Analysis
[1] "景気動向指数個別系列:先行系列:寄与度:鉱工業用生産財在庫率指数(逆サイクル):内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 -0.03
2000 -0.40 0.46 -0.19 -0.03 0.05 0.11 -0.29 0.36 -0.29 -0.25 -0.02 -0.05
2001 -0.55 -0.20 -0.16 -0.56 0.23 -0.28 -0.03 0.07 0.02 -0.10 0.03 0.13
2002 0.45 0.40 0.11 0.63 0.53 -0.28 0.28 -0.09 -0.12 0.17 -0.02 -0.12
2003 0.18 0.13 -0.23 -0.11 0.22 -0.34 0.29 -0.19 0.24 0.39 -0.70 0.51
2004 0.06 -0.14 0.07 -0.03 -0.15 0.17 0.23 -0.51 0.09 -0.23 0.18 -0.07
2005 -0.32 -0.08 0.17 -0.10 -0.21 0.19 -0.39 0.12 0.04 -0.04 -0.04 0.05
2006 -0.12 0.05 0.02 0.07 -0.17 0.17 -0.20 0.36 -0.40 -0.02 -0.11 -0.08
2007 0.09 -0.22 -0.34 0.15 0.42 -0.36 0.15 0.18 -0.62 0.69 -0.36 -0.08
2008 0.01 0.27 -0.17 -0.36 -0.13 -0.47 0.46 -0.70 0.13 -0.39 -0.80 -0.73
2009 -0.57 -0.46 0.51 0.78 0.67 0.77 0.61 -0.15 0.77 0.55 -0.02 0.68
2010 0.11 -0.56 0.81 -0.23 -0.22 0.09 -0.08 -0.14 -0.04 -0.54 0.63 -0.29
2011 0.09 -0.40 -0.65 -0.63 -0.42 0.73 -0.16 0.46 -0.28 -0.17 -0.07 0.40
2012 -0.17 0.62 0.04 -0.12 0.26 -0.34 -0.39 -0.01 -0.27 0.18 0.00 0.03
2013 -0.31 0.30 0.48 0.02 0.11 0.02 0.32 -0.08 0.00 -0.01 0.35 -0.19
2014 -0.06 -0.20 -0.15 -0.21 -0.14 -0.11 0.02 -0.24 0.06 0.09 -0.21 -0.19
2015 0.22 -0.24 -0.09 0.13 0.23 -0.10 -0.07 -0.23 0.30 0.17 -0.30 -0.10
2016 0.03 0.07 0.04 0.08 -0.14 0.19 0.23 0.19 -0.13 0.48 0.48 -0.06
2017 -0.16 -0.05 -0.06 0.01 -0.09 0.03 -0.11 0.23 -0.30 -0.55 0.63 -0.25
2018 -0.48 0.19 -0.10 0.08 -0.31 0.04 -0.16 0.05 -0.55 0.50 -0.34 0.04
2019 -0.11 -0.23 0.22 -0.25 0.14 -0.18 -0.04 -0.39 0.25
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.64363 -0.25734 -0.06834 0.18104 0.77456
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.056343 0.127784 0.441 0.662
ID -0.003484 0.005568 -0.626 0.535
Residual standard error: 0.3914 on 37 degrees of freedom
Multiple R-squared: 0.01047, Adjusted R-squared: -0.01627
F-statistic: 0.3915 on 1 and 37 DF, p-value: 0.5354
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.15385, p-value = 0.7523
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.3284, p-value = 0.8076
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 3.0219, df = 1, p-value = 0.08215
Box-Ljung test
data: lm_residuals
X-squared = 1.4725, df = 1, p-value = 0.225
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.51350 -0.16679 -0.03218 0.12932 0.66774
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.035373 0.053485 0.661 0.510
ID -0.001239 0.001133 -1.094 0.277
Residual standard error: 0.2385 on 79 degrees of freedom
Multiple R-squared: 0.01491, Adjusted R-squared: 0.002441
F-statistic: 1.196 on 1 and 79 DF, p-value: 0.2775
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 = 2.4445, p-value = 0.9724
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 2.1858, df = 1, p-value = 0.1393
Box-Ljung test
data: lm_residuals
X-squared = 5.1061, df = 1, p-value = 0.02384
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.78669 -0.34716 -0.08195 0.41661 0.81110
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) -0.0186441 0.1202707 -0.155 0.877
ID 0.0007627 0.0034865 0.219 0.828
Residual standard error: 0.456 on 57 degrees of freedom
Multiple R-squared: 0.0008389, Adjusted R-squared: -0.01669
F-statistic: 0.04786 on 1 and 57 DF, p-value: 0.8276
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.23729, p-value = 0.07193
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.6657, p-value = 0.07533
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 10.114, df = 1, p-value = 0.001471
Box-Ljung test
data: lm_residuals
X-squared = 1.5475, df = 1, p-value = 0.2135
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-0.51433 -0.14918 -0.02592 0.11567 0.66655
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0126640 0.0530709 0.239 0.812
ID -0.0008789 0.0011673 -0.753 0.454
Residual standard error: 0.2321 on 76 degrees of freedom
Multiple R-squared: 0.007404, Adjusted R-squared: -0.005656
F-statistic: 0.5669 on 1 and 76 DF, p-value: 0.4538
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.12821, p-value = 0.546
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 2.5312, p-value = 0.9887
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 4.6698, df = 1, p-value = 0.0307
Box-Ljung test
data: lm_residuals
X-squared = 6.2207, df = 1, p-value = 0.01263