我试图将LASSO回归拟合到我的矩阵中，以提取出有意义的特征。
我应用以下代码：
x_sparse <- x[,-c(1)]
y_sparse <- x[,c(1)]
model <- glmnet(x_sparse, y_sparse, family = "poisson")
是否可以在梯度增强模型中绘制与特征重要性相似的图形？
我想从当前单词列表中预测哪些功能最重要。
我如何将LASSO应用于连续变量，我一直在阅读的有关LASSO的大量文章都将其更多地用于分类。
数据如下：
EXHGKJ 0.8254469 21 15 7 92 31 11 9 6 . 58 39 19 10 57 11 1 13
IUEYRR 0.9957524 33 15 9 91 17 7 18 . 6 86 21 9 21 29 119 6 26
PPOYTA 1.7726538 37 27 25 129 40 30 79 67 91 54 211 18 50 41 109 36 120
QUEYRI 3.7775961 44 3 16 85 71 29 33 . . 97 69 12 15 69 5 21 25
在我有4个EXHGKJ, IUEYRR, PPOYTA, QUEYRI且每个Item具有一个连续变量0.82544, 0.99574, 1.77265, 3.77759的情况下，最后是一个稀疏矩阵，其中包含每个单词对每个Item出现的次数。
我想根据文本/稀疏数据预测词条得分，然后在importance之类的情节中提取最有意义的词/文本。有可能吗？
数据：
new("dgCMatrix", i = c(0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 1L, 2L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 2L, 0L, 1L,
2L, 3L, 0L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L,
2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 2L, 2L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 0L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
1L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 2L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 2L, 3L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 3L, 0L, 1L, 2L, 3L, 1L, 2L,
3L, 0L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 2L, 3L, 0L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 3L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 0L, 1L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 0L,
1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 1L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 2L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 3L, 0L, 1L, 2L, 3L, 1L, 3L, 1L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L,
3L, 3L, 0L, 1L, 2L, 3L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L, 2L,
3L, 0L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 0L, 1L, 2L, 3L, 0L,
1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 0L, 2L, 3L, 0L, 1L,
2L, 3L, 0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L, 2L, 3L, 0L, 1L, 2L, 3L,
0L, 1L, 2L, 3L, 0L, 1L, 2L, 3L), p = c(0L, 4L, 8L, 12L, 16L,
20L, 24L, 28L, 32L, 34L, 36L, 40L, 44L, 48L, 52L, 56L, 60L, 64L,
68L, 72L, 76L, 80L, 84L, 87L, 91L, 95L, 99L, 103L, 106L, 109L,
113L, 117L, 121L, 125L, 129L, 133L, 136L, 140L, 143L, 147L, 151L,
153L, 157L, 160L, 164L, 168L, 172L, 175L, 179L, 182L, 186L, 188L,
192L, 196L, 200L, 204L, 208L, 212L, 215L, 219L, 223L, 227L, 231L,
232L, 236L, 238L, 242L, 246L, 248L, 252L, 256L, 260L, 264L, 268L,
272L, 276L, 280L, 284L, 288L, 292L, 296L, 300L, 304L, 308L, 311L,
315L, 319L, 323L, 326L, 330L, 334L, 338L, 342L, 345L, 348L, 351L,
355L, 356L, 357L, 361L, 365L, 369L, 373L, 377L, 381L, 385L, 387L,
390L, 394L, 398L, 402L, 406L, 410L, 414L, 417L, 420L, 424L, 427L,
431L, 435L, 438L, 442L, 446L, 450L, 454L, 458L, 462L, 466L, 470L,
473L, 477L, 479L, 483L, 487L, 491L, 494L, 498L, 502L, 506L, 508L,
512L, 516L, 517L, 521L, 525L, 529L, 533L, 537L, 541L, 545L, 549L,
553L, 557L, 561L, 565L, 569L, 573L, 576L, 580L, 584L, 588L, 592L,
596L, 600L, 604L, 608L, 612L, 616L, 620L, 622L, 625L, 629L, 633L,
635L, 639L, 643L, 647L, 651L, 654L, 655L, 659L, 663L, 667L, 671L,
675L, 679L, 683L, 687L, 691L, 695L, 699L, 703L, 707L, 711L, 714L,
718L, 722L, 725L, 729L, 730L, 734L, 738L, 740L, 744L, 747L, 750L,
753L, 757L, 761L, 765L, 769L, 772L, 776L, 780L, 782L, 785L, 788L,
792L, 796L, 800L, 804L, 808L, 812L, 816L, 820L, 824L, 828L, 832L,
835L, 839L, 843L, 845L, 848L, 852L, 855L, 859L, 862L, 866L, 869L,
873L, 877L, 880L, 884L, 888L, 892L, 896L, 900L, 904L, 908L, 912L,
913L, 916L, 920L, 924L, 928L, 932L, 936L, 940L, 944L, 948L, 952L,
956L, 960L, 964L, 968L, 972L, 975L, 979L, 983L, 987L, 991L, 995L,
999L, 1001L, 1005L, 1009L, 1013L, 1017L, 1021L, 1025L, 1029L,
1032L, 1034L, 1035L, 1039L, 1043L, 1047L, 1051L, 1055L, 1059L,
1063L, 1067L, 1071L, 1075L, 1079L, 1083L, 1087L, 1091L, 1095L,
1099L, 1103L, 1107L, 1111L, 1115L, 1116L, 1120L, 1124L, 1128L,
1132L, 1136L, 1140L, 1144L, 1148L, 1150L, 1154L, 1158L, 1162L,
1165L, 1169L, 1170L, 1173L, 1177L, 1181L, 1185L, 1189L, 1192L,
1196L, 1199L, 1202L, 1206L, 1209L, 1213L, 1217L, 1219L, 1222L,
1226L, 1227L, 1231L, 1235L, 1239L, 1243L, 1246L, 1250L, 1254L,
1258L, 1262L, 1266L, 1270L, 1274L, 1278L, 1282L, 1286L, 1290L,
1294L, 1298L, 1302L, 1306L, 1310L, 1314L, 1317L, 1321L, 1325L,
1329L, 1333L, 1337L, 1341L, 1345L, 1348L, 1351L, 1355L, 1359L,
1363L, 1367L, 1371L, 1375L, 1379L, 1383L, 1387L, 1391L, 1395L,
1399L, 1403L, 1407L, 1411L, 1415L, 1419L, 1423L, 1427L, 1431L,
1433L, 1437L, 1440L, 1444L, 1447L, 1451L, 1454L, 1458L, 1462L,
1466L, 1470L, 1472L, 1476L, 1480L, 1484L, 1488L, 1492L, 1496L,
1500L, 1504L, 1508L, 1512L, 1516L, 1518L, 1522L, 1526L, 1530L,
1533L, 1537L, 1541L, 1545L, 1549L, 1553L, 1557L, 1561L, 1565L,
1569L, 1573L, 1576L, 1577L, 1581L, 1585L, 1589L, 1593L, 1597L,
1600L, 1604L, 1606L, 1608L, 1612L, 1616L, 1620L, 1623L, 1624L,
1628L, 1631L, 1635L, 1639L, 1643L, 1647L, 1651L, 1655L, 1659L,
1660L, 1664L, 1667L, 1671L, 1673L, 1677L, 1681L, 1685L, 1689L,
1692L, 1696L, 1700L, 1703L, 1707L, 1710L, 1714L, 1717L, 1721L,
1725L, 1729L, 1733L, 1736L, 1740L, 1744L, 1748L, 1750L, 1754L,
1758L, 1762L), Dim = c(4L, 480L), Dimnames = list(c("EXHGKJ",
"IUEYRR", "PPOYTA", "QUEYRI"), c("markups", "accelerated", "accompanying",
"accordance", "accounting", "accounts", "accrued", "accumulated",
"acquire", "acquisitions", "act", "activities", "actual", "addition",
"additional", "adjusted", "adjustment", "adjustments", "administrative",
"adopted", "adoption", "affect", "aggregate", "agreement", "agreements",
"also", "amended", "americas", "among", "amortization", "amount",
"amounts", "analysis", "annual", "anticipated", "appeal", "applicable",
"applied", "approach", "approximately", "arbitration", "arrangements",
"asset", "assets", "associated", "assumptions", "attributable",
"authorized", "available", "average", "award", "balance", "balances",
"based", "basis", "beginning", "believe", "believes", "benefit",
"benefits", "billion", "board", "brokerage", "business", "businesses",
"can", "capital", "card", "carrying", "cash", "certain", "change",
"changes", "charges", "check", "chief", "claims", "commercial",
"commission", "commitments", "common", "companies", "company",
"comparable", "compared", "compensation", "completed", "component",
"components", "comprehensive", "condensed", "condition", "conditions",
"connection", "consideration", "consolidated", "consolidating",
"consulting", "contents", "continued", "continuing", "contract",
"contracts", "control", "controls", "convertible", "core", "corporate",
"corporation", "cost", "costs", "court", "credit", "cumulative",
"currency", "current", "currently", "customer", "customers",
"damages", "data", "date", "debt", "decision", "decrease", "decreased",
"deferred", "defined", "depreciation", "derivative", "derivatives",
"described", "designated", "determined", "development", "diluted",
"disclosure", "disclosures", "discontinued", "discussion", "district",
"divested", "dividends", "document", "driven", "due", "early",
"earnings", "effect", "effective", "effects", "either", "employee",
"end", "ended", "entered", "entity", "equity", "equivalents",
"estimate", "estimated", "estimates", "except", "exchange", "executive",
"existing", "expect", "expected", "expects", "expenditures",
"expense", "expenses", "facilities", "facility", "factors", "fair",
"federal", "fees", "fiduciary", "filed", "filer", "financial",
"financing", "first", "fiscal", "fixed", "flow", "flows", "following",
"follows", "foreign", "form", "forward", "full", "funds", "future",
"gain", "gains", "gaming", "general", "generally", "gift", "global",
"goods", "goodwill", "government", "gross", "growth", "guarantees",
"guidance", "half", "hedge", "hedges", "hedging", "held", "high",
"higher", "historical", "impact", "impairment", "include", "included",
"includes", "including", "income", "increase", "increased", "incurred",
"indicate", "information", "infringement", "inputs", "instruments",
"insurance", "intangible", "intercompany", "interest", "interests",
"interim", "internal", "international", "inventory", "investing",
"investment", "investments", "issuance", "issued", "item", "items",
"jewelry", "judgment", "lease", "leases", "legal", "less", "level",
"liabilities", "liability", "limited", "liquidity", "litigation",
"long", "looking", "loss", "losses", "lower", "made", "make",
"management", "margin", "mark", "market", "marketable", "markets",
"material", "materially", "matters", "maximum", "measure", "measurement",
"measures", "merchandise", "metal", "million", "millions", "modified",
"months", "net", "new", "nine", "note", "notes", "number", "obligation",
"obligations", "officer", "offset", "one", "operating", "operations",
"option", "options", "ordinary", "organic", "outstanding", "owned",
"paid", "paper", "part", "partially", "parties", "party", "patents",
"payable", "payment", "payments", "pension", "per", "percent",
"percentage", "performance", "period", "periodic", "periods",
"permitted", "plan", "plans", "points", "policies", "policy",
"portion", "position", "postretirement", "potential", "practical",
"precious", "presentation", "presented", "previously", "price",
"prices", "primarily", "principal", "prior", "procedures", "proceedings",
"proceeds", "product", "products", "program", "property", "provide",
"provided", "provides", "provisional", "provisions", "purchase",
"purchases", "purposes", "pursuant", "quarter", "quarterly",
"rate", "rates", "reasonable", "reasonably", "receivable", "receivables",
"reclassified", "recognition", "recognized", "record", "recorded",
"reduction", "refer", "reflects", "regarding", "related", "report",
"reported", "reporting", "reports", "represents", "required",
"requirements", "requires", "respect", "respectively", "restructuring",
"result", "resulting", "results", "retail", "retained", "retirement",
"retrospective", "return", "returns", "revenue", "revenues",
"risk", "risks", "rule", "sale", "sales", "sec", "second", "section",
"securities", "see", "segment", "segments", "senior", "september",
"service", "services", "set", "settlement", "share", "shareholders",
"shares", "sheet", "short", "significant", "six", "software",
"sold", "solutions", "standard", "standards", "statement", "statements",
"states", "statutory", "stock", "store", "stores", "subject",
"subsidiaries", "subsidiary", "swaps", "swatch", "table", "target",
"tax", "taxes", "technology", "term", "terms", "third", "three",
"tiffany", "time", "timing", "total", "trademark", "transaction",
"transactions", "transfer", "transition", "translation", "two",
"typically", "underlying", "united", "units", "upon", "us", "use",
"used", "using", "value", "various", "weighted", "well", "whether",
"wholesale", "within", "year", "years")), x = c(0.825446869246662,
0.995752391405404, 1.77265380509198, 3.77759608626366, 21, 33,
37, 44, 15, 15, 27, 3, 7, 9, 25, 16, 92, 91, 129, 85, 31, 17,
40, 71, 11, 7, 30, 29, 9, 18, 79, 33, 6, 67, 6, 91, 58, 86, 54,
97, 39, 21, 211, 69, 19, 9, 18, 12, 10, 21, 50, 15, 57, 29, 41,
69, 11, 119, 109, 5, 1, 6, 36, 21, 13, 26, 120, 25, 12, 20, 3,
35, 16, 21, 9, 41, 24, 75, 139, 76, 6, 9, 21, 18, 21, 15, 21,
25, 20, 23, 16, 20, 9, 30, 101, 45, 22, 40, 71, 18, 15, 14, 13,
5, 1, 45, 5, 26, 22, 25, 48, 68, 13, 54, 22, 147, 105, 34, 94,
64, 65, 18, 31, 16, 18, 39, 11, 27, 35, 9, 3, 39, 11, 2, 12,
48, 5, 15, 39, 33, 6, 42, 15, 4, 18, 20, 30, 19, 19, 69, 67,
3, 144, 30, 9, 103, 15, 14, 76, 38, 87, 97, 405, 104, 27, 6,
115, 45, 15, 6, 57, 17, 7, 146, 8, 27, 15, 39, 16, 31, 34, 47,
32, 27, 64, 39, 6, 107, 45, 6, 66, 53, 17, 10, 33, 6, 148, 31,
198, 110, 21, 14, 79, 168, 15, 11, 43, 52, 28, 18, 21, 10, 3,
20, 31, 13, 11, 108, 86, 31, 26, 99, 42, 87, 19, 82, 50, 15,
3, 9, 27, 66, 86, 9, 200, 89, 3, 52, 39, 3, 13, 22, 24, 60, 72,
61, 53, 21, 12, 8, 48, 13, 180, 113, 506, 280, 38, 83, 180, 103,
43, 24, 78, 29, 45, 50, 152, 102, 11, 2, 38, 24, 17, 15, 17,
18, 33, 30, 14, 15, 8, 3, 43, 30, 21, 16, 84, 16, 12, 12, 19,
14, 12, 9, 27, 13, 66, 37, 7, 89, 20, 21, 18, 33, 54, 18, 451,
508, 66, 6, 83, 45, 38, 126, 57, 54, 12, 112, 31, 3, 8, 82, 18,
6, 33, 21, 14, 11, 25, 24, 30, 36, 169, 66, 150, 6, 263, 152,
16, 13, 19, 15, 9, 28, 41, 6, 45, 12, 3, 83, 9, 181, 143, 288,
186, 85, 71, 3, 3, 3, 148, 45, 7, 4, 6, 12, 107, 234, 8, 14,
3, 96, 13, 36, 7, 81, 149, 36, 24, 69, 39, 30, 30, 15, 27, 104,
3, 12, 39, 3, 35, 10, 20, 33, 87, 10, 89, 5, 41, 69, 119, 165,
52, 23, 275, 108, 36, 4, 44, 114, 23, 79, 79, 140, 3, 35, 13,
30, 167, 125, 40, 100, 253, 87, 12, 29, 28, 41, 6, 32, 27, 49,
6, 88, 55, 18, 26, 104, 37, 22, 54, 15, 25, 9, 69, 143, 59, 91,
118, 66, 7, 2, 12, 60, 23, 23, 98, 45, 6, 2, 28, 26, 24, 9, 29,
35, 9, 12, 35, 15, 59, 27, 5, 6, 10, 39, 66, 75, 23, 27, 19,
16, 20, 15, 9, 20, 76, 12, 3, 19, 47, 54, 10, 22, 22, 30, 92,
38, 21, 18, 28, 18, 16, 14, 34, 12, 9, 124, 39, 10, 17, 12, 27,
4, 5, 30, 97, 27, 25, 31, 16, 18, 9, 25, 3, 21, 8, 61, 6, 115,
67, 123, 111, 12, 4, 17, 22, 9, 156, 138, 281, 17, 23, 53, 82,
26, 19, 108, 131, 12, 17, 25, 30, 9, 3, 22, 18, 29, 1, 33, 11,
30, 12, 45, 6, 124, 254, 419, 163, 9, 8, 24, 54, 7, 53, 25, 55,
9, 135, 41, 58, 29, 75, 23, 3, 6, 48, 18, 59, 15, 77, 67, 28,
3, 68, 17, 27, 22, 31, 18, 71, 52, 275, 207, 21, 24, 15, 27,
9, 26, 16, 25, 29, 12, 13, 6, 16, 39, 55, 41, 59, 34, 6, 36,
33, 101, 74, 254, 97, 63, 11, 146, 106, 34, 29, 6, 7, 31, 36,
28, 22, 59, 30, 53, 39, 195, 90, 15, 12, 9, 19, 9, 69, 15, 91,
43, 18, 29, 33, 24, 18, 24, 24, 276, 170, 408, 359, 12, 21, 73,
55, 213, 18, 183, 115, 412, 21, 3, 112, 4, 7, 63, 8, 9, 12, 63,
53, 18, 31, 106, 80, 46, 11, 80, 38, 15, 3, 90, 56, 47, 8, 182,
173, 69, 31, 34, 43, 52, 39, 48, 161, 12, 25, 20, 6, 12, 60,
12, 33, 12, 91, 61, 7, 23, 69, 16, 6, 35, 33, 55, 29, 22, 56,
35, 4, 9, 46, 16, 27, 33, 5, 9, 50, 9, 3, 39, 15, 3, 47, 1, 44,
16, 2, 40, 15, 19, 58, 34, 9, 147, 62, 4, 3, 72, 1, 22, 3, 154,
50, 59, 2, 67, 13, 2, 27, 72, 38, 10, 27, 33, 35, 104, 3, 47,
13, 20, 24, 10, 24, 9, 1, 44, 12, 11, 15, 18, 52, 53, 217, 70,
3, 7, 100, 3, 19, 46, 71, 61, 35, 42, 93, 98, 22, 17, 115, 66,
67, 57, 150, 98, 225, 165, 897, 186, 43, 30, 190, 79, 55, 20,
60, 142, 3, 72, 19, 15, 20, 15, 18, 90, 55, 160, 98, 33, 18,
6, 51, 27, 12, 21, 67, 146, 1, 119, 5, 27, 3, 51, 9, 3, 62, 15,
72, 77, 105, 134, 3, 90, 2, 6, 6, 9, 40, 16, 15, 18, 29, 12,
37, 6, 17, 28, 3, 23, 15, 3, 60, 15, 21, 45, 72, 33, 10, 14,
157, 34, 22, 3, 28, 19, 102, 14, 83, 117, 75, 48, 97, 66, 10,
10, 19, 18, 81, 1, 10, 41, 18, 226, 64, 3, 3, 107, 28, 18, 27,
7, 27, 35, 12, 28, 68, 6, 16, 13, 48, 81, 90, 78, 294, 94, 15,
6, 8, 53, 18, 3, 46, 18, 15, 24, 42, 31, 15, 6, 25, 76, 18, 54,
26, 29, 33, 30, 36, 27, 61, 19, 291, 126, 28, 11, 71, 53, 13,
16, 30, 21, 14, 37, 33, 13, 2, 36, 14, 17, 19, 70, 166, 28, 18,
40, 49, 15, 15, 18, 24, 60, 23, 115, 72, 68, 47, 18, 18, 52,
37, 33, 25, 22, 53, 18, 21, 27, 15, 18, 11, 54, 6, 12, 3, 24,
15, 3, 21, 89, 12, 17, 6, 18, 27, 24, 16, 36, 17, 81, 109, 235,
234, 888, 382, 97, 79, 183, 117, 9, 6, 21, 30, 167, 262, 485,
177, 158, 132, 517, 431, 43, 99, 208, 118, 76, 66, 134, 38, 132,
92, 64, 36, 251, 37, 96, 72, 32, 27, 49, 58, 16, 3, 56, 23, 40,
9, 58, 41, 36, 36, 18, 48, 20, 14, 61, 47, 25, 16, 53, 68, 80,
127, 200, 74, 39, 167, 459, 154, 5, 6, 5, 38, 1, 27, 12, 20,
3, 3, 56, 3, 87, 38, 33, 72, 57, 12, 21, 9, 14, 29, 38, 56, 25,
21, 13, 61, 14, 21, 18, 40, 22, 16, 10, 53, 8, 6, 3, 17, 298,
3, 1, 15, 44, 69, 6, 12, 18, 33, 17, 7, 3, 15, 34, 9, 33, 102,
17, 21, 136, 28, 74, 135, 154, 92, 110, 14, 24, 36, 68, 15, 130,
32, 75, 90, 257, 90, 3, 3, 40, 44, 16, 32, 62, 87, 3, 22, 34,
17, 6, 126, 20, 9, 69, 61, 12, 5, 59, 15, 9, 36, 14, 12, 6, 42,
13, 27, 36, 52, 15, 23, 79, 29, 48, 15, 11, 38, 20, 2, 21, 25,
9, 110, 12, 13, 27, 24, 12, 19, 31, 30, 16, 53, 22, 16, 34, 9,
25, 54, 9, 24, 33, 79, 27, 123, 53, 28, 21, 31, 43, 25, 34, 145,
83, 18, 24, 15, 21, 18, 4, 18, 13, 18, 6, 39, 26, 49, 3, 1, 46,
55, 6, 6, 36, 52, 32, 76, 133, 9, 23, 32, 11, 12, 14, 35, 25,
35, 35, 147, 25, 3, 14, 14, 22, 18, 8, 27, 12, 16, 5, 5, 27,
18, 19, 21, 3, 12, 20, 19, 52, 17, 24, 16, 18, 35, 33, 62, 246,
45, 236, 212, 41, 21, 28, 27, 45, 111, 69, 177, 25, 8, 180, 45,
12, 9, 19, 26, 9, 18, 18, 7, 21, 2, 46, 6, 41, 42, 6, 33, 20,
30, 22, 36, 69, 43, 42, 20, 196, 57, 19, 9, 10, 18, 25, 36, 66,
76, 13, 19, 11, 25, 57, 30, 42, 6, 3, 7, 51, 6, 21, 24, 27, 36,
126, 67, 272, 131, 72, 38, 77, 45, 16, 60, 75, 44, 32, 18, 51,
45, 12, 12, 25, 15, 9, 46, 39, 7, 41, 31, 44, 39, 15, 6, 34,
45, 10, 3, 31, 24, 5, 3, 7, 41, 78, 79, 98, 36, 7, 191, 21, 6,
39, 59, 20, 28, 21, 51, 53, 129, 82, 19, 10, 42, 9, 15, 38, 10,
11, 29, 14, 7, 15, 27, 27, 38, 26, 10, 17, 18, 18, 1, 23, 286,
76, 396, 51, 36, 34, 33, 24, 104, 45, 33, 3, 36, 21, 28, 12,
18, 24, 8, 9, 102, 29, 78, 187, 34, 471, 22, 6, 18, 7, 78, 11,
56, 68, 24, 30, 21, 30, 182, 37, 89, 100, 18, 20, 28, 57, 26,
5, 18, 20, 27, 27, 22, 9, 21, 27, 12, 4, 253, 20, 7, 12, 47,
50, 12, 283, 12, 5, 3, 19, 33, 14, 12, 27, 45, 113, 176, 239,
166, 44, 42, 140, 2, 96, 47, 169, 62, 18, 3, 21, 27, 3, 21, 75,
42, 52, 13, 80, 56, 23, 62, 138, 38, 36, 4, 9, 2, 6, 18, 37,
85, 25, 33, 94, 7, 17, 58, 20, 39, 3, 24, 110, 48, 217, 160,
311, 189, 72, 14, 27, 11, 12, 3, 37, 174, 49, 16, 123, 32, 64,
37, 79, 23, 6, 39, 39, 24, 3, 124, 49, 9, 3, 36, 11, 21, 3, 70,
132, 26, 6, 37, 179, 4, 57, 12, 159, 155, 296, 329, 24, 33, 113,
48, 27, 6, 55, 16, 31, 116, 180, 113, 8, 24, 28, 37, 74, 13,
81, 98, 55, 152, 281, 145, 472, 49, 22, 143, 95, 11, 19, 22,
76, 49, 178, 89, 3, 48, 6, 13, 83, 42, 20, 12, 36, 78, 6, 6,
68, 21, 19, 6, 46, 39, 3, 66, 31, 14, 4, 21, 24, 3, 7, 49, 8,
9, 47, 9, 72, 14, 42, 11, 13, 22, 33, 37, 24, 73, 27, 24, 21,
27, 33, 27, 76, 60, 21, 3, 109, 29, 15, 22, 64, 47, 93, 63, 205,
109, 15, 47, 19, 24, 3, 26, 7, 23, 4, 45, 91, 12, 12, 25, 23,
3, 68, 21, 58, 32, 106, 425, 67, 176, 232, 65, 6, 20, 75), factors = list())