24,464 research outputs found
Statistical Methods for the Qualitative Assessment of Dynamic Models with Time Delay (R Package qualV)
Results of ecological models differ, to some extent, more from measured data than from empirical knowledge. Existing techniques for validation based on quantitative assessments sometimes cause an underestimation of the performance of models due to time shifts, accelerations and delays or systematic differences between measurement and simulation. However, for the application of such models it is often more important to reproduce essential patterns instead of seemingly exact numerical values. This paper presents techniques to identify patterns and numerical methods to measure the consistency of patterns between observations and model results. An orthogonal set of deviance measures for absolute, relative and ordinal scale was compiled to provide informations about the type of difference. Furthermore, two different approaches accounting for time shifts were presented. The first one transforms the time to take time delays and speed differences into account. The second one describes known qualitative criteria dividing time series into interval units in accordance to their main features. The methods differ in their basic concepts and in the form of the resulting criteria. Both approaches and the deviance measures discussed are implemented in an R package. All methods are demonstrated by means of water quality measurements and simulation data. The proposed quality criteria allow to recognize systematic differences and time shifts between time series and to conclude about the quantitative and qualitative similarity of patterns.
Spectral Simplicity of Apparent Complexity, Part I: The Nondiagonalizable Metadynamics of Prediction
Virtually all questions that one can ask about the behavioral and structural
complexity of a stochastic process reduce to a linear algebraic framing of a
time evolution governed by an appropriate hidden-Markov process generator. Each
type of question---correlation, predictability, predictive cost, observer
synchronization, and the like---induces a distinct generator class. Answers are
then functions of the class-appropriate transition dynamic. Unfortunately,
these dynamics are generically nonnormal, nondiagonalizable, singular, and so
on. Tractably analyzing these dynamics relies on adapting the recently
introduced meromorphic functional calculus, which specifies the spectral
decomposition of functions of nondiagonalizable linear operators, even when the
function poles and zeros coincide with the operator's spectrum. Along the way,
we establish special properties of the projection operators that demonstrate
how they capture the organization of subprocesses within a complex system.
Circumventing the spurious infinities of alternative calculi, this leads in the
sequel, Part II, to the first closed-form expressions for complexity measures,
couched either in terms of the Drazin inverse (negative-one power of a singular
operator) or the eigenvalues and projection operators of the appropriate
transition dynamic.Comment: 24 pages, 3 figures, 4 tables; current version always at
http://csc.ucdavis.edu/~cmg/compmech/pubs/sdscpt1.ht
ABC of multi-fractal spacetimes and fractional sea turtles
We clarify what it means to have a spacetime fractal geometry in quantum
gravity and show that its properties differ from those of usual fractals. A
weak and a strong definition of multi-scale and multi-fractal spacetimes are
given together with a sketch of the landscape of multi-scale theories of
gravitation. Then, in the context of the fractional theory with
-derivatives, we explore the consequences of living in a multi-fractal
spacetime. To illustrate the behavior of a non-relativistic body, we take the
entertaining example of a sea turtle. We show that, when only the time
direction is fractal, sea turtles swim at a faster speed than in an ordinary
world, while they swim at a slower speed if only the spatial directions are
fractal. The latter type of geometry is the one most commonly found in quantum
gravity. For time-like fractals, relativistic objects can exceed the speed of
light, but strongly so only if their size is smaller than the range of
particle-physics interactions. We also find new results about log-oscillating
measures, the measure presentation and their role in physical observations and
in future extensions to nowhere-differentiable stochastic spacetimes.Comment: 20 pages, 1 figure. v2: typos corrected, minor improvements of the
tex
Cortical spatio-temporal dimensionality reduction for visual grouping
The visual systems of many mammals, including humans, is able to integrate
the geometric information of visual stimuli and to perform cognitive tasks
already at the first stages of the cortical processing. This is thought to be
the result of a combination of mechanisms, which include feature extraction at
single cell level and geometric processing by means of cells connectivity. We
present a geometric model of such connectivities in the space of detected
features associated to spatio-temporal visual stimuli, and show how they can be
used to obtain low-level object segmentation. The main idea is that of defining
a spectral clustering procedure with anisotropic affinities over datasets
consisting of embeddings of the visual stimuli into higher dimensional spaces.
Neural plausibility of the proposed arguments will be discussed
FRACTAL GEOMETRY IN AGRICULTURAL CASH PRICE DYNAMICS
Agricultural prices are determined by natural and socio-economic factors that are known to be self-similar at different time scales and to follow non-periodic cyclical patterns. These properties are most easily understood using Mandelbrot's fractal geometry, in which a jagged time series is treated as a jagged coastline or any other natural phenomenon. The fractal market hypothesis provides the theory needed to explain why fractal structure exists in agricultural prices. Empirical evidence confirms theoretical predictions.Demand and Price Analysis,
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