I am trying to capture certain parts of the output from the ur.ls function I got from the GitHub.
The code that I am using is:
my_test <- ur.ls(y=mydf$x, model = "break", breaks = 2, lags = maxlag, method = "GTOS",pn = 0.1, print.results = "print" )
print(my_test)
Which gives the following output:
[[1]]
[[1]]$`t-stat`
[1] -5.529869
[[1]]$`First break`
[1] 35
[[1]]$`Second break`
[1] 55
[[1]]$Runtime
Time difference of 0.07702468 mins
[[2]]
Call:
lm(formula = y.diff ~ 0 + lagmatrix(S.tilde, 1)[, -1] + datmat[,
2:(slag + 2)] + DTt.diff)
Residuals:
Min 1Q Median 3Q Max
-15.1301 -1.7312 0.0684 1.8045 10.3472
Coefficients: (1 not defined because of singularities)
Estimate Std. Error t value Pr(>|t|)
lagmatrix(S.tilde, 1)[, -1] -0.23512 0.04252 -5.530 5.71e-07 ***
datmat[, 2:(slag + 2)]NoLags NA NA NA NA
datmat[, 2:(slag + 2)]S.tilde.diff.l1 0.21258 0.09923 2.142 0.035797 *
datmat[, 2:(slag + 2)]S.tilde.diff.l2 0.29349 0.10449 2.809 0.006509 **
datmat[, 2:(slag + 2)]S.tilde.diff.l3 0.45070 0.11026 4.088 0.000119 ***
datmat[, 2:(slag + 2)]S.tilde.diff.l4 0.21321 0.13451 1.585 0.117662
datmat[, 2:(slag + 2)]S.tilde.diff.l5 -0.10950 0.11104 -0.986 0.327638
datmat[, 2:(slag + 2)]S.tilde.diff.l6 -0.26316 0.11047 -2.382 0.020050 *
DTt.diff1 -3.48648 1.16726 -2.987 0.003934 **
DTt.diff2 -11.06934 5.14490 -2.152 0.035044 *
DTt.diff3 11.16147 2.60165 4.290 5.87e-05 ***
DTt.diff4 9.94658 5.91986 1.680 0.097575 .
DTt.diff5 -11.26274 2.10680 -5.346 1.17e-06 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 4.34 on 67 degrees of freedom
(7 observations deleted due to missingness)
Multiple R-squared: 0.6446, Adjusted R-squared: 0.5809
F-statistic: 10.13 on 12 and 67 DF, p-value: 5.789e-11
I am trying to capture the following information from the output:
Of course, this could be done manually using:
tstat<- c(-5.529869)
break1<-c(35)
break2<-c(55)
estimate<-c(-0.23512)
nlag<- c(6)
nbreak<- c(2)
But an issue is that I need to do several scores of these tests, so this is not very practical.
I first tried to capture the coefficients with tidy using broom package which usually works pretty well, but in this case tidy package simply does not recognize the output. That is when I try to apply it I get:
tidy(my_test)
Error: No tidy method recognized for this list.
After that I managed to find an approach that sort of works but only for capturing the t-statitics:
tstat<- c(as.numeric(substring((capture.output(print(my_test))[3]),5)))
In principle I could apply this to other things I need to capture but problem is that everything in the printed output moves up or down depending on whether I use 1 or 2 breaks and in addition number of lags keeps changing. The only two things that do not change their place are t-stat at the beginning and first break. Position of everything else changes when there is switch from two to one break, or depending on the number of lags.
Consequently, I am looking for some way how the output from the above test could be dynamically captured even when the positions are changing. It does not necessarily need to be done by capture.output function - that was just only thing that I managed to make work.
dput for my_test:
list(list(`t-stat` = -5.52986939989444, `First break` = 35, `Second break` = 55,
Runtime = structure(0.243574384848277, class = "difftime", units = "mins")),
structure(list(call = lm(formula = y.diff ~ 0 + lagmatrix(S.tilde,
1)[, -1] + datmat[, 2:(slag + 2)] + DTt.diff), terms = y.diff ~
0 + lagmatrix(S.tilde, 1)[, -1] + datmat[, 2:(slag +
2)] + DTt.diff, residuals = c(`8` = 0.872355573916085,
`9` = -0.697717191898609, `10` = -1.2862848943206, `11` = 0.320933377794575,
`12` = -2.40645214393101, `13` = 2.39038766132493, `14` = 1.153249843184,
`15` = -0.39800522090757, `16` = -0.217625238730097, `17` = -2.24998945123775,
`18` = -1.86235465631137, `19` = 1.52748936990644, `20` = 0.722105553225127,
`21` = 1.6896236096191, `22` = 1.21756654083507, `23` = -2.2737081032416,
`24` = -0.0555189856184707, `25` = -1.32745447769992, `26` = -2.69191851601456,
`27` = 0.450323241676394, `28` = -0.619946732648159, `29` = 0.0684171523027832,
`30` = 1.36501867693609, `31` = 7.01636358940376, `32` = 7.45606136222332,
`33` = -0.0603699574229863, `34` = -7.06134338379436, `35` = -3.04120659857061,
`36` = 1.87843876200867e-16, `37` = -1.56067141954618, `38` = -3.98995837788732,
`39` = -2.64034463279261, `40` = 2.46318877060907, `41` = -0.0946579433877879,
`42` = -0.00627968340149751, `43` = -1.12994022351662, `44` = 3.87981944634356,
`45` = 3.3557912879781, `46` = 9.63244802758174, `47` = 5.24100528509744,
`48` = -1.60009293145095, `49` = -5.2376819302277, `50` = -9.38754075959704,
`51` = 10.3471769906691, `52` = -12.1568213639348, `53` = 0.85133551132459,
`54` = 2.24952813266479, `55` = -0.216304186525884, `56` = -3.97245045306514e-16,
`57` = 2.71150736214547, `58` = -3.66810792780268, `59` = 0.358219488791779,
`60` = 1.56109333234247, `61` = -0.753216017616136, `62` = -15.1300849652179,
`63` = 4.61095601773964, `64` = 1.91940902601647, `65` = -3.09550436133278,
`66` = 2.49107250967601, `67` = 3.82885377877594, `68` = 0.787299241035634,
`69` = -5.65977223850224, `70` = -4.46105368830907, `71` = -2.00896053907376,
`72` = -0.983959541709144, `73` = 0.385499753844272, `74` = 1.38470803882371,
`75` = 0.341275340812954, `76` = 0.228639263368348, `77` = -4.17228901167752,
`78` = 1.63431085026858, `79` = 5.33398073977219, `80` = 4.03952947226404,
`81` = 3.63845224619818, `82` = 0.567342464096198, `83` = 3.13210340972586,
`84` = -0.906695505369889, `85` = 4.99623519164391, `86` = -3.1108437307305
), coefficients = structure(c(-0.23511569792016, 0.21258442578596,
0.293489227268745, 0.450696031637051, 0.213211609782706,
-0.109499991050521, -0.263162801329296, -3.48647692130263,
-11.0693444630996, 11.1614685510626, 9.94657879595707, -11.2627444589128,
0.0425174051894693, 0.0992264489202736, 0.104487280919139,
0.110259125401975, 0.134513214269294, 0.111044998102637,
0.110466070195529, 1.16726401701977, 5.1449023295093, 2.60164949654566,
5.91986223733132, 2.10680207458884, -5.52986939989444, 2.14241694728758,
2.80885122750846, 4.08760753356181, 1.5850607015892, -0.986086657854799,
-2.38229531351562, -2.98687946382877, -2.15151692960425,
4.29015075469706, 1.68020443672368, -5.34589584601145, 5.7066830928081e-07,
0.0357972680393423, 0.00650896518048846, 0.000118991853434715,
0.117661531503541, 0.327638306451416, 0.020050387349118,
0.00393444251065558, 0.0350440626131117, 5.87177198313913e-05,
0.0975747763082409, 1.16724779705709e-06), .Dim = c(12L,
4L), .Dimnames = list(c("lagmatrix(S.tilde, 1)[, -1]", "datmat[, 2:(slag + 2)]S.tilde.diff.l1",
"datmat[, 2:(slag + 2)]S.tilde.diff.l2", "datmat[, 2:(slag + 2)]S.tilde.diff.l3",
"datmat[, 2:(slag + 2)]S.tilde.diff.l4", "datmat[, 2:(slag + 2)]S.tilde.diff.l5",
"datmat[, 2:(slag + 2)]S.tilde.diff.l6", "DTt.diff1", "DTt.diff2",
"DTt.diff3", "DTt.diff4", "DTt.diff5"), c("Estimate", "Std. Error",
"t value", "Pr(>|t|)"))), aliased = c(`lagmatrix(S.tilde, 1)[, -1]` = FALSE,
`datmat[, 2:(slag + 2)]NoLags` = TRUE, `datmat[, 2:(slag + 2)]S.tilde.diff.l1` = FALSE,
`datmat[, 2:(slag + 2)]S.tilde.diff.l2` = FALSE, `datmat[, 2:(slag + 2)]S.tilde.diff.l3` = FALSE,
`datmat[, 2:(slag + 2)]S.tilde.diff.l4` = FALSE, `datmat[, 2:(slag + 2)]S.tilde.diff.l5` = FALSE,
`datmat[, 2:(slag + 2)]S.tilde.diff.l6` = FALSE, DTt.diff1 = FALSE,
DTt.diff2 = FALSE, DTt.diff3 = FALSE, DTt.diff4 = FALSE,
DTt.diff5 = FALSE), sigma = 4.34022853989968, df = c(12L,
67L, 13L), r.squared = 0.644573890970572, adj.r.squared = 0.580915483383212,
fstatistic = c(value = 10.1255107596904, numdf = 12,
dendf = 67), cov.unscaled = structure(c(9.59639922665142e-05,
2.20580058347817e-05, -1.86765939916722e-05, -6.97933563296721e-05,
-9.18368279866152e-05, -2.74027448794235e-05, -1.08445650048574e-06,
0.00166049760804861, 0.00505585030558691, -0.00497849874276068,
-0.00336957248783249, 0.00332058543538181, 2.20580058347817e-05,
0.000522672561463745, -0.000170134234480263, -0.000136299258433012,
-0.000156683869192449, 3.20741691986199e-05, 0.000109417994668808,
-0.000340545121006471, 0.000835502882418284, -0.00034262796834208,
-0.00311928203169194, 0.00137747915213809, -1.86765939916722e-05,
-0.000170134234480263, 0.000579564343400617, -0.000118662022760285,
-0.000113907761908382, -7.56369903448711e-05, -1.67418563277836e-05,
-0.000673822989020871, 0.00199348470539279, 0.00202854373119897,
-0.00443981226091342, -0.00134400501096897, -6.97933563296721e-05,
-0.000136299258433012, -0.000118662022760285, 0.000645362742765626,
-5.98565469825177e-05, -3.8229997405084e-05, -0.000146569197018866,
-0.00144027001250464, -0.00434693403705934, 0.004657498011182,
0.00200435070362651, -0.00352774302397917, -9.18368279866152e-05,
-0.000156683869192449, -0.000113907761908382, -5.98565469825177e-05,
0.000960516222555618, -0.000232668650784361, 2.61183442453487e-05,
-0.00216702563816879, -0.010485401200229, 0.00424329320154643,
0.0246863500668702, -0.00150724670465891, -2.74027448794235e-05,
3.20741691986199e-05, -7.56369903448711e-05, -3.8229997405084e-05,
-0.000232668650784361, 0.000654595183149194, -0.000227073038814052,
-0.00050839722994379, -0.00414193034888211, 0.0012164182953312,
-0.0101302132850535, -0.000174392386630977, -1.08445650048574e-06,
0.000109417994668808, -1.67418563277836e-05, -0.000146569197018866,
2.61183442453487e-05, -0.000227073038814052, 0.000647787572328266,
-0.000832648885600449, 0.00184942667154017, -0.00111837128659685,
0.0101221919879007, 0.00341776474899047, 0.00166049760804861,
-0.000340545121006471, -0.000673822989020871, -0.00144027001250464,
-0.00216702563816879, -0.00050839722994379, -0.000832648885600449,
0.0723290896245352, 0.099047414012332, -0.126717608042948,
-0.0879683442319499, 0.0467983613397516, 0.00505585030558691,
0.000835502882418284, 0.00199348470539279, -0.00434693403705934,
-0.010485401200229, -0.00414193034888211, 0.00184942667154017,
0.099047414012332, 1.40517065730678, -0.317384545601921,
-0.294134124076671, 0.205736990719251, -0.00497849874276068,
-0.00034262796834208, 0.00202854373119897, 0.004657498011182,
0.00424329320154643, 0.0012164182953312, -0.00111837128659685,
-0.126717608042948, -0.317384545601921, 0.359312541483163,
0.15130744081174, -0.232250025264234, -0.00336957248783249,
-0.00311928203169194, -0.00443981226091342, 0.00200435070362651,
0.0246863500668702, -0.0101302132850535, 0.0101221919879007,
-0.0879683442319499, -0.294134124076671, 0.15130744081174,
1.86036432914864, -0.0614605342855884, 0.00332058543538181,
0.00137747915213809, -0.00134400501096897, -0.00352774302397917,
-0.00150724670465891, -0.000174392386630977, 0.00341776474899047,
0.0467983613397516, 0.205736990719251, -0.232250025264234,
-0.0614605342855884, 0.235625493888645), .Dim = c(12L,
12L), .Dimnames = list(c("lagmatrix(S.tilde, 1)[, -1]",
"datmat[, 2:(slag + 2)]S.tilde.diff.l1", "datmat[, 2:(slag + 2)]S.tilde.diff.l2",
"datmat[, 2:(slag + 2)]S.tilde.diff.l3", "datmat[, 2:(slag + 2)]S.tilde.diff.l4",
"datmat[, 2:(slag + 2)]S.tilde.diff.l5", "datmat[, 2:(slag + 2)]S.tilde.diff.l6",
"DTt.diff1", "DTt.diff2", "DTt.diff3", "DTt.diff4", "DTt.diff5"
), c("lagmatrix(S.tilde, 1)[, -1]", "datmat[, 2:(slag + 2)]S.tilde.diff.l1",
"datmat[, 2:(slag + 2)]S.tilde.diff.l2", "datmat[, 2:(slag + 2)]S.tilde.diff.l3",
"datmat[, 2:(slag + 2)]S.tilde.diff.l4", "datmat[, 2:(slag + 2)]S.tilde.diff.l5",
"datmat[, 2:(slag + 2)]S.tilde.diff.l6", "DTt.diff1",
"DTt.diff2", "DTt.diff3", "DTt.diff4", "DTt.diff5"))),
na.action = structure(1:7, .Names = c("1", "2", "3",
"4", "5", "6", "7"), class = "omit")), class = "summary.lm"))
This is mainly a subsetting problem.
tstat = my_test[[1L]][['t-stat']]
## breaks ##
break_names = endsWith(names(my_test[[1L]]), 'break')
nbreak = sum(break_names)
for (i in seq_len(nbreak)) { ## note, I would assign breaks to a list: breaks = my_test[[1L]][break_names]
assign(paste0('break', i), my_test[[1L]][[i + 1L]])
}
estimate = my_test[[2L]][['coefficients']][1L, 1L]
txt = row.names(my_test[[2L]][['coefficients']])
nlag = max(as.integer(regmatches(txt, regexpr("\\d*$", txt))), na.rm = TRUE)
The only uncertain part is the nlag. It is fragile right now as I am unsure of the rules that it would follow. But for this dataset, it matches OP request.