DETECTING INTERACTIONS USING LOW-DIMENSIONAL SEARCHES IN HIGH-DIMENSIONAL DATA

被引：2

作者：

SPIEGELMAN, CH ^{[1
]}

WANG, CY ^{[1
]}

机构：

[1] FRED HUTCHINSON CANC RES CTR,DIV PUBL HLTH SCI,SEATTLE,WA 98104

来源：

CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS | 1994年 / 23卷 / 02期

基金：

美国国家科学基金会;

关键词：

D O I：

10.1016/0169-7439(94)00009-3

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

One important issue in chemometrics is to detect interactions among several factors. In this paper, we propose methods that detect interactions using low dimensional smoothers. Two methods are investigated and compared with usual least squared methods via Monte Carlo simulations. In addition, we show, using real data, how the methods affect our decisions.

引用

页码：293 / 299

页数：7

共 11 条

[1] BOX GEP, 1978, STATISTICS EXPT
[2] THE LITTLE BOOTSTRAP AND OTHER METHODS FOR DIMENSIONALITY SELECTION IN REGRESSION - X-FIXED PREDICTION ERROR
BREIMAN, L
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1992, 87 (419) : 738 - 754
[3] INTERACTION SPLINE MODELS AND THEIR CONVERGENCE-RATES
CHEN, ZH
[J]. ANNALS OF STATISTICS, 1991, 19 (04) : 1855 - 1868
[4] Eubank R. L, 1988, SMOOTHING SPLINE NON
[5] TESTING THE GOODNESS OF FIT OF A LINEAR-MODEL VIA NONPARAMETRIC REGRESSION TECHNIQUES
EUBANK, RL
SPIEGELMAN, CH
[J]. JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 1990, 85 (410) : 387 - 392
[6] FRIEDMAN JH, 1989, TECHNOMETRICS, V31, P3, DOI 10.2307/1270359
[7] HASTIE T, 1989, TECHNOMETRICS, V31, P3
[8] Hastie T.J., 2017, GEN ADDITIVE MODELS, P1, DOI [DOI 10.1201/9780203753781, 10.1201/9780203753781]
[9] SILVERMAN BW, 1985, J R STAT SOC B, V47, P1
[10] SNEDECOR GW, 1993, ANN STAT, V21, P235

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