A precomputed bootstrap distribution of the coefficients of a model used in the vignette.
modpls.boot3Format
a class boot object
References
Régression Bêta PLS. (French) [PLS Beta regression.],
F. Bertrand, N. Meyer, M. Beau-Faller, K. El Bayed, N. Izzie-J.,
M. Maumy-Bertrand, (2013), J. SFdS, 154(3):143-159
Partial Least Squares Regression for Beta Regression Models.
F. Bertrand, M. Maumy (2021). useR! 2021, Zurich.
Examples
data(modpls.boot3)
#> Warning: data set ‘modpls.boot3’ not found
str(modpls.boot3)
#> List of 11
#> $ t0 : num [1:180, 1] -0.7407 0.01442 0.02374 0.02421 0.00622 ...
#> ..- attr(*, "dimnames")=List of 2
#> .. ..$ : chr [1:180] "Intercept" "X4.69499969" "X4.68499947" "X4.67499971" ...
#> .. ..$ : NULL
#> $ t : num [1:250, 1:180] -0.995 -0.55 -1.067 -0.924 -0.451 ...
#> $ R : int 250
#> $ data :'data.frame': 80 obs. of 180 variables:
#> ..$ y : num [1:80] 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 ...
#> ..$ X4.69499969: num [1:80] 8.99e-05 -8.83e-05 -1.38e-05 7.74e-04 -1.48e-05 ...
#> ..$ X4.68499947: num [1:80] 8.54e-05 -9.43e-05 9.67e-06 7.21e-04 -1.08e-04 ...
#> ..$ X4.67499971: num [1:80] 1.50e-04 -8.04e-05 8.10e-05 8.56e-04 -1.12e-04 ...
#> ..$ X4.66499949: num [1:80] 3.59e-04 -3.75e-05 2.44e-04 1.30e-03 1.60e-04 ...
#> ..$ X4.65499973: num [1:80] 0.000858 0.00017 0.00061 0.00421 0.002897 ...
#> ..$ X4.6449995 : num [1:80] 3.87e-04 3.59e-05 2.61e-04 3.05e-03 1.55e-03 ...
#> ..$ X4.63499975: num [1:80] 0.000596 0.000147 0.000641 0.002869 0.001939 ...
#> ..$ X4.62499952: num [1:80] 2.19e-04 -1.03e-05 1.45e-04 8.88e-04 2.46e-04 ...
#> ..$ X4.61499977: num [1:80] 2.30e-04 -2.13e-05 1.97e-04 7.91e-04 1.04e-04 ...
#> ..$ X4.60499954: num [1:80] 2.72e-04 1.92e-05 4.53e-04 8.31e-04 2.37e-04 ...
#> ..$ X4.59499979: num [1:80] 4.90e-04 9.56e-05 9.26e-04 1.30e-03 8.26e-04 ...
#> ..$ X4.58499956: num [1:80] 0.00092 0.000286 0.001638 0.001838 0.001668 ...
#> ..$ X4.57499981: num [1:80] 0.001012 0.000348 0.001851 0.002019 0.001903 ...
#> ..$ X4.56499958: num [1:80] 0.000713 0.000218 0.001074 0.001364 0.001047 ...
#> ..$ X4.55499983: num [1:80] 3.83e-04 4.46e-05 3.68e-04 7.45e-04 2.24e-04 ...
#> ..$ X4.5449996 : num [1:80] 2.79e-04 -2.30e-05 2.23e-04 5.12e-04 5.82e-05 ...
#> ..$ X4.53499985: num [1:80] 2.15e-04 -3.79e-05 2.37e-04 4.67e-04 -8.30e-07 ...
#> ..$ X4.52499962: num [1:80] 0.000966 0.000245 0.001627 0.00247 0.001954 ...
#> ..$ X4.51499987: num [1:80] 0.001216 0.000362 0.001684 0.001861 0.001258 ...
#> ..$ X4.50499964: num [1:80] 3.02e-04 2.53e-05 3.19e-04 7.99e-04 1.61e-04 ...
#> ..$ X4.49499989: num [1:80] 3.15e-04 3.95e-06 2.30e-04 6.48e-04 1.98e-05 ...
#> ..$ X4.48499966: num [1:80] 3.01e-04 1.65e-05 3.41e-04 5.78e-04 1.67e-04 ...
#> ..$ X4.4749999 : num [1:80] 3.67e-04 2.14e-05 2.67e-04 6.50e-04 1.92e-04 ...
#> ..$ X4.46499968: num [1:80] 4.10e-04 1.26e-05 2.87e-04 6.40e-04 7.65e-05 ...
#> ..$ X4.45499992: num [1:80] 3.75e-04 3.56e-05 4.47e-04 7.15e-04 1.92e-04 ...
#> ..$ X4.44499969: num [1:80] 5.34e-04 8.22e-05 5.52e-04 8.56e-04 4.96e-04 ...
#> ..$ X4.43499947: num [1:80] 0.000661 0.000124 0.000612 0.000984 0.000617 ...
#> ..$ X4.42499971: num [1:80] 0.000582 0.00013 0.000809 0.001099 0.000516 ...
#> ..$ X4.41499949: num [1:80] 0.000554 0.000158 0.000919 0.001172 0.000603 ...
#> ..$ X4.40499973: num [1:80] 0.000527 0.000138 0.000954 0.001048 0.000667 ...
#> ..$ X4.3949995 : num [1:80] 0.000559 0.000119 0.000974 0.000949 0.000563 ...
#> ..$ X4.38499975: num [1:80] 0.000615 0.000165 0.001093 0.001322 0.000648 ...
#> ..$ X4.37499952: num [1:80] 0.000751 0.000234 0.001365 0.00197 0.000956 ...
#> ..$ X4.36499977: num [1:80] 0.000768 0.000234 0.001271 0.001762 0.000851 ...
#> ..$ X4.35499954: num [1:80] 0.000808 0.000213 0.001216 0.001665 0.000708 ...
#> ..$ X4.34499979: num [1:80] 0.001221 0.000331 0.001931 0.002355 0.001624 ...
#> ..$ X4.33499956: num [1:80] 0.001829 0.000502 0.003084 0.003697 0.003243 ...
#> ..$ X4.32499981: num [1:80] 0.002211 0.000722 0.004042 0.004747 0.004498 ...
#> ..$ X4.31499958: num [1:80] 0.001843 0.000609 0.0034 0.003802 0.003518 ...
#> ..$ X4.30499983: num [1:80] 0.001308 0.000529 0.002397 0.002966 0.00229 ...
#> ..$ X4.2949996 : num [1:80] 0.00101 0.00039 0.00173 0.00208 0.00141 ...
#> ..$ X4.28499985: num [1:80] 0.0011 0.00039 0.00185 0.00213 0.00143 ...
#> ..$ X4.27499962: num [1:80] 0.001184 0.000436 0.002059 0.002134 0.001581 ...
#> ..$ X4.26499987: num [1:80] 0.001126 0.000454 0.002035 0.002173 0.001327 ...
#> ..$ X4.25499964: num [1:80] 0.001059 0.000412 0.001895 0.001904 0.001288 ...
#> ..$ X4.24499989: num [1:80] 0.000899 0.000283 0.001539 0.001531 0.000918 ...
#> ..$ X4.23499966: num [1:80] 0.0008 0.000187 0.001201 0.001265 0.000575 ...
#> ..$ X4.2249999 : num [1:80] 0.000762 0.000131 0.001096 0.001066 0.000399 ...
#> ..$ X4.21499968: num [1:80] 0.000711 0.000108 0.000945 0.00112 0.000334 ...
#> ..$ X4.20499992: num [1:80] 0.000693 0.000111 0.000945 0.001135 0.000223 ...
#> ..$ X4.19499969: num [1:80] 0.000804 0.000172 0.00164 0.001528 0.000459 ...
#> ..$ X4.18499994: num [1:80] 0.001246 0.000522 0.003401 0.002819 0.001436 ...
#> ..$ X4.17499971: num [1:80] 0.00214 0.00108 0.00545 0.0044 0.00308 ...
#> ..$ X4.16499949: num [1:80] 0.00279 0.00138 0.00529 0.00655 0.00422 ...
#> ..$ X4.15499973: num [1:80] 0.00251 0.00101 0.00365 0.00668 0.00348 ...
#> ..$ X4.1449995 : num [1:80] 0.00371 0.00147 0.00797 0.00822 0.00499 ...
#> ..$ X4.13499975: num [1:80] 0.00573 0.00211 0.01354 0.01176 0.00862 ...
#> ..$ X4.12499952: num [1:80] 0.00593 0.00268 0.01487 0.01133 0.00941 ...
#> ..$ X4.11499977: num [1:80] 0.00808 0.0038 0.01942 0.01456 0.01432 ...
#> ..$ X4.10499954: num [1:80] 0.00405 0.00158 0.00821 0.00709 0.00651 ...
#> ..$ X4.09499979: num [1:80] 0.002255 0.000585 0.003045 0.002778 0.002261 ...
#> ..$ X4.08499956: num [1:80] 0.002157 0.000229 0.001354 0.001741 0.000784 ...
#> ..$ X4.07499981: num [1:80] 0.003341 0.000475 0.00207 0.002829 0.001476 ...
#> ..$ X4.06499958: num [1:80] 0.00594 0.00129 0.00587 0.00846 0.00733 ...
#> ..$ X4.05499983: num [1:80] 0.01216 0.00299 0.01732 0.01715 0.01925 ...
#> ..$ X4.0449996 : num [1:80] 0.00717 0.00108 0.00794 0.00597 0.0066 ...
#> ..$ X4.03499985: num [1:80] 0.00417 0.000357 0.002302 0.002532 0.001724 ...
#> ..$ X4.02499962: num [1:80] 0.003417 0.000364 0.002225 0.002955 0.001875 ...
#> ..$ X4.01499987: num [1:80] 0.002721 0.000293 0.002024 0.002641 0.00155 ...
#> ..$ X4.00499964: num [1:80] 0.002934 0.000441 0.002968 0.003111 0.001966 ...
#> ..$ X3.99499965: num [1:80] 0.00434 0.00137 0.00744 0.0067 0.0066 ...
#> ..$ X3.98499966: num [1:80] 0.00566 0.0024 0.0119 0.01158 0.01207 ...
#> ..$ X3.97499967: num [1:80] 0.00707 0.00324 0.01267 0.01634 0.01684 ...
#> ..$ X3.96499968: num [1:80] 0.00563 0.00235 0.00826 0.01258 0.0123 ...
#> ..$ X3.95499969: num [1:80] 0.00376 0.00117 0.00412 0.00751 0.00702 ...
#> ..$ X3.94499969: num [1:80] 0.002652 0.000628 0.004445 0.00498 0.004357 ...
#> ..$ X3.9349997 : num [1:80] 0.00655 0.00281 0.02079 0.01522 0.01211 ...
#> ..$ X3.92499971: num [1:80] 0.00363 0.00123 0.00905 0.00718 0.00681 ...
#> ..$ X3.91499972: num [1:80] 0.002792 0.000865 0.004798 0.006672 0.006196 ...
#> ..$ X3.90499973: num [1:80] 0.002578 0.000781 0.003784 0.004664 0.004461 ...
#> ..$ X3.89499974: num [1:80] 0.002639 0.000759 0.003503 0.005601 0.005141 ...
#> ..$ X3.88499975: num [1:80] 0.002802 0.000867 0.003552 0.005681 0.005107 ...
#> ..$ X3.87499976: num [1:80] 0.002679 0.000654 0.003415 0.004034 0.003941 ...
#> ..$ X3.86499977: num [1:80] 0.002779 0.000804 0.003319 0.003711 0.003696 ...
#> ..$ X3.85499978: num [1:80] 0.00341 0.00178 0.00348 0.00454 0.00436 ...
#> ..$ X3.84499979: num [1:80] 0.00402 0.00207 0.00397 0.0048 0.00475 ...
#> ..$ X3.8349998 : num [1:80] 0.00329 0.00104 0.00372 0.00594 0.00538 ...
#> ..$ X3.82499981: num [1:80] 0.002469 0.000598 0.002882 0.005108 0.003755 ...
#> ..$ X3.81499982: num [1:80] 0.001844 0.000403 0.002334 0.003874 0.002338 ...
#> ..$ X3.80499983: num [1:80] 0.001687 0.000349 0.002409 0.002988 0.001682 ...
#> ..$ X3.7949996 : num [1:80] 0.002887 0.000936 0.004881 0.005173 0.004458 ...
#> ..$ X3.78499961: num [1:80] 0.0058 0.00254 0.01103 0.01143 0.01135 ...
#> ..$ X3.77499962: num [1:80] 0.00786 0.00373 0.01485 0.01407 0.01538 ...
#> ..$ X3.76499963: num [1:80] 0.00625 0.00324 0.01118 0.00987 0.01087 ...
#> ..$ X3.75499964: num [1:80] 0.00663 0.00408 0.00789 0.00782 0.00823 ...
#> ..$ X3.74499965: num [1:80] 0.0099 0.00765 0.00661 0.00757 0.00722 ...
#> ..$ X3.73499966: num [1:80] 0.01079 0.00887 0.0045 0.00583 0.00477 ...
#> ..$ X3.72499967: num [1:80] 0.01506 0.01546 0.00503 0.00496 0.00387 ...
#> .. [list output truncated]
#> $ seed : int [1:626] 403 624 1638542565 108172386 -1884566405 -1838154368 -250773631 919185230 -1001918601 -1002779316 ...
#> $ statistic:function (dataset, ind, nt, modele, family = NULL, method = "logistic",
#> link = NULL, link.phi = NULL, type = "ML")
#> $ sim : chr "ordinary"
#> $ call : language boot(data = dataset, statistic = coefs.plsRbeta, R = 250L, sim = sim, stype = stype, nt = nt, modele = model| __truncated__ ...
#> $ stype : chr "i"
#> $ strata : num [1:80] 1 1 1 1 1 1 1 1 1 1 ...
#> $ weights : num [1:80] 0.0125 0.0125 0.0125 0.0125 0.0125 0.0125 0.0125 0.0125 0.0125 0.0125 ...
#> - attr(*, "class")= chr "boot"
plot(modpls.boot3)
