18 research outputs found
Complementarity in classical dynamical systems
The concept of complementarity, originally defined for non-commuting
observables of quantum systems with states of non-vanishing dispersion, is
extended to classical dynamical systems with a partitioned phase space.
Interpreting partitions in terms of ensembles of epistemic states (symbols)
with corresponding classical observables, it is shown that such observables are
complementary to each other with respect to particular partitions unless those
partitions are generating. This explains why symbolic descriptions based on an
\emph{ad hoc} partition of an underlying phase space description should
generally be expected to be incompatible. Related approaches with different
background and different objectives are discussed.Comment: 18 pages, no figure
Extranets of National Tourist Organisations: The Internet and planned Extranet Web-site of the Danish Tourist Board — compared with existing or planned Extranets of Australia, Austria and Norway
The sampling volume of trawl and acoustics: estimating availability probabilities from observations of tracked individual fish
The Internet in Competition with the Traditional Information Sources - A Study of Vacation Planning for Package vs. Non-Package Travel
Understanding the Willingness to Participate in Mobile Surveys: Exploring the Role of Utilitarian, Affective, Hedonic, Social, Self-Expressive, and Trust-Related Factors
Can the precision of bottom trawl indices be increased by using simultaneously collected acoustic data? The Barents Sea experience
Functional-coefficient regression models for nonlinear time series
The local linear regression technique is applied to estimation of functional-coefficient regression models for time series data. The models include threshold autoregressive models and functional-coefficient autoregressive models as special cases but with the added advantages such as depicting finer structure of the underlying dynamics and better postsample forecasting performance. Also proposed are a new bootstrap test for the goodness of fit of models and a bandwidth selector based on newly defined cross-validatory estimation for the expected forecasting errors. The proposed methodology is data-analytic and of sufficient flexibility to analyze complex and multivariate nonlinear structures without suffering from the “curse of dimensionality.” The asymptotic properties of the proposed estimators are investigated under the α-mixing condition. Both simulated and real data examples are used for illustration