Treatment of responses below the detection limit: some current techniques compared by factor analysis on environmental data

被引:23
作者
Aruga, R
机构
[1] Department of Analytical Chemistry, University of Turin, Via Giuria 5
关键词
detection limit; responses below; factor analysis and detection limit; principal component analysis and detection limit; reporting limit;
D O I
10.1016/S0003-2670(97)00463-7
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Three methods of treatment of values below the detection limit (or 'less-than' values) are compared, in a typical case of multivariate statistical processing of environmental data. The: data refer to the concentration of 14 chemical species in 42 samples of surface waters, on which a Factor Analysis is made to study the causes of pollution. Considerable effectiveness is shown, even in the presence of severe censoring, by two rather simple and widespread methods. They consist, respectively, in replacing the less-than values with a constant value and with values randomly distributed within zero and the detection limit. On the other hand, the method which estimates less than values by means of Principal Component Analysis on the known data proves to be less effective. It is also shown that a logarithmic transformation of the original data makes the methods of treatment of less-thans less effective. (C) 1997 Elsevier Science B.V.
引用
收藏
页码:255 / 262
页数:8
相关论文
共 18 条
[1]  
[Anonymous], 1983, INTERPRETATION ANAL
[2]  
*APHA AWWA WPCF, 1975, STAND METH EX WAT WA
[3]  
ARUGA R, 1990, ANN CHIM-ROME, V80, P341
[4]   MULTIVARIATE DATA-ANALYSIS APPLIED TO THE INVESTIGATION OF RIVER POLLUTION [J].
ARUGA, R ;
NEGRO, G ;
OSTACOLI, G .
FRESENIUS JOURNAL OF ANALYTICAL CHEMISTRY, 1993, 346 (10-11) :968-975
[5]  
ARUGA R, UNPUB
[6]  
*CENS CORP IDR, 1980, REG PIEM ASS AMB EN
[7]  
*CNR IRSA, 1975, MET AN ACQ
[8]  
DAVIS JC, 1986, STATISTICS DATA ANAL
[9]  
FORINA M, 1988, PARVUS
[10]   SOURCE INPUT ELUCIDATION IN POLLUTED COASTAL SYSTEMS BY FACTOR-ANALYSIS OF SEDIMENTARY HYDROCARBON DATA [J].
GRIMALT, JO ;
CANTON, L ;
OLIVE, J .
CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 1993, 18 (01) :93-109