ThreeMode Abstracts, Part Y
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INDEX
Ya  Yb 
Yc  Yd 
Ye  Yf 
Yg  Yh 
Yi  Yj 
Yk  Yl 
Ym  Yn 
Yo  Yp 
Yq  Yr 
Ys  Yt 
Yu  Yv 
Yw  Yx 
Yy  Yz 


Yakovleva, E., Hopke, P.K., & Wallace, L. (1999).
Receptor modeling assessment of particle total exposure assessment methodology
data. Environmental Science & Technology, 33, 36453652.
Data from the 1991 Particle Total Exposure Assessment Methodology (PTEAM) study
in Riverside, CA, were analyzed using a new receptor modeling method. Positive
matrix factorization analysis (Paatero, 1997) was performed on the threeway array that
was constructed with the following modes: (1) elemental concentrations (18
variables), (2) samples (303 measurements), (3) sampling type (personal
PM_{10}, indoor PM_{10}, outdoor PM_{10}, indoor
PM_{2.5}, outdoor PM_{2.5}) in order to describe the sources of
personal exposure. The threeway PMF solution for these data yielded both factor
profiles and their contributions and in addition provided the distribution of
each source between personal/indoor/outdoor fine/coarse PM, allowing the
analysis of the influence of outdoor sources on personal particulate exposure.
To identify relative contribution of different sources, regression of the
particulate matter mass against the factor contributions was
performed.

Yanai, H. (1994).
Tahenryo data kaisekiho: Riron to ohyo [Methods of
multivariate data analysis: Theory and applications]. Chapter 8
(pp. 151159). Tokyo: Asakurashoten.
Overview of threeway methods and their estimation, e.g. Tucker3, INDSCAL and
PARAFAC.

Yoshino, Y. (1986).
Dimensional subtypes of depression derived by threemode factor
analysis. Kyushu Neuro psychiatry, 32, 245257.
Studied the dimensional subtypes of depression reflecting the therapeutic
response to 4 wks of
antidepressant therapy. Human subjects: 55 male and female Japanese adults
(aged 2079 yrs)
(depression). Psychic and somatic changes were assessed before drug
administration and weekly
thereafter for 4 wks using the Clinical Psychopharmacology Research Group
Depression Rating
Scale for Doctor's Use. Longitudinal data were subjected to threemode
factor analysis (55 Ss
* 20 scales * 5 occasions).

Yoshizawa, T. (1975).
Models for quantification techniques in
multiple contingency
tables: The theoretical approach. Kodokeiryogaku (Japanese Journal of
Behaviormetrics),
3, 111.; English abstract, p. 82.
Models which may decompose the three variable interaction in rxsxt
contingency tables are
proposed, the models for the additive and multiplicative definition of no
interaction being
extended. One of those models makes possible an interferential approach to
Iwatsubo's (1974)
quantification technique, which is regarded as a statistically
descriptionoriented method.
The equivalence of our chi square criterion to the maximization of the
third order
correlation coefficient p (rho) is shown. Several properties of the new
models are derived,
including the n.s. conditions that the p vanishes and the exact upper
bound of p squared. Many
versions of the models and testing procedures for them are suggested.

Yoshizawa, T. (1976).
A generalized definition of interactions and singular value
decomposition of multiway arrays. Kodokeiryogaku (Japanese
Journal of Behaviormetrics), 4, 3242.; English abstract, p. 87.
A generalized definition of the sth order interactions is given
for multiway arrays, from which the similar properties with ANOVA
model are derived. The problem of maximization of the highest
order correlation function is solved. Moreover, an expression
decomposing multiway arrays is shown as a recurrent algorithm
that is an extension of the singular value decomposition of
matrices. Applications of the decomposition to multiway
contingency tables and to the multiway classified data are
outlined. This research develops Iwatsubo (1974) and Yoshizawa
(1975), and relates with Bahadur's expression and Lancaster's
definition of no interaction for contingency tables. The
definition and expression given here are more general and
constructive than theirs.

Yoshizawa, T. (1988).
Singular value decomposition of multiarray data and its
applications. In E. Diday, C. Hayashi, M. Jambu, & N. Ohsumi
(Eds.), Recent Developments in Clustering and Data Analysis:
Proceedings of the JapaneseFrench Scientific Seminar, March 2426,
1987
(pp. 241257). Boston: Academic Press, Inc.
In this paper, the theory of singular value decomposition of multiarray data is
roughly sketched. The configuration of the extended singular value decomposition
is demonstrated, in comparison with the Tucker3 model for three way data. Next,
the criteria and algorithms needed to derive the decomposition, the nested
configuration and its interpretation are described. Finally, some applications
are given.

Young, F.W. (1981).
Quantitative analysis of qualitative
data.Psychometrika,46, 357388
Presents an overview of an approach to the quantitative analysis
of qualitative data with theoretical and methodological
explanations of its basis in alternating least squares and
optimal scaling. Using these 2 principles, analysis procedures
originally proposed for quantitative (interval or ratio) data are
extended to qualitative (nominal or ordinal) data, including
common factor and threemode factor analysis and multidimensional
scaling. If a least squares procedure is known for analyzing
quantitative data, it can be extended to qualitative data and the
resulting algorithm will be convergent.

Yue, H. H., Qin, S. J., Markle, R. J., Nauert, C., & Gatto, M. (2000).
Fault detection of plasma etchers using optical emission spectra.
IEEE Transactions on Semiconductor Manufacturing, 13, 374385.
The objective of this paper is to investigate the suitability of using optical
emission spectroscopy (OES) for the fault detection and classification of plasma etchers. The OES
sensor system used in this study can collect spectra at up to 512 different wavelengths, Multiple
scans of the spectra are taken from a wafer, and the spectra data are available for multiple wafers,
As a result, the amount of the OES data is typically large, This poses a difficulty in extracting
relevant information for fault detection and classification, In this paper, we propose the use of
multiway principal component analysis (PCA) to analyze the sensitivity of the multiple scans within a
wafer with respect to typical faults such as etch stop, which is a fault that occurs when the polymer
deposition rate is larger than the etch rate, Several PCAbased schemes are tested for the purpose of
fault detection and wavelength selection, A sphere criterion is proposed for wavelength selection and
compared with an existing method in the literature. To construct the final monitoring model, the OES
data of selected wavelengths are properly scaled to calculate fault detection indices, Reduction in
the number of wavelengths implies reduced cost for implementing the fault detection system. All
experiments are conducted on an Applied Materials 5300 oxide etcher at Advanced Micro Devices (AMD) in
Austin, TX.
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P.M. Kroonenberg
Education and Child Studies, Leiden University
Wassenaarseweg 52, 2333 AK Leiden, The Netherlands
Tel. *31715273446/5273434 (secr.); fax *31715273945
Email:
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First version : 12/02/1997;