.21 0.01 -0.06
2013 0.16 -0.10 -0.04 0.11 0.04 -0.03 0.12 -0.11 0.16 -0.06 0.05 0.05
2014 0.13 -0.15 0.43 -0.74 0.14 0.08 0.05 -0.17 0.31 -0.08 -0.27 0.15
2015 -0.08 -0.07 -0.26 0.45 -0.40 0.36 -0.13 -0.01 -0.15 0.07 -0.04 -0.13
2016 -0.17 0.14 -0.20 0.10 -0.10 -0.05 -0.03 0.25 -0.16 -0.05 0.37 -0.08
2017 0.16 -0.02 0.25 -0.17 0.39 -0.13 -0.09 0.09 -0.02 0.08 0.05 0.10
2018 0.01 -0.21 -0.09 0.27 0.00 -0.19 0.12 -0.06 -0.32 0.49 -0.27 -0.32
2019 -0.03 -0.01 -0.11 0.16 -0.22 -0.03 0.22 -0.27 0.58
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.43760 -0.12077 0.01693 0.11513 0.37333
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.162119 0.058974 2.749 0.00919 **
ID -0.006362 0.002570 -2.476 0.01799 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 0.1806 on 37 degrees of freedom
Multiple R-squared: 0.1421, Adjusted R-squared: 0.1189
F-statistic: 6.13 on 1 and 37 DF, p-value: 0.01799
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.23077, p-value = 0.2523
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.9796, p-value = 0.4064
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.05916, df = 1, p-value = 0.8078
Box-Ljung test
data: lm_residuals
X-squared = 0.0041516, df = 1, p-value = 0.9486
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.74239 -0.13296 -0.03201 0.11795 0.57516
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.00178704 0.04843025 0.037 0.971
ID 0.00003771 0.00102610 0.037 0.971
Residual standard error: 0.2159 on 79 degrees of freedom
Multiple R-squared: 1.71e-05, Adjusted R-squared: -0.01264
F-statistic: 0.001351 on 1 and 79 DF, p-value: 0.9708
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.12346, p-value = 0.5705
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.9437, p-value = 1
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.27853, df = 1, p-value = 0.5977
Box-Ljung test
data: lm_residuals
X-squared = 22.736, df = 1, p-value = 0.000001858
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.55150 -0.09754 0.00120 0.12598 0.53682
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.059345 0.057469 -1.033 0.306
ID 0.001549 0.001666 0.930 0.356
Residual standard error: 0.2179 on 57 degrees of freedom
Multiple R-squared: 0.01494, Adjusted R-squared: -0.002345
F-statistic: 0.8643 on 1 and 57 DF, p-value: 0.3565
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.15254, p-value = 0.5021
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.5964, p-value = 0.04341
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 5.6635, df = 1, p-value = 0.01732
Box-Ljung test
data: lm_residuals
X-squared = 2.5031, df = 1, p-value = 0.1136
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.74168 -0.13276 -0.02757 0.11797 0.57458
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.00093240 0.05008086 0.019 0.985
ID 0.00005754 0.00110150 0.052 0.958
Residual standard error: 0.219 on 76 degrees of freedom
Multiple R-squared: 3.59e-05, Adjusted R-squared: -0.01312
F-statistic: 0.002729 on 1 and 76 DF, p-value: 0.9585
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.16667, p-value = 0.2297
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.948, p-value = 1
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.094819, df = 1, p-value = 0.7581
Box-Ljung test
data: lm_residuals
X-squared = 21.988, df = 1, p-value = 0.000002743