Analysis
[1] "機械受注統計調査:非製造業業種別受注額(季調系列・月次)(単位:億円):不動産業:内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2005 37.12 39.19 38.42 52.86 40.10 32.30 27.96 38.64 37.30
2006 30.33 47.40 31.52 43.77 35.62 85.06 35.35 24.28 36.15 48.22 43.35 45.77
2007 59.21 31.37 28.76 44.76 47.42 43.88 31.96 39.19 42.23 40.51 34.63 30.07
2008 27.31 34.62 46.57 37.20 38.93 35.93 37.01 33.83 42.86 35.80 20.54 48.15
2009 97.53 42.83 44.58 23.95 35.59 31.88 28.62 23.92 29.88 27.77 23.21 21.85
2010 18.27 33.29 23.67 28.13 16.54 29.63 28.31 36.17 27.59 30.22 34.52 30.57
2011 45.95 27.81 21.66 28.10 29.71 23.78 38.51 36.79 27.94 28.34 29.64 24.35
2012 28.48 30.36 37.64 32.89 37.02 29.67 26.60 23.28 31.17 31.16 38.54 42.18
2013 33.24 37.15 43.80 35.45 33.35 39.43 39.74 54.17 32.15 53.39 54.90 50.37
2014 39.30 35.46 30.59 56.29 67.69 60.74 56.14 61.86 60.50 45.71 28.89 42.42
2015 36.41 86.19 49.12 117.06 37.00 55.33 56.38 45.65 49.98 56.34 53.47 53.81
2016 56.00 50.65 58.22 59.13 61.27 46.62 49.65 33.62 56.42 47.14 48.96 47.04
2017 65.13 44.69 55.73 38.63 41.82 48.83 40.85 56.07 54.04 54.08 42.09 54.77
2018 111.99 54.63 49.72 42.96 53.03 45.18 47.31 41.17 42.73 37.51 54.60 49.70
2019 45.78 51.51 51.51 72.48 47.29 93.31 58.37 63.98 44.25
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-10.668 -2.950 -1.325 3.441 17.029
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 25.49459 1.90380 13.391 0.000000000000000923 ***
ID 0.21413 0.08296 2.581 0.0139 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 5.831 on 37 degrees of freedom
Multiple R-squared: 0.1526, Adjusted R-squared: 0.1297
F-statistic: 6.663 on 1 and 37 DF, p-value: 0.01394
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 = 0.9114
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.7341, p-value = 0.1551
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.032408, df = 1, p-value = 0.8571
Box-Ljung test
data: lm_residuals
X-squared = 0.45201, df = 1, p-value = 0.5014
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-20.156 -9.388 -2.677 5.882 67.372
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 46.09207 3.32205 13.875 <0.0000000000000002 ***
ID 0.12842 0.07039 1.824 0.0719 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.81 on 79 degrees of freedom
Multiple R-squared: 0.04043, Adjusted R-squared: 0.02829
F-statistic: 3.329 on 1 and 79 DF, p-value: 0.07186
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 = 1.9382, p-value = 0.3467
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.012696, df = 1, p-value = 0.9103
Box-Ljung test
data: lm_residuals
X-squared = 0.039564, df = 1, p-value = 0.8423
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-16.574 -5.120 -1.863 3.496 62.983
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 35.35278 2.92797 12.074 <0.0000000000000002 ***
ID -0.08954 0.08488 -1.055 0.296
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 11.1 on 57 degrees of freedom
Multiple R-squared: 0.01915, Adjusted R-squared: 0.001942
F-statistic: 1.113 on 1 and 57 DF, p-value: 0.2959
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.11864, p-value = 0.8052
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.3599, p-value = 0.003703
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 1.8168, df = 1, p-value = 0.1777
Box-Ljung test
data: lm_residuals
X-squared = 5.799, df = 1, p-value = 0.01604
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-20.976 -9.191 -1.713 5.223 66.681
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 47.81198 3.42329 13.967 <0.0000000000000002 ***
ID 0.10270 0.07529 1.364 0.177
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 14.97 on 76 degrees of freedom
Multiple R-squared: 0.02389, Adjusted R-squared: 0.01105
F-statistic: 1.86 on 1 and 76 DF, p-value: 0.1766
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 = 1.9642, p-value = 0.3911
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.00020783, df = 1, p-value = 0.9885
Box-Ljung test
data: lm_residuals
X-squared = 0.0072004, df = 1, p-value = 0.9324