Print the cv.ptLasso object.
print.cv.ptLasso.RdPrint the cv.ptLasso object.
Usage
# S3 method for class 'cv.ptLasso'
print(x, ...)Examples
out = gaussian.example.data()
x = out$x; y=out$y; groups = out$group;
cvfit = cv.ptLasso(x, y, groups = groups, family = "gaussian", type.measure = "mse")
print(cvfit)
#>
#> Call:
#> cv.ptLasso(x = x, y = y, groups = groups, family = "gaussian",
#> type.measure = "mse", use.case = "inputGroups", group.intercepts = TRUE)
#>
#>
#>
#> type.measure: mse
#>
#>
#> alpha overall mean wtdMean group_1 group_2 group_3 group_4 group_5
#> Overall 687.5 687.5 687.5 672.6 558.7 557.3 653.6 995.4
#> Pretrain 0.0 536.0 536.0 536.0 529.1 513.9 540.0 564.8 531.9
#> Pretrain 0.1 527.6 527.6 527.6 497.4 504.7 559.1 535.6 541.4
#> Pretrain 0.2 520.1 520.1 520.1 498.7 480.1 560.5 528.8 532.5
#> Pretrain 0.3 522.8 522.8 522.8 490.1 500.0 545.1 521.1 557.7
#> Pretrain 0.4 521.6 521.6 521.6 471.0 470.1 568.6 554.1 544.5
#> Pretrain 0.5 532.0 532.0 532.0 465.1 511.7 569.6 556.4 557.2
#> Pretrain 0.6 528.0 528.0 528.0 465.2 523.9 564.1 537.4 549.4
#> Pretrain 0.7 548.0 548.0 548.0 480.7 551.7 597.7 551.4 558.3
#> Pretrain 0.8 550.1 550.1 550.1 500.1 575.5 572.7 537.0 565.2
#> Pretrain 0.9 549.8 549.8 549.8 531.7 570.2 603.3 497.0 546.9
#> Pretrain 1.0 564.7 564.7 564.7 553.7 563.6 624.6 532.0 549.4
#> Individual 564.7 564.7 564.7 553.7 563.6 624.6 532.0 549.4
#>
#> alphahat (fixed) = 0.2
#> alphahat (varying):
#> group_1 group_2 group_3 group_4 group_5
#> 0.5 0.4 0.0 0.9 0.0