Analysis
[1] "景気動向指数個別系列:先行系列:実質機械受注(製造業)(百万円):内閣府"
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1999 317976
2000 329598 340674 302492 339806 343364 377423 360395 388990 353142 394255 385939 401771
2001 363961 354491 344784 333789 327132 300660 304926 334982 290686 235426 279275 261922
2002 258306 269962 304524 267084 262235 277880 303067 276882 293766 298132 286296 295750
2003 341553 312250 324548 287138 341128 347154 340550 337212 352934 385464 372274 368295
2004 381185 377277 375437 419635 406546 396355 378868 398788 380562 384550 400481 427084
2005 388438 419471 454222 461970 394739 407689 439634 440158 440095 444647 444475 449813
2006 406059 462803 471658 479798 457304 518776 460548 491547 477687 447118 463843 452441
2007 448190 465910 448896 442133 475156 411240 454204 452794 471048 496612 480935 448046
2008 469544 460601 426245 449054 458041 448400 431312 405170 426439 399618 280356 291269
2009 204620 198643 232294 229373 243427 258839 211994 225730 252337 304961 235847 276532
2010 273018 273061 279917 295360 267246 280130 305455 323660 302287 318270 300124 306114
2011 314534 327226 328768 318383 337091 346892 312260 338506 319465 328169 327021 323196
2012 320573 342042 313868 317536 319366 302714 317874 292718 281994 275929 286768 286767
2013 271089 291369 297608 283666 292364 313254 307750 329158 329201 337812 349525 305884
2014 338147 320595 379134 335049 288924 301332 345991 336211 371111 341270 337292 398177
2015 361235 368626 355077 392644 438587 379354 356309 341532 348544 366528 332449 350722
2016 442184 326108 371205 330039 333902 365696 361233 337988 339982 330451 361310 395119
2017 343211 350685 355218 352024 359884 356197 355656 392619 395791 403522 410296 388913
2018 407059 429941 369550 435234 436679 388220 422266 441212 386225 416857 398088 382526
2019 374212 386142 344335 398902 369487 363663 384494 380566 360381
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-57396 -17677 4251 15291 40518
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 291861.0 7562.8 38.592 <0.0000000000000002 ***
ID 691.1 329.5 2.097 0.0429 *
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 23160 on 37 degrees of freedom
Multiple R-squared: 0.1062, Adjusted R-squared: 0.08208
F-statistic: 4.398 on 1 and 37 DF, p-value: 0.04287
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 = 0.78581, p-value = 0.000004034
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.0049739, df = 1, p-value = 0.9438
Box-Ljung test
data: lm_residuals
X-squared = 14.026, df = 1, p-value = 0.0001803
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-53411 -21889 -3624 17579 90760
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 316356.3 6640.6 47.640 < 0.0000000000000002 ***
ID 1085.2 140.7 7.713 0.0000000000315 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 29610 on 79 degrees of freedom
Multiple R-squared: 0.4296, Adjusted R-squared: 0.4223
F-statistic: 59.49 on 1 and 79 DF, p-value: 0.00000000003151
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.074074, p-value = 0.9806
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.2984, p-value = 0.0003482
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.0071798, df = 1, p-value = 0.9325
Box-Ljung test
data: lm_residuals
X-squared = 8.6814, df = 1, p-value = 0.003215
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-111782 -28867 -136 21269 145057
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 313267.9 14517.3 21.579 <0.0000000000000002 ***
ID -284.3 420.8 -0.676 0.502
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 55050 on 57 degrees of freedom
Multiple R-squared: 0.007944, Adjusted R-squared: -0.009461
F-statistic: 0.4564 on 1 and 57 DF, p-value: 0.502
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.10169, p-value = 0.9239
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 0.27632, p-value < 0.00000000000000022
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 27.786, df = 1, p-value = 0.0000001355
Box-Ljung test
data: lm_residuals
X-squared = 39.805, df = 1, p-value = 0.0000000002806
Call:
lm(formula = value ~ ID)
Residuals:
Min 1Q Median 3Q Max
-51436 -20408 -3294 16578 88206
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 324725.2 6706.1 48.42 < 0.0000000000000002 ***
ID 986.7 147.5 6.69 0.00000000335 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 29330 on 76 degrees of freedom
Multiple R-squared: 0.3706, Adjusted R-squared: 0.3623
F-statistic: 44.75 on 1 and 76 DF, p-value: 0.000000003351
Two-sample Kolmogorov-Smirnov test
data: lm_residuals and rnorm(n = length(lm_residuals), mean = 0, sd = sd(lm_residuals))
D = 0.089744, p-value = 0.9147
alternative hypothesis: two-sided
Durbin-Watson test
data: value ~ ID
DW = 1.3657, p-value = 0.001324
alternative hypothesis: true autocorrelation is greater than 0
studentized Breusch-Pagan test
data: value ~ ID
BP = 0.0058166, df = 1, p-value = 0.9392
Box-Ljung test
data: lm_residuals
X-squared = 6.8422, df = 1, p-value = 0.008903
