Last updated on 2020-01-27 00:48:07 CET.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.1-1 | 2.75 | 38.68 | 41.43 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.1-1 | 2.38 | 27.11 | 29.49 | ERROR | |
| r-devel-linux-x86_64-fedora-clang | 1.1-1 | 51.92 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.1-1 | 50.93 | OK | |||
| r-devel-windows-ix86+x86_64 | 1.1-1 | 10.00 | 88.00 | 98.00 | OK | |
| r-devel-windows-ix86+x86_64-gcc8 | 1.1-1 | 9.00 | 83.00 | 92.00 | OK | |
| r-patched-linux-x86_64 | 1.1-1 | 2.34 | 36.43 | 38.77 | OK | |
| r-patched-solaris-x86 | 1.1-1 | 79.50 | OK | |||
| r-release-linux-x86_64 | 1.1-1 | 2.47 | 36.38 | 38.85 | OK | |
| r-release-windows-ix86+x86_64 | 1.1-1 | 5.00 | 64.00 | 69.00 | OK | |
| r-release-osx-x86_64 | 1.1-1 | OK | ||||
| r-oldrel-windows-ix86+x86_64 | 1.1-1 | 4.00 | 80.00 | 84.00 | OK | |
| r-oldrel-osx-x86_64 | 1.1-1 | OK |
Version: 1.1-1
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘sfsmisc’
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.1-1
Check: examples
Result: ERROR
Running examples in ‘longmemo-Ex.R’ failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: WhittleEst
> ### Title: Whittle Estimator for Fractional Gaussian Noise / Fractional
> ### ARIMA
> ### Aliases: WhittleEst print.WhittleEst nobs nobs.WhittleEst
> ### Keywords: ts
>
> ### ** Examples
>
> data(NileMin)
> (f.Gn.N <- WhittleEst(NileMin)) # H = 0.837
'WhittleEst' Whittle estimator for fractional Gaussian noise ('fGn'); call:
WhittleEst(x = NileMin)
time series of length n = 663.
H = 0.8374209
coefficients 'eta' =
Estimate Std. Error z value Pr(>|z|)
H 0.83742094 0.02602955 32.17193 < 2.22e-16
<==> d := H - 1/2 = 0.337 (0.026)
$ vcov : num [1, 1] 0.000678
..- attr(*, "dimnames")=List of 2
.. ..$ : chr "H"
.. ..$ : chr "H"
$ periodogr.x: num [1:331] 56564 5379 52555 1098 2916 ...
$ spec : num [1:331] 22306 13972 10627 8752 7528 ...
> (f.A00.N <- WhittleEst(NileMin, model = "fARIMA", p=0, q=0)) # H = 0.899
'WhittleEst' Whittle estimator for fractional ARIMA ('fARIMA'); call:
WhittleEst(x = NileMin, model = "fARIMA", p = 0, q = 0)
ARMA order (p=0, q=0); time series of length n = 663.
H = 0.8991688
coefficients 'eta' =
Estimate Std. Error z value Pr(>|z|)
H 0.89916883 0.03044038 29.53869 < 2.22e-16
<==> d := H - 1/2 = 0.399 (0.03)
$ vcov : num [1, 1] 0.000927
..- attr(*, "dimnames")=List of 2
.. ..$ : chr "H"
.. ..$ : chr "H"
$ periodogr.x: num [1:331] 56564 5379 52555 1098 2916 ...
$ spec : num [1:331] 32127 18473 13365 10623 8890 ...
> confint(f.Gn.N)
2.5 % 97.5 %
H 0.786404 0.8884379
> confint(f.A00.N)
2.5 % 97.5 %
H 0.8395068 0.9588309
>
> data(videoVBR)
> (f.GN <- WhittleEst(videoVBR))
'WhittleEst' Whittle estimator for fractional Gaussian noise ('fGn'); call:
WhittleEst(x = videoVBR)
time series of length n = 1000.
H = 0.9899496
coefficients 'eta' =
Estimate Std. Error z value Pr(>|z|)
H 0.98994955 0.02150389 46.03584 < 2.22e-16
<==> d := H - 1/2 = 0.49 (0.022)
$ vcov : num [1, 1] 0.000462
..- attr(*, "dimnames")=List of 2
.. ..$ : chr "H"
.. ..$ : chr "H"
$ periodogr.x: num [1:499] 5145 22812 40031 7476 33737 ...
$ spec : num [1:499] 16986 8612 5788 4366 3509 ...
>
> ## similar {but faster !}:
> (f.am00 <- WhittleEst(videoVBR, model = "fARIMA", p=0, q=0))
'WhittleEst' Whittle estimator for fractional ARIMA ('fARIMA'); call:
WhittleEst(x = videoVBR, model = "fARIMA", p = 0, q = 0)
ARMA order (p=0, q=0); time series of length n = 1000.
H = 0.9899576
coefficients 'eta' =
Estimate Std. Error z value Pr(>|z|)
H 0.98995757 0.02478602 39.94015 < 2.22e-16
<==> d := H - 1/2 = 0.49 (0.025)
$ vcov : num [1, 1] 0.000614
..- attr(*, "dimnames")=List of 2
.. ..$ : chr "H"
.. ..$ : chr "H"
$ periodogr.x: num [1:499] 5145 22812 40031 7476 33737 ...
$ spec : num [1:499] 15814 8018 5389 4065 3267 ...
> rbind(f.am00$coef,
+ f.GN $coef)# really similar
Estimate Std. Error z value Pr(>|z|)
H 0.9899576 0.02478602 39.94015 0
H 0.9899496 0.02150389 46.03584 0
>
> f.am11 <- WhittleEst(videoVBR, model = "fARIMA",
+ start= list(H= .5, AR = .5, MA= .5))
> f.am11
'WhittleEst' Whittle estimator for fractional ARIMA ('fARIMA'); call:
WhittleEst(x = videoVBR, model = "fARIMA", start = list(H = 0.5,
AR = 0.5, MA = 0.5))
ARMA order (p=1, q=1); time series of length n = 1000.
H = 0.950087
coefficients 'eta' =
Estimate Std. Error z value Pr(>|z|)
H 0.95008698 0.09652219 9.84320 < 2.22e-16
AR 0.67345045 0.08513683 7.91021 2.5695e-15
MA 0.29096113 0.04087322 7.11863 1.0901e-12
<==> d := H - 1/2 = 0.45 (0.097)
$ vcov : num [1:3, 1:3] 0.00932 -0.00773 -0.00156 -0.00773 0.00725 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : chr [1:3] "H" "AR" "MA"
.. ..$ : chr [1:3] "H" "AR" "MA"
$ periodogr.x: num [1:499] 5145 22812 40031 7476 33737 ...
$ spec : num [1:499, 1] 67174 35966 24936 19213 15681 ...
> vcov(f.am11)
H AR MA
H 0.009316534 -0.0077260165 -0.0015633632
AR -0.007726017 0.0072482799 0.0006527909
MA -0.001563363 0.0006527909 0.0016706198
>
> op <- if(require("sfsmisc"))
+ mult.fig(3, main = "Whittle Estimators for videoVBR data")$old.par else
+ par(mar = c(3,1), mgp = c(1.5, 0.6, 0), mar = c(4,4,2,1)+.1)
Loading required package: sfsmisc
Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE, :
there is no package called ‘sfsmisc’
Error in par(mar = c(3, 1), mgp = c(1.5, 0.6, 0), mar = c(4, 4, 2, 1) + :
graphical parameter "mar" has the wrong length
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc
Version: 1.1-1
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
...
--- re-building ‘BspecFGN.Rnw’ using Sweave
Loading required package: longmemo
Error: processing vignette 'BspecFGN.Rnw' failed with diagnostics:
chunk 4 (label = curve-fB)
Error in loadNamespace(name) : there is no package called 'sfsmisc'
--- failed re-building 'BspecFGN.Rnw'
SUMMARY: processing the following file failed:
'BspecFGN.Rnw'
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-debian-gcc