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Simplest Model (simplest + model)

Distribution by Scientific Domains

Chemistry	40%

Selected Abstracts

Non-parametric statistical methods for multivariate calibration model selection and comparison,

JOURNAL OF CHEMOMETRICS, Issue 12 2003
Edward V. Thomas
Abstract Model selection is an important issue when constructing multivariate calibration models using methods based on latent variables (e.g. partial least squares regression and principal component regression). It is important to select an appropriate number of latent variables to build an accurate and precise calibration model. Inclusion of too few latent variables can result in a model that is inaccurate over the complete space of interest. Inclusion of too many latent variables can result in a model that produces noisy predictions through incorporation of low-order latent variables that have little or no predictive value. Commonly used metrics for selecting the number of latent variables are based on the predicted error sum of squares (PRESS) obtained via cross-validation. In this paper a new approach for selecting the number of latent variables is proposed. In this new approach the prediction errors of individual observations (obtained from cross-validation) are compared across models incorporating varying numbers of latent variables. Based on these comparisons, non-parametric statistical methods are used to select the simplest model (least number of latent variables) that provides prediction quality that is indistinguishable from that provided by more complex models. Unlike methods based on PRESS, this new approach is robust to the effects of anomalous observations. More generally, the same approach can be used to compare the performance of any models that are applied to the same data set where reference values are available. The proposed methodology is illustrated with an industrial example involving the prediction of gasoline octane numbers from near-infrared spectra. Published in 2004 by John Wiley & Sons, Ltd. [source]

Further Reflections on the Corn,Guano Model

METROECONOMICA, Issue 3 2001
Christian Bidard
The corn,guano model is the simplest model with exhaustible resources. On the constant rate of profit hypothesis, a change of the numeraire from corn to corn-and-labour affects the price trajectories. In particular, the corn price at the exhaustion date is no longer equal to its long-term level. The system of intertemporal prices admits one degree of freedom. Only one path, called the natural path, admits a positive price, wage and royalty for any number of periods before exhaustion. But, for a given exhaustion date, the non-natural paths close to it are also associated with positive prices, wages and royalties. In this paper we study the characteristics of the natural path and the properties of the non-natural paths. The results are partly extended to multisector models. [source]

Quantitative Aggregation,Activity Relationship (QAAR): Supermolecular View, Dimer as the Simplest Aggregation State and Monomolecule

MOLECULAR INFORMATICS, Issue 6 2007
Feng Fan
Abstract Aggregation state of bioactive compounds plays a key role in its bio-interactive procedure. In this paper, based on the structural information of dimers, the simplest model of aggregation state, classical QSAR, was used for the investigation of the relationship between aggregation state and bioactivity. Aided by the template of crystal structure of Teflubenzuron, two dimer descriptors of ,E and ,Rg which could describe parts of the aggregation state characters were used to establish the models. QSAR research implicates that the bioactivity may strongly depend on the molecular aggregation state. [source]

Hitting time of large subsets of the hypercube

RANDOM STRUCTURES AND ALGORITHMS, Issue 2 2008
erný
Abstract We study the simple random walk on the n -dimensional hypercube, in particular its hitting times of large (possibly random) sets. We give simple conditions on these sets ensuring that the properly rescaled hitting time is asymptotically exponentially distributed, uniformly in the starting position of the walk. These conditions are then verified for percolation clouds with densities that are much smaller than (n log n) -1. A main motivation behind this article is the study of the so-called aging phenomenon in the Random Energy Model, the simplest model of a mean-field spin glass. Our results allow us to prove aging in the REM for all temperatures, thereby extending earlier results to their optimal temperature domain. © 2008 Wiley Periodicals, Inc. Random Struct. Alg., 2008 [source]

The Gyldén-type problem revisited: More refined analytical solutions

ASTRONOMISCHE NACHRICHTEN, Issue 4 2006
A. Pal
Abstract We resume and consistently extend our previous researches concerning the Gyldén-type problem (a two-body problem with time-dependent equivalent gravitational parameter). To approach most of the concrete astronomical situations to be modelled in this way, we consider a periodic small perturbation. For the nonresonant case, we present a second-order analytical solution. For the resonant case, we adopt the most realistic astronomical situation: only one dominant term of the Hamiltonian. In this case we point out a fundamental model of resonance, common to every resonant situation, and, moreover, identical to the first fundamental model of resonance . Considering the simplest model of periodic change of the equivalent gravitational parameter, we .nd that all possible resonances are con.ned to the first fundamental model. (© 2006 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim) [source]