bluuebunny/crossref_metadata_2025 huggingface dataset:
ECONOMETRICS
Authors: Choi In
Published: November 2002

There are six factors that can enhance or weaken an econometrics
text: coverage, lucidity, speed, independence, examples, and
exercises. With clear explanations and a smooth pace, Fumio
Hayashi's Econometrics succeeds as a solid first-year
graduate text. The ample empirical applications examples reflect
the author's research interest—applied
econometrics—and make the work best suited for students
sharing that interest.
MIXING AND MOMENT PROPERTIES OF VARIOUS GARCH AND STOCHASTIC
VOLATILITY MODELS
Authors: Carrasco Marine , Chen Xiaohong
Published: November 2002

This paper first provides some useful results on a generalized
random coefficient autoregressive model and a generalized hidden
Markov model. These results simultaneously imply strict
stationarity, existence of higher order moments, geometric
ergodicity, and β-mixing with exponential decay rates, which are
important properties for statistical inference. As applications, we
then provide easy-to-verify sufficient conditions to ensure β-mixing
and finite higher order moments for various linear and nonlinear
GARCH(1,1), linear and power GARCH(p,q), stochastic
volatility, and autoregressive conditional duration models. For many of
these models, our sufficient conditions for existence of second
moments and exponential β-mixing are also necessary. For several
GARCH(1,1) models, our sufficient conditions for existence of higher
order moments again coincide with the necessary ones in He and Terasvirta
(1999, Journal of Econometrics 92, 173–192).
ON INTERCEPT ESTIMATION IN THE SAMPLE SELECTION MODEL
Authors: Schafgans Marcia M.A. , Zinde-Walsh Victoria
Published: November 2002

We provide a proof of the consistency and asymptotic normality
of the estimator suggested by Heckman (1990, American Economic
Review 80, 313–318) for the intercept of a
semiparametrically estimated sample selection model. The estimator
is based on “identification at infinity,” which
leads to nonstandard convergence rate.
SAMPLE MEANS, SAMPLE AUTOCOVARIANCES, AND LINEAR REGRESSION
OF STATIONARY MULTIVARIATE LONG MEMORY PROCESSES
Authors: Chung Ching-Fan
Published: November 2002

We develop an asymptotic theory for the first two sample moments
of a stationary multivariate long memory process under fairly
general conditions. In this theory the convergence rates and
the limits (the fractional Brownian motion, the Rosenblatt process,
etc.) all depend intrinsically on the degree of long memory
in the process. The theory of the sample moments is then applied
to the multiple linear regression model. An interesting finding
is that, even though all the regressors and the disturbance
are stationary and ergodic, the joint long memory in one single
regressor and in the disturbance can invalidate the usual
asymptotic theory for the ordinary least squares (OLS) estimation.
Specifically, the convergence rates of the OLS estimators become
slower, the limits are not normal, and the standard t- and
F-tests all collapse.
ON THE JACKKNIFE-AFTER-BOOTSTRAP METHOD FOR DEPENDENT DATA
AND ITS CONSISTENCY PROPERTIES
Authors: Lahiri S.N.
Published: November 2002

Motivated by Efron (1992, Journal of the Royal Statistical
Society, Series B 54, 83–111), this paper proposes
a version of the moving block jackknife as a method of estimating
standard errors of block-bootstrap estimators under dependence.
As in the case of independent and identically distributed (i.i.d.)
observations, the proposed method merely regroups the values
of a statistic from different bootstrap replicates to produce
an estimate of its standard error. Consistency of the resulting
jackknife standard error estimator is proved for block-bootstrap
estimators of the bias and the variance of a large class of
statistics. Consistency of Efron's method is also established
in similar problems for i.i.d. data.
STATIONARY PROCESSES THAT LOOK LIKE RANDOM WALKS— THE
BOUNDED RANDOM WALK PROCESS IN DISCRETE AND CONTINUOUS TIME
Authors: Nicolau João
Published: November 2002

Several economic and financial time series are bounded by an
upper and lower finite limit (e.g., interest rates). It is not
possible to say that these time series are random walks because
random walks are limitless with probability one (as time goes
to infinity). Yet, some of these time series behave just like
random walks. In this paper we propose a new approach that takes
into account these ideas. We propose a discrete-time and a
continuous-time process (diffusion process) that generate bounded
random walks. These paths are almost indistinguishable from
random walks, although they are stochastically bounded by an
upper and lower finite limit. We derive for both cases the ergodic
conditions, and for the diffusion process we present a closed
expression for the stationary distribution. This approach suggests
that many time series with random walk behavior can in fact
be stationarity processes.
REGRESSION QUANTILES FOR TIME SERIES
Authors: Cai Zongwu
Published: November 2002

In this paper we study nonparametric estimation of regression
quantiles for time series data by inverting a weighted
Nadaraya–Watson (WNW) estimator of conditional distribution
function, which was first used by Hall, Wolff, and Yao (1999,
Journal of the American Statistical Association 94,
154–163). First, under some regularity conditions, we
establish the asymptotic normality and weak consistency of the
WNW conditional distribution estimator for α-mixing time
series at both boundary and interior points, and we show that
the WNW conditional distribution estimator not only preserves
the bias, variance, and, more important, automatic good boundary
behavior properties of local linear “double-kernel”
estimators introduced by Yu and Jones (1998, Journal of
the American Statistical Association 93, 228–237),
but also has the additional advantage of always being a
distribution itself. Second, it is shown that under some regularity
conditions, the WNW conditional quantile estimator is weakly
consistent and normally distributed and that it inherits all
good properties from the WNW conditional distribution estimator.
A small simulation study is carried out to illustrate the
performance of the estimates, and a real example is also used
to demonstrate the methodology.
NONPARAMETRIC ESTIMATION AND TESTING OF INTERACTION IN ADDITIVE
MODELS
Authors: Sperlich Stefan , Tjøstheim Dag , Yang Lijian
Published: November 2002

We consider an additive model with second-order interaction
terms. Both marginal integration estimators and a combined
backfitting-integration estimator are proposed for all components
of the model and their derivatives. The corresponding asymptotic
distributions are derived. Moreover, two test statistics for
testing the presence of interactions are proposed. Asymptotics
for the test functions and local power results are obtained.
Because direct implementation of the test procedure based on
the asymptotics would produce inaccurate results unless the
number of observations is very large, a bootstrap procedure
is provided, which is applicable for small or moderate sample
sizes. Further, based on these methods a general test for
additivity is developed. Estimation and testing methods are
shown to work well in simulation studies. Finally, our methods
are illustrated on a five-dimensional production function for
a set of Wisconsin farm data. In particular, the separability
hypothesis for the production function is discussed.
CONSISTENCY AND EFFICIENCY OF LEAST SQUARES ESTIMATION FOR
MIXED REGRESSIVE, SPATIAL AUTOREGRESSIVE MODELS
Authors: Lee Lung-Fei
Published: November 2002

Least squares estimation has casually been dismissed as an
inconsistent estimation method for mixed regressive, spatial
autoregressive models with or without spatial correlated
disturbances. Although this statement is correct for a wide
class of models, we show that, in economic spatial environments
where each unit can be influenced aggregately by a significant
portion of units in the population, least squares estimators
can be consistent. Indeed, they can even be asymptotically
efficient relative to some other estimators. Their computations
are easier than alternative instrumental variables and maximum
likelihood approaches.
ASYMPTOTIC ROBUSTNESS IN MULTIPLE GROUP LINEAR-LATENT VARIABLE
MODELS
Authors: Satorra Albert
Published: November 2002

Standard methods for analyzing linear-latent variable models
rely on the assumption that the observed variables are normally
distributed. Normality allows statistical inferences to be carried
out based solely on the first-and second-order moments. In general,
inferences for nonnormally distributed data require the estimates
of matrices of third-and fourth-order moments. In the present
paper, we show that inferences based on normal theory retain
validity and asymptotic efficiency under general assumptions
that allow for considerable departure from normality. In
particular, we obtain conditions under which correct asymptotic
inferences are attained when replacing a matrix of higher order
moments by a matrix that depends only on cross-product moments
of the data.
TESTING FOR A UNIT ROOT IN A TIME SERIES WITH A LEVEL SHIFT
AT UNKNOWN TIME
Authors: Saikkonen Pentti , Lütkepohl Helmut
Published: November 2002

Unit root tests for time series with level shifts of general
form are considered when the timing of the shift is unknown.
It is proposed to estimate the nuisance parameters of the data
generation process including the shift date in a first step
and apply standard unit root tests to the residuals. The estimation
of the nuisance parameters is done in such a way that the unit
root tests on the residuals have the same limiting distributions
as for the case of a known break date. Simulations are performed
to investigate the small sample properties of the tests, and
empirical examples are discussed to illustrate the procedure.
ROBUST ESTIMATION OF STRUCTURAL BREAK POINTS
Authors: Fiteni Inmaculada
Published: November 2002

This paper proposes robust M-estimators of dynamic
linear models with a structural break of unknown location. Rates
of convergence and limiting distributions for the estimated
shift point and the estimated regression parameters are derived.
The analysis is carried out in the framework of possibly dependent
observations and also with trending regressors. The asymptotic
distribution of the break location estimator is obtained both
for fixed magnitude of shift and for shift with magnitude
converging to zero as the sample size increases. The latter
is essential for the derivation of feasible confidence intervals
for the break location. Monte Carlo simulations illustrate the
performance of asymptotic inferences in practice.
NONPARAMETRIC ESTIMATION WITH AGGREGATED DATA
Authors: Linton Oliver , Whang Yoon-Jae
Published: November 2002

We introduce a kernel-based estimator of the density function
and regression function for data that have been grouped into
family totals. We allow for a common intrafamily component but
require that observations from different families be independent.
We establish consistency and asymptotic normality for our
procedures. As usual, the rates of convergence can be very slow
depending on the behavior of the characteristic function at
infinity. We investigate the practical performance of our method
in a simple Monte Carlo experiment.
AN INVARIANCE PRINCIPLE FOR SIEVE BOOTSTRAP IN TIME SERIES
Authors: Park Joon Y.
Published: November 2002

This paper establishes an invariance principle applicable for
the asymptotic analysis of sieve bootstrap in time series. The
sieve bootstrap is based on the approximation of a linear process
by a finite autoregressive process of order increasing with
the sample size, and resampling from the approximated
autoregression. In this context, we prove an invariance principle
for the bootstrap samples obtained from the approximated
autoregressive process. It is of the strong form and holds almost
surely for all sample realizations. Our development relies upon
the strong approximation and the Beveridge–Nelson
representation of linear processes. For illustrative purposes,
we apply our results and show the asymptotic validity of the
sieve bootstrap for Dickey–Fuller unit root tests for
the model driven by a general linear process with independent
and identically distributed innovations. We thus provide a
theoretical justification on the use of the bootstrap
Dickey–Fuller tests for general unit root models, in place
of the testing procedures by Said and Dickey and by Phillips.
THE PROPERTIES OF Lp-GMM ESTIMATORS
Authors: de Jong Robert , Han Chirok
Published: November 2002

This paper considers generalized method of moment–type
estimators for which a criterion function is minimized that
is not the “standard” quadratic distance measure
but instead is a general Lp
distance measure. It is shown that the resulting estimators
are root-n consistent but not in general asymptotically
normally distributed, and we derive the limit distribution of
these estimators. In addition, we prove that it is not possible
to obtain estimators that are more efficient than the
“usual” L2-GMM estimators
by considering Lp-GMM estimators. We
also consider the issue of the choice of the weight matrix for
Lp-GMM estimators.
TESTING LINEAR RESTRICTIONS ON COINTEGRATING VECTORS: SIZES
AND POWERS OF WALD AND LIKELIHOOD RATIO TESTS IN FINITE SAMPLES
Authors: Haug Alfred A.
Published: November 2002

The Wald test for linear restrictions on cointegrating vectors
is compared in finite samples using the Monte Carlo method.
The Wald test is calculated within the vector error-correction
based estimation methods of Bewley, Orden, Yang, and Fisher
(1994, Journal of Econometrics 64, 3–27) and
of Johansen (1991, Econometrica 59, 1551–1580),
the canonical cointegration method of Park (1992,
Econometrica 60, 119–143), the dynamic ordinary
least squares method of Phillips and Loretan (1991, Review
of Economic Studies 58, 407–436), Saikkonen (1991,
Econometric Theory 7, 1–21), and Stock and Watson
(1993, Econometrica 61, 783–820), the fully modified
ordinary least squares method of Phillips and Hansen (1990,
Review of Economic Studies 57, 99–125), and the
band spectral techniques of Phillips (1991, in W. Barnett, J.
Powell, & G. E. Tauchen (eds.), Nonparametric and
Semiparametric Methods in Economics and Statistics, pp.
413–435). The Wald test performance is also compared to
that of the likelihood ratio test suggested by Johansen and
Juselius (1990, Oxford Bulletin of Economics and
Statistics 52, 169–210) and to a Bartlett correction
of that test as proposed by Johansen (1998, A Small Sample Test
for Tests of Hypotheses on Cointegrating Vectors, European
University Institute).
ON A PARTITIONED INVERSION FORMULA HAVING USEFUL APPLICATIONS
IN ECONOMETRICS
Authors: Faliva Mario , Zoia Maria Grazia
Published: November 2002

In this paper a novel partitioned inversion formula is obtained
in terms of the orthogonal complements of off-diagonal blocks,
with the emblematic matrix of unit-root econometrics emerging
as the leading diagonal block of the inverse. The result paves
the way to a straightforward derivation of a key result of vector
autoregressive econometrics.
PARTIAL REDUNDANCY OF MOMENT CONDITIONS
Authors: Qian Hailong
Published: November 2002

In this paper, we first transform a set of moment conditions
into a set of transformed moment conditions, based on which
the efficient partial generalized method of moments estimation
for part of a parameter vector is defined. Given the set of
transformed moment conditions, we then show that the conditions
for partial redundancy of an additional set of moment conditions
given an original set of moment conditions simply become the
conditions for full redundancy of the second subset of transformed
moment conditions given the first subset of transformed moment
conditions. Thus the transformed moment conditions proposed
in this paper unify partial redundancy of moment conditions
with full redundancy of moment conditions. Using transformed
moment conditions, we then straightforwardly derive necessary
and sufficient conditions for partial redundancy of one or two
subset(s) of moment conditions given the other when the large
set of moment conditions consists of three subsets of moment
conditions. The paper also provides several easily checkable
sufficient conditions for partial redundancy of one set of moment
conditions given other sets of moment conditions.
THE EXACT CUMULATIVE DISTRIBUTION FUNCTION OF A RATIO OF
QUADRATIC FORMS IN NORMAL VARIABLES, WITH APPLICATION TO THE
AR(1) MODEL
Authors: Forchini G.
Published: November 2002

Often neither the exact density nor the exact cumulative
distribution function (c.d.f.) of a statistic of interest is
available in the statistics and econometrics literature (e.g.,
the maximum likelihood estimator of the autocorrelation coefficient
in a simple Gaussian AR(1) model with zero start-up value).
In other cases the exact c.d.f. of a statistic of interest is
very complicated despite the statistic being “simple”
(e.g., the circular serial correlation coefficient, or a quadratic
form of a vector uniformly distributed over the unit
n-sphere). The first part of the paper tries to explain
why this is the case by studying the analytic properties of
the c.d.f. of a statistic under very general assumptions.
Differential geometric considerations show that there can be
points where the c.d.f. of a given statistic is not analytic,
and such points do not depend on the parameters of the model
but only on the properties of the statistic itself. The second
part of the paper derives the exact c.d.f. of a ratio of quadratic
forms in normal variables, and for the first time a closed form
solution is found. These results are then specialized to the
maximum likelihood estimator of the autoregressive parameter
in a Gaussian AR(1) model with zero start-up value, which is
shown to have precisely those properties highlighted in the
first part of the paper.
OPTIMAL SIMILAR TESTS FOR STRUCTURAL CHANGE FOR THE LINEAR
REGRESSION MODEL
Authors: Forchini G.
Published: November 2002

This paper analyzes similar tests for structural change for
the normal linear regression model in finite samples. Using
the approach of Wald (1943, American Mathematical Society
Transactions 54, 426–482), Hillier (1987,
Econometric Theory 3, 1–44), Andrews and Ploberger
(1994, Econometrica 62, 1382–1414), and Andrews,
Lee, and Ploberger (1996, Journal of Econometrics 70,
9–36), we characterize a class of optimal similar tests
for the existence of (possibly multiple) changepoints at unknown
times. We extend the analysis of Andrews et al. (1996) by deriving
weighted optimal similar tests for the case where the error
variance is not known. We also show that when the sample size
is large, the tests of Andrews et al. constructed by replacing
the error variance with an estimate are equivalent to the optimal
test derived in this paper. Power comparisons are provided by
a small simulation study.
MOMENT STRUCTURE OF A FAMILY OF FIRST-ORDER EXPONENTIAL GARCH
MODELS
Authors: He Changli , Teräsvirta Timo , Malmsten Hans
Published: November 2002

In this paper we consider the moment structure of a class of
first-order exponential generalized autoregressive conditional
heteroskedasticity (GARCH) models. This class contains as special
cases both the standard exponential GARCH model and the symmetric
and asymmetric logarithmic GARCH model. Conditions for the
existence of any arbitrary moment are given. Furthermore, the
expressions for the kurtosis and the autocorrelations of positive
powers of absolute-valued observations are derived. The properties
of the autocorrelation structure are discussed and compared
to those of the standard first-order GARCH process. In particular,
it is seen that, contrary to the standard GARCH case, the decay
rate of the autocorrelations of squared errors is not constant
and that the rate can be quite rapid in the beginning, depending
on the parameters of the model.
ESTIMATION IN AN ADDITIVE MODEL WHEN THE COMPONENTS ARE LINKED
PARAMETRICALLY
Authors: Carroll Raymond J. , Härdle Wolfgang , Mammen Enno
Published: November 2002

Motivated by a nonparametric GARCH model we consider nonparametric
additive autoregression models in the special case that the
additive components are linked parametrically. We show that
the parameter can be estimated with parametric rate and give
the normal limit. Our procedure is based on two steps. In the
first step nonparametric smoothers are used for the estimation
of each additive component without taking into account the
parametric link of the functions. In a second step the parameter
is estimated by using the parametric restriction between the
additive components. Interestingly, our method needs no
undersmoothing in the first step.
ON VARIABLE SELECTION IN LINEAR REGRESSION
Authors: Kabaila Paul
Published: November 2002

Shibata (1981, Biometrika 68, 45–54) considers
data-generating mechanisms belonging to a certain class of linear
regressions with errors that are independent and identically
normally distributed. He compares the variable selection criteria
AIC (Akaike information criterion) and BIC (Bayesian information
criterion) using the following type of comparison. For each
fixed possible data–generating mechanism, these criteria
are compared as the data length increases. The results of this
comparison have been interpreted as meaning that, in the context
of the data-generating mechanisms considered by Shibata, AIC
is better than BIC for large data lengths. Shibata's
comparison is pointwise in the space of data–generating
mechanisms (as the data length increases). Such comparisons
are potentially misleading. We consider a simple class of
data-generating mechanisms satisfying Shibata's assumptions
and carry out a different type of comparison. For each fixed
data length (possibly large) we compare the variable selection
criteria for every possible data-generating mechanism in this
class. According to this comparison, for this class of
data-generating mechanisms no matter how large the data length
AIC is not better than BIC.
KERNEL AND BANDWIDTH SELECTION, PREWHITENING, AND THE
PERFORMANCE OF THE FULLY MODIFIED LEAST SQUARES ESTIMATION METHOD
Authors: Christou Christina , Pittis Nikitas
Published: November 2002

This paper examines several practical issues regarding the
implementation of the Phillips and Hansen fully modified least
squares (FMLS) method for the estimation of a cointegrating
vector. Various versions of this method arise by selecting between
standard and prewhitened kernel estimation and between parametric
and nonparametric automatic bandwidth estimators and also among
alternative kernels. A Monte Carlo study is conducted to
investigate the finite-sample properties of the alternative
versions of the FMLS procedure. The results suggest that the
prewhitened kernel estimator of Andrews and Monahan (1992,
Econometrica 60, 953–966) in which the bandwidth
parameter is selected via the nonparametric procedure of Newey
and West (1994, Review of Economic Studies 61,
631–653) minimizes the second-order asymptotic bias effects.
EQUIVALENCE OF THE HIGHER ORDER ASYMPTOTIC EFFICIENCY OF
k-STEP AND EXTREMUM STATISTICS
Authors: Andrews Donald W.K.
Published: November 2002

It is well known that a one-step scoring estimator that starts
from any N1/2-consistent estimator has the same
first-order asymptotic efficiency as the maximum likelihood estimator.
This paper extends this result to k-step estimators and
test statistics for k ≥ 1, higher order asymptotic
efficiency, and general extremum estimators and test statistics.

The paper shows that a k-step estimator has the same
higher order asymptotic efficiency, to any given order, as the
extremum estimator toward which it is stepping, provided (i)
k is sufficiently large, (ii) some smoothness and moment
conditions hold, and (iii) a condition on the initial estimator
holds.

For example, for the Newton–Raphson k-step
estimator based on an initial estimator in a wide class, we
obtain asymptotic equivalence to integer order s provided
2k ≥ s + 1. Thus, for k = 1, 2,
and 3, one obtains asymptotic equivalence to first, third, and seventh
orders, respectively. This means that the maximum differences between
the probabilities that the (N1/2-normalized)
k-step and extremum estimators lie in any convex set
are o(1), o(N−3/2), and
o(N−3), respectively.
ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR
FOR REGRESSIONS WITH UNSTABLE REGRESSORS
Authors: SHIN DONG WAN , OH MAN SUK
Published: November 2002

For regression models with general unstable regressors having
characteristic roots on the unit circle and general stationary
errors independent of the regressors, sufficient conditions
are investigated under which the ordinary least squares estimator
(OLSE) is asymptotically efficient in that it has the same limiting
distribution as the generalized least squares estimator (GLSE)
under the same normalization. A key condition for the asymptotic
efficiency of the OLSE is that one multiplicity of a characteristic
root of the regressor process is strictly greater than the
multiplicities of the other roots. Under this condition, the
covariance matrix Γ of the errors and the regressor matrix
X are shown to satisfy a relationship
(ΓX = XC + V for some matrix
C) for V asymptotically dominated by X,
which is analogous to the condition (ΓX = XC
for some matrix C) for numerical equivalence of the
OLSE and the GLSE.
ASYMPTOTIC THEORY FOR SOME HIGH BREAKDOWN POINT ESTIMATORS
Authors: Zinde-Walsh Victoria
Published: November 2002

High breakdown point estimators in regression are robust against
gross contamination in the regressors and also in the errors;
the least median of squares (LMS) estimator has the additional
property of packing the majority of the sample most tightly
around the estimated regression hyperplane in terms of absolute
deviations of the residuals and thus is helpful in identifying
outliers. Asymptotics for a class of high breakdown point smoothed
LMS estimators are derived here under a variety of conditions
that allow for time series applications; joint limit processes
for several smoothed estimators are examined. The limit process
for the LMS estimator is represented via a generalized Gaussian
process that defines the generalized derivative of the Wiener
process.
Introduction to AIEDAM
Authors: BROWN DAVID C.
Published: November 2002

I am very pleased to have been appointed to be the new Editor
of the AIEDAM journal: only the third in its 15 years
of existence. My involvement with AIEDAM started early
in the life of the journal, due to my professional interactions
with Professor Clive Dym, its first Editor. Clive put the journal
on a very sound footing, and set the high standards that the
journal continues to uphold. That it has maintained such a high
reputation in the fields that it covers is due to Professor
William Birmingham, the second Editor. My goal is to continue
with the policies developed by these two prior Editors, while
striving to raise the journal's standards, reputation,
and visibility even further.
Visual typology in design: A computational view
Authors: CASAKIN HERNAN , DAI WEI
Published: November 2002

This paper investigates the use of typological knowledge in
the visual modality through a computer framework that combines
multidisciplinary technologies from computer science, that is,
artificial intelligence, software engineering, database system,
and programming language, to help provide solutions and services
to building designers. The solving of design problems frequently
involves visual thinking, which has to do with the intensive
use of visual knowledge like pictures, images, and other types
of visual displays. The recognized power of typological knowledge
in design problem solving is applied to support the exploration
of a diversity of possible design solutions represented in a
pictorial mode. The innovative use of computer science technologies
enables a smooth link of visual typological knowledge with the
design goals. Within the framework, a core technology was designed
to respond to a designer's specific needs through dynamic
user viewpoint generation, so that design solutions are associated
with relevant (retrieved) visual typologies from the knowledge
base. This has been achieved in a two-way process, in which
the designer establishes an interactive dialogue with an
experimental computerized framework.
Solving the 0/1 knapsack problem using an adaptive genetic
algorithm
Authors: EZZIANE ZOHEIR
Published: November 2002

Probabilistic and stochastic algorithms have been used to solve
many hard optimization problems since they can provide solutions
to problems where often standard algorithms have failed. These
algorithms basically search through a space of potential solutions
using randomness as a major factor to make decisions. In this
research, the knapsack problem (optimization problem) is solved
using a genetic algorithm approach. Subsequently, comparisons
are made with a greedy method and a heuristic algorithm. The
knapsack problem is recognized to be NP-hard. Genetic algorithms
are among search procedures based on natural selection and natural
genetics. They randomly create an initial population of
individuals. Then, they use genetic operators to yield new
offspring. In this research, a genetic algorithm is used to
solve the 0/1 knapsack problem. Special consideration is given
to the penalty function where constant and self-adaptive penalty
functions are adopted.
Vehicle route-sequence planning using temporal logic
Authors: SEOW KIAM TIAN , PASQUIER MICHEL
Published: November 2002

This paper proposes a new logical framework for vehicle
route-sequence planning of passenger travel requests. Each request
is a fetch-and-send service task associated with
two request-locations, namely, a source and a destination. The
proposed framework is developed using propositional linear time
temporal logic of Manna and Pnueli. The novelty lies in the
use of the formal language for both the specification and
theorem-proving analysis of precedence constraints among the
location visits that are inherent in route sequences. In the
framework, legal route sequences—each of which visits
every request location once and only once in the precedence
order of fetch-and-send associated with every such request—is
formalized and justified, forming a basis upon which the link
between a basic precedence constraint and the corresponding
canonical forbidden-state formula is formally established. Over
a given base route plan, a simple procedure to generate a feasible
subplan based on a specification of the forbidden-state canonical
form is also given. An example demonstrates how temporal logic
analysis and the proposed procedure can be applied to select
a final (feasible) subplan based on additional precedence constraints.
Design of combinational logic circuits through an evolutionary
multiobjective optimization approach
Authors: COELLO COELLO CARLOS A. , AGUIRRE ARTURO HERNÁNDEZ
Published: November 2002

In this paper, we propose a population-based evolutionary
multiobjective optimization approach to design combinational
circuits. Our results indicate that the proposed approach can
significantly reduce the computational effort required by a
genetic algorithm (GA) to design circuits at a gate level while
generating equivalent or even better solutions (i.e., circuits
with a lower number of gates) than a human designer or even
other GAs. Several examples taken from the literature are used
to evaluate the performance of the proposed approach.
CoMem: Designing an interaction experience for reuse of rich
contextual knowledge from a corporate memory
Authors: FRUCHTER R. , DEMIAN P.
Published: November 2002

Managing and reusing knowledge in architecture, engineering,
and construction firms can lead to greater competitive advantage,
improved designs, and more effective management of constructed
facilities. However, reuse often fails because knowledge is
not captured; it is captured out of context, rendering it not
reusable; or there are no formal mechanisms for finding and
retrieving reusable knowledge. This paper presents ongoing research
on design knowledge reuse that introduces the notion of knowledge
in context from a corporate perspective. We argue that in order
for knowledge to be reusable, the user should be able to see
the rich context in which this knowledge was originally created
and interact with it. We call a repository of such knowledge
in context the corporate memory. We describe empirical observations
of designers reusing knowledge from their personal design
experiences. Based on these observations, we formalize two key
activities in the process of knowledge reuse from a corporate
repository: finding reusable items and understanding these items
in context. We formalize six degrees of exploration that lead
to understanding. We describe a prototype system, CoMem, that
supports these activities. CoMem is distinguished from the
document-centric state of practice solutions by its approach
of “overview first, zoom and filter, and then details
on demand.” In order to accomplish this approach we propose
three metaphors: corporate map, fisheye lens, and storyteller.
These metaphors and their implementation in CoMem are illustrated
using an industry scenario.
Drawing marks, acts, and reacts: Toward a computational
sketching interface for architectural design
Authors: DO ELLEN YI-LUEN
Published: November 2002

Architects use sketching and diagramming in their design process
to perform functional reasoning, formal arrangements, analogy
transfer, structure mapping, and knowledge acquisition. This
paper describes a research framework of the author's efforts
in the studies of design drawings and the building of computational
sketching tools to support the early conceptual design process
in architecture. The first part of the paper discusses empirical
studies conducted to determine or guess a designer's thought
process from sketches and thus identifies domain-specific graphical
symbols. It proposes a reasoning process framework of drawing
marks, acts, and reacts. The second part of the paper illustrates
how design support tools could be developed based on these concepts
and describes the various applications of the study, such as
indexing and retrieving of design drawings or images based on
the recognition of geometric shapes and the spatial relationships
among them.
Creation of flexible graphical user interfaces through model
composition
Authors: RAPHAEL B. , BHATNAGAR G. , SMITH I.F.C.
Published: November 2002

Nearly all software products have rigid and predefined interfaces.
Users are usually unable to modify or customize features beyond
cosmetic aspects. Interface adaptability is important because
aspects such as user preferences and task sequences vary widely
in engineering, even within specialized domains. A methodology
for the creation of adaptable user interfaces using model
composition is presented in this paper. User interfaces are
generated dynamically through the composition of model fragments
that are stored in a fragment library. When fragments are linked
to models of physical behavior, interface model composition
applications are likely to be easier to extend and maintain
than traditional graphical user interfaces. A prototype system
within the domain of bridge diagnosis illustrates the potential
for practical applications.
Improving problem definition through interactive evolutionary
computation
Authors: PARMEE I.C.
Published: November 2002

Poor definition and uncertainty are primary characteristics
of conceptual design processes. During the initial stages of
these generally human-centric activities, little knowledge
pertaining to the problem at hand may be available. The degree
of problem definition will depend on information available in
terms of appropriate variables, constraints, and both quantitative
and qualitative objectives. Typically, the problem space develops
with information gained in a dynamical process in which design
optimization plays a secondary role, following the establishment
of a sufficiently well-defined problem domain. This paper
concentrates on background human–computer interaction
relating to the machine-based generation of high-quality design
information that, when presented in an appropriate manner to
the designer, supports a better understanding of a problem domain.
Knowledge gained from such information combined with the
experiential knowledge of the designer can result in a
reformulation of the problem, providing increased definition
and greater confidence in the machine-based representation.
Conceptual design domains related to gas turbine blade cooling
systems and a preliminary air frame configuration are introduced.
These are utilized to illustrate the integration of interactive
evolutionary strategies that support the extraction of optimal
design information, its presentation to the designer, and
subsequent human-based modification of the design domain based
on knowledge gained from the information received. An experimental
iterative designer or evolutionary search process resulting
in a better understanding of the problem and improved machine-based
representation of the design domain is thus established.
Structural monitoring using engineer–computer interaction
Authors: STALKER RUTH , SMITH IAN F.C.
Published: November 2002

Engineer–computer interaction (ECI) is a new subdomain
of human–computer interaction that is specifically tailored
to engineers' needs. ECI uses an information classification
schema, provides a modular approach to task decomposition, and
integrates standard engineering characteristics and working
procedures into software. A software tool kit that interprets
monitoring data taken from bridges was developed according to
ECI guidelines. This tool kit was given to engineers for testing
and evaluation. An empirical evaluation using questionnaires
was performed. The results show that this ECI software corresponds
to engineers' needs and the ECI approach has potential
applications to other engineering tasks.
The absent interface in design engineering
Authors: LECLERCQ PIERRE , JUCHMES ROLAND
Published: November 2002

In order to respond to the difficulties encountered by CAD
software applications in really assisting the conceptual designer,
we propose a tool that is capable of interpreting design sketches
and feeding data to various project evaluators, right from the
early phases in the design process. For that purpose, we use
the concept of the absent interface, which is the only interface
that is compatible with the cognitive process involved in
sketching. In this paper, we present the principles of such
an interface, illustrated by EsQUIsE, a software prototype for
capturing and interpreting architectural sketches, which has
been under development for several years.
No zero match browsing of hierarchically categorized information
entities
Authors: McMAHON CHRIS , CROSSLAND ROSE , LOWE ALISTAIR , SHAH TULAN , WILLIAMS JON SIMS , CULLEY STEVE
Published: November 2002

The two main ways to search for information in electronic document
collections are by using free-text retrieval search engines
or browsing information that has been organized into predefined
organizational structures. However, each of these approaches
has limitations. Using word or phrase search, users are faced
with a compromise between overly broad searches returning an
excessive amount of information or overly narrow searches that
may fail to return relevant information. Browsing organizational
structures is dependent on the user's knowledge of the
structures, and a user may find it difficult to refine searches.
This paper introduces a user interface based approach to the
browsing of hierarchically organized information entities that
avoids these problems by allowing the incremental narrowing
down of a set of search results and by pruning the organizational
structure after each user selection to show the consequences
of the selection. The effect is to present to the user at all
times only that part of the organizational structure that will
lead to a nonnull selection. The approach is called no zero
match (NZM) browsing. The paper presents the computational basis
of NZM browsing before describing a trial implementation of
the approach and presenting three case studies, which represent
common search situations in an engineering context.
Preschool children with disruptive behavior: Three-year outcome as a function of adaptive
disability
Authors: BARKLEY RUSSELL A. , SHELTON TERRI L. , CROSSWAIT CHERYL , MOOREHOUSE MAUREEN , FLETCHER KENNETH , BARRETT SUSAN , JENKINS LUCY , METEVIA LORI
Published: November 2002

A significant discrepancy between intelligence and daily adaptive functioning, or adaptive
disability (AD), has been previously found to be a associated with significant psychological
morbidity in preschool children with disruptive behavior (DB). The utility of AD as a predictor of
later developmental risks was examined in a 3-year longitudinal study of normal ( N=
43) and DB preschool children. The DB children were grouped into those with AD (DB+AD; N = 28) and those without AD (DB-only; N = 98). All children were
followed with annual evaluations to the end of second grade. Both DB groups demonstrated
substantial and pervasive psychological and educational morbidity at 3-year follow-up. In
comparison to DB-only children, DB+AD children had more symptoms of attention-deficit
hyperactivity disorder (ADHD) and conduct disorder (CD), more severe and pervasive behavior
problems at home, more parent-rated externalizing and internalizing, and lower academic
competence and more behavioral problems at school. Parents of DB+AD children also reported
greater parenting stress than did parents in the other groups. A significant contribution of AD to
adverse outcomes in the DB group remained on some measures even after controlling for initial
severity of DB. AD also contributed significantly to CD symptoms at follow-up after controlling
for initial DB severity and initial CD symptoms. The results corroborate and extend earlier
findings of the utility of AD as a risk indicator above severity of DB alone. They also imply that
AD in the context of normal intellectual development may arise from both the deficient
self-regulation associated with ADHD and from disrupted parenting, with exposure to
kindergarten moderating these adverse effects.
A longitudinal analysis of patterns of adjustment following peer victimization
Authors: HANISH LAURA D. , GUERRA NANCY G.
Published: November 2002

This study examined the effects of being victimized by peers on children's behavioral,
social, emotional, and academic functioning. We assessed an ethnically diverse sample of 2,064
first, second, and fourth graders and followed them over 2 years, locating 1,469 of the
participants at the follow-up. Correlation and partial correlation analyses revealed that prior
victimization predicted externalizing, internalizing, and social problems 2 years later for the
sample as a whole. However, not all victimized children experienced the same types of outcomes;
instead, there was heterogeneity in children's responses to victimization. Using cluster
analysis, we identified eight outcome patterns that represented different patterns of functioning.
These were labeled as externalizing, internalizing, symptomatic, popular, disliked, absent, low
achieving, and high achieving. Discriminant function analyses revealed that the symptomatic,
externalizing, and disliked patterns were systematically related to victimization. Moreover,
significant gender and age differences in the severity of effects were obtained. The discussion
highlights the complexity of victimization effects.
Peer to peer sexual harassment in early adolescence: A developmental perspective
Authors: MCMASTER LOREN E. , CONNOLLY JENNIFER , PEPLER DEBRA , CRAIG WENDY M.
Published: November 2002

The goal of this study was to examine sexual harassment in early adolescence. Available data
indicate that peer to peer sexual harassment is prevalent in high school and is associated with
psychosocial problems for both victims and perpetrators. For the present study, we adopted a
developmental contextual model to examine the possibility that this behavior develops during the
late elementary and middle school years and is linked to the biological and social changes that
occur at this time. Youths from Grades 6–8 (N = 1,213) enrolled in seven
elementary and middle schools in a large south-central Canadian city were asked to report on their
sexual harassment behaviors with same- and cross-gender peers; their pubertal development, and
the gender composition of their peer network. The results revealed that cross-gender harassment
was distinct from same-gender harassment, increased in frequency from Grade 6 to Grade 8, and
was linked to pubertal maturation and participation in mixed-gender peer groups. The implications
of a developmental contextual model for understanding the emergence of this problematic
behavior in adolescence are discussed.
Response decision processes and externalizing behavior problems in adolescents
Authors: FONTAINE REID GRIFFITH , BURKS VIRGINIA SALZER , DODGE KENNETH A.
Published: November 2002

Externalizing behavior problems of 124 adolescents were assessed across Grades
7–11. In Grade 9, participants were also assessed across social-cognitive domains after
imagining themselves as the object of provocations portrayed in six videotaped vignettes.
Participants responded to vignette-based questions representing multiple processes of the
response decision step of social information processing. Phase 1 of our investigation supported a
two-factor model of the response evaluation process of response decision (response valuation and
outcome expectancy). Phase 2 showed significant relations between the set of these response
decision processes, as well as response selection, measured in Grade 9 and (a) externalizing
behavior in Grade 9 and (b) externalizing behavior in Grades 10–11, even after controlling
externalizing behavior in Grades 7–8. These findings suggest that on-line behavioral
judgments about aggression play a crucial role in the maintenance and growth of aggressive
response tendencies in adolescence.
Prediction of peer-rated adult hostility from autonomy struggles in adolescent–family
interactions
Authors: ALLEN JOSEPH P. , HAUSER STUART T. , O'CONNOR THOMAS G. , BELL KATHY L.
Published: November 2002

Observed parent–adolescent autonomy struggles were assessed as potential predictors
of the development of peer-rated hostility over a decade later in young adulthood in both normal
and previously psychiatrically hospitalized groups of adolescents. Longitudinal, multireporter data
were obtained by coding family interactions involving 83 adolescents and their parents at age 16
years and then obtaining ratings by close friends of adolescents' hostility at age 25 years.
Fathers' behavior undermining adolescents' autonomy in interactions at age 16 years
were predictive of adolescents-as-young-adults' hostility, as rated by close friends at age 25
years. These predictions contributed additional variance to understanding young adult hostility
even after accounting for concurrent levels of adolescent hostility at age 16 years and paternal
hostility at this age, each of which also significantly contributed to predicting future hostility.
Results are discussed as highlighting a pathway by which difficulties attaining autonomy in
adolescence may presage the development of long-term difficulties in social functioning.