Technometrics Highlights
Forecasting, Reliability, and Design
of Experiments Part of Newest Issue
David M. steinberg, Technometrics Editor
T
he August issue of Technometrics includes 10
articles that cover a broad range of topics,
including forecasting, reliability, design of
experiments, computer experiments, automatic
control, regression, and measurement.
The lead article, by Haipeng Shen, is “On
Modeling and Forecasting Time Series of Smooth
Curves.” This research was motivated by problems
arising in the operations management of telephone
customer service centers, where forecasts of daily
call arrival rate profiles are needed for service agent
staffing and scheduling purposes. The article shows
how these data can be effectively modeled as a time
series of smooth curves and develops methods for
forecasting such curves and dynamically updating
the forecasts. The methodology has three compo-
nents: dimension reduction through a smooth factor
model, time series modeling and forecasting of the
factor scores, and dynamic updating using penalized
least squares. The proposed methods are illustrated
via call center data and two simulation studies.
“Two-Stage Leveraged Measurement System
Assessment,” by Ryan Browne, Jock MacKay, and
of control-by-noise interactions without altering the
Stefan Steiner, presents a method for studying the
effect hierarchy. A modified exchange algorithm is
variation in a measurement system. The new plan
proposed for finding the designs, and matching
is conducted in two stages. In the first stage, called
software is available online. The authors also explain
the baseline, a number of parts are measured once.
how to design experiments with internal noise fac-
In the second stage, a few extreme parts are selected
tors, a topic that has received scant attention in the
(based on their baseline measurement) and each is
literature. The advantages of the proposed approach
re-measured several times. The authors compare this
are illustrated using several examples.
to the standard approach of making repeat measure-
In “Algorithmic Construction of Efficient
ments on a random sample of parts and demon-
Fractional Factorial Designs with Large Run Sizes,”
strate the advantage of the leveraged plan in terms of
Hongquan Xu develops a sequential algorithm
the bias and standard deviation of estimators of the
for constructing minimum aberration, two-level,
intraclass correlation coefficient. They also present a
fractional factorial designs. The algorithm exploits
method to determine sample size when planning a
results that relate minimum aberration designs to
leveraged measurement system assessment.
minimum aberration projections onto a subset of
Lulu Kang and V. Roshan Joseph contrib-
factors in a sequential build-up process. Moment
ute “Bayesian Optimal Single Arrays for Robust
projection patterns are used to efficiently identify
Parameter Design.” A critical goal in robust param-
nonisomorphic designs. A fast isomorphism check
eter design experiments is to estimate control factor-
procedure is developed by matching the factors
by-noise factor interactions. To achieve this goal in
using their delete-one-factor projections. This algo-
small experiments, some researchers have proposed
rithm is used to completely enumerate all 128-run
use of a modified effect hierarchy principle. In this
designs of resolution 4, all 256-run designs of res-
article, Kang and Joseph propose a Bayesian criteri-
olution 4 up to 17 factors, all 512-run designs of
on for single arrays that incorporates the importance
resolution 5, all 1024-run designs of resolution 6,
OCTObER 2009 AMsTAT NEWs 23
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