1,959 research outputs found
Testing hypothesis on stability of expected value and variance
The simple samples are independently taken from normal distribution. The two functions of the sample means and sample variances are considered. The density functions of these two statistics have been derived. These statistics can be applied for verifying the hypothesis on stability of expected value and variance of normal distribution considered, e.g., in statistical process control. The critical values for these statistics have been found using numerical integration. The tables with approximated critical values of these statistics have been presented.density function, sample variance, test statistic, numerical integration, statistical process control
Regime variance testing - a quantile approach
This paper is devoted to testing time series that exhibit behavior related to
two or more regimes with different statistical properties. Motivation of our
study are two real data sets from plasma physics with observable two-regimes
structure. In this paper we develop estimation procedure for critical point of
division the structure change of a time series. Moreover we propose three tests
for recognition such specific behavior. The presented methodology is based on
the empirical second moment and its main advantage is lack of the distribution
assumption. Moreover, the examined statistical properties we express in the
language of empirical quantiles of the squared data therefore the methodology
is an extension of the approach known from the literature. The theoretical
results we confirm by simulations and analysis of real data of turbulent
laboratory plasma
Note on the luminosity distance
We re-derive a formula relating the areal and luminosity distances, entirely
in the framework of the classical Maxwell theory, assuming a geometric-optics
type condition.Comment: Section 4 revised, misprints correcte
The Social Engagement as a Source of Innovation
Innovation, innovation economy, innovation management are all crucial
issues in both theory and practice of management. The purpose of this paper
is to provide mechanisms for the use of corporate community involvement in
public affairs as a source of innovation for both business organizations and in
relation to ways of solving social problems and pursuing public purposes. The
use of business engagement in social affairs as a source and inspiration for
innovation and the mechanisms of responsible use of that business engagement
by community and public organizations were analyzed. Companies have
discovered that social problems have their economic side and the involvement
in solving the problems of the public sector can strongly stimulate their own
business processes. The new paradigm for innovation grows in the field of
cooperation between private business and public interest, generating positive
and permanent changes for both sides. There is a strong need for the cause
social responsiveness and increased social sensitivity, not only on the side of
the business but also in public organizations
A general framework for providing interval representations of Pareto optimal outcomes for large-scale bi- and tri-criteria MIP problems
The Multi-Objective Mixed-Integer Programming (MOMIP) problem is one of the
most challenging. To derive its Pareto optimal solutions one can use the
well-known Chebyshev scalarization and Mixed-Integer Programming (MIP) solvers.
However, for a large-scale instance of the MOMIP problem, its scalarization may
not be solved to optimality, even by state-of-the-art optimization packages,
within the time limit imposed on the optimization. If a MIP solver cannot
derive the optimal solution within the assumed time limit, it provides the
optimality gap, which gauges the quality of the approximate solution. However,
for the MOMIP case, no information is provided on the lower and upper bounds of
the components of the Pareto optimal outcome. For the MOMIP problem with two
and three objective functions, an algorithm is proposed to provide the
so-called interval representation of the Pareto optimal outcome designated by
the weighting vector when there is a time limit on solving the Chebyshev
scalarization. Such interval representations can be used to navigate on the
Pareto front. The results of several numerical experiments on selected
large-scale instances of the multi-objective, multidimensional 0-1 knapsack
problem illustrate the proposed approach. The limitations and possible
enhancements of the proposed method are also discussed
The Principles of Implementing Early Recognition Systems in an Organization
In the context of the turbulent environment, contemporary organizations have
to work out and implement tools enabling them to handle the turbulence, and
primarily, to avoid negative consequences of these processes. The tools are
related, among others, to obtaining and providing managers, sufficiently
in advance, with adequate management information on the environment.
Early Recognition Systems (ERS) are a response to such conditions of the
organization functioning and the challenge in respect of information support
for decision-making processes. Unfortunately, they are mainly of informalized
character, dispersed on various levels and in various functional areas of
organizations, and very often based on unconscious, habitual actions, and,
in consequence, their advancement and effectiveness are low. Based on the
main characteristics of early recognition systems, the article presents the
framework procedure of systemic solutions in the area of early recognition,
which is supposed to enable formally organized activities within this scope
External bias in the model of isolation of communities
We extend a model of community isolation in the d-dimensional lattice onto
the case with an imposed imbalance between birth rates of competing
communities. We give analytical and numerical evidences that in the asymmetric
two-specie model there exists a well defined value of the asymmetry parameter
when the emergence of the isolated (blocked) subgroups is the fastest, i.e. the
characteristic time tc is minimal. This critical value of the parameter depends
only on the lattice dimensionality and is independent from the system size.
Similar phenomenon was observed in the multi-specie case with a geometric
distribution of the birth rates. We also show that blocked subgroups in the
multi-specie case are absent or very rare when either there is a strictly
dominant specie that outnumbers the others or when there is a large diversity
of species. The number of blocked species of different kinds decreases with the
dimension of the multi-specie system.Comment: 6 pages, 4 figure
A neural-network controlled dynamic evolutionary scheme for global molecular geometry optimization
A novel, neural network controlled, dynamic evolutionary algorithm is proposed for the purposes of molecular geometry optimization. The approach is tested for selected model molecules and some molecular systems of importance in biochemistry. The new algorithm is shown to compare favorably with the standard, statically parametrized memetic algorithm
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