Analysis
[1] "景気動向指数個別系列:一致系列:寄与度:商業販売額(小売業)(前年同月比):内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 0.14
2000 -0.03 0.16 -0.26 0.00 0.09 0.13 0.05 -0.05 -0.03 -0.08 0.12 0.00
2001 0.14 -0.18 0.20 -0.26 -0.01 -0.07 -0.05 -0.07 0.11 -0.19 0.16 -0.23
2002 0.08 -0.14 0.08 0.07 0.11 -0.03 -0.17 0.30 -0.06 0.02 0.08 -0.09
2003 0.08 0.21 -0.05 -0.13 0.07 0.02 -0.05 0.08 0.01 0.20 -0.33 0.27
2004 0.16 0.08 -0.34 0.05 -0.15 -0.05 0.35 -0.30 0.11 -0.08 0.13 -0.17
2005 0.31 -0.54 0.28 0.37 -0.09 0.02 -0.25 0.10 -0.14 -0.05 0.10 0.07
2006 -0.16 0.16 -0.01 -0.20 0.09 0.01 -0.03 0.10 -0.03 -0.07 -0.02 0.01
2007 -0.07 0.08 -0.04 0.07 0.07 -0.05 -0.19 0.28 0.00 0.03 0.06 -0.13
2008 0.11 0.16 -0.19 -0.17 0.04 0.00 0.18 -0.13 -0.09 -0.03 -0.14 -0.18
2009 -0.32 -0.26 0.12 0.06 0.00 -0.02 0.03 0.06 0.03 0.02 -0.02 0.07
2010 0.19 0.16 0.05 0.01 -0.16 0.04 0.09 0.03 -0.24 -0.12 0.13 -0.36
2011 0.20 0.01 -0.75 0.23 0.30 0.20 -0.09 -0.30 0.08 0.27 -0.34 0.44
2012 -0.09 0.14 0.59 -0.41 -0.19 -0.30 -0.10 0.24 -0.08 -0.15 0.19 -0.06
2013 -0.12 -0.10 0.17 0.01 0.09 0.07 -0.18 0.13 0.18 -0.06 0.17 -0.16
2014 0.19 -0.08 0.63 -1.12 0.39 -0.02 0.12 0.06 0.11 -0.09 -0.09 -0.04
2015 -0.21 0.03 -0.53 0.49 -0.19 -0.20 0.08 -0.10 -0.09 0.19 -0.29 0.00
2016 0.09 0.06 -0.14 0.01 -0.12 0.08 0.11 -0.20 0.05 0.15 0.19 -0.10
2017 0.03 -0.08 0.19 0.11 -0.11 0.01 -0.04 0.00 0.05 -0.25 0.23 0.15
2018 -0.21 0.02 -0.07 0.05 -0.09 0.11 -0.02 0.12 -0.05 0.14 -0.22 -0.01
2019 -0.07 0.00 0.04 -0.06 0.09 -0.08 -0.28 0.37 0.74
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.74986 -0.12817 0.00918 0.16371 0.60161
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0170580 0.0831300 0.205 0.839
ID -0.0009555 0.0036223 -0.264 0.793
Residual standard error: 0.2546 on 37 degrees of freedom
Multiple R-squared: 0.001877, Adjusted R-squared: -0.0251
F-statistic: 0.06957 on 1 and 37 DF, p-value: 0.7934
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.10256, p-value = 0.9885
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.3905, p-value = 0.8576
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 1.1605, df = 1, p-value = 0.2814
Box-Ljung test
data: lm_residuals
X-squared = 1.6092, df = 1, p-value = 0.2046
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-1.10746 -0.09815 -0.00174 0.10326 0.70614
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.0239599 0.0516704 -0.464 0.644
ID 0.0007139 0.0010948 0.652 0.516
Residual standard error: 0.2304 on 79 degrees of freedom
Multiple R-squared: 0.005354, Adjusted R-squared: -0.007237
F-statistic: 0.4252 on 1 and 79 DF, p-value: 0.5162
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.18519, p-value = 0.1245
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.6879, p-value = 0.999
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.69926, df = 1, p-value = 0.403
Box-Ljung test
data: lm_residuals
X-squared = 13.754, df = 1, p-value = 0.0002084
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.73921 -0.11119 0.02614 0.14260 0.59495
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.0278083 0.0579017 -0.48 0.633
ID 0.0004863 0.0016785 0.29 0.773
Residual standard error: 0.2196 on 57 degrees of freedom
Multiple R-squared: 0.00147, Adjusted R-squared: -0.01605
F-statistic: 0.08393 on 1 and 57 DF, p-value: 0.7731
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.13559, p-value = 0.6544
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.2341, p-value = 0.7795
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 3.0245, df = 1, p-value = 0.08202
Box-Ljung test
data: lm_residuals
X-squared = 0.94021, df = 1, p-value = 0.3322
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-1.10695 -0.09847 -0.00086 0.10185 0.70595
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.0224675 0.0533680 -0.421 0.675
ID 0.0007246 0.0011738 0.617 0.539
Residual standard error: 0.2334 on 76 degrees of freedom
Multiple R-squared: 0.004989, Adjusted R-squared: -0.008103
F-statistic: 0.3811 on 1 and 76 DF, p-value: 0.5389
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.17949, p-value = 0.1624
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.6979, p-value = 0.999
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 1.0104, df = 1, p-value = 0.3148
Box-Ljung test
data: lm_residuals
X-squared = 13.575, df = 1, p-value = 0.0002292