Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.

Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Testing for multicointegration in panel data with common factors

The paper addresses the concept of multicointegration in panel data frame- work. The proposal builds upon the panel data cointegration procedures developed in Pedroni (2004), for which we compute the moments of the parametric statistics. When individuals are either cross-section independent or cross-section dependence can be re- moved by cross-section demeaning, our approach can be applied to the wider framework of mixed I(2) and I(1) stochastic processes analysis. The paper also deals with the issue of cross-section dependence using approximate common factor models. Finite sample performance is investigated through Monte Carlo simulations. Finally, we illustrate the use of the procedure investigating inventories, sales and production relationship for a panel of US industries.

Proton emission off nuclei induced by kaons in flight

We study the (K-, p) reaction on nuclei with a 1 GeV/c momentum kaon beam, paying special attention to the region of emitted protons having kinetic energy above 600 MeV, which was used to claim a deeply attractive kaon nucleus optical potential. Our model describes the nuclear reaction in the framework of a local density approach and the calculations are performed following two different procedures: one is based on a many-body method using the Lindhard function and the other is based on a Monte Carlo simulation. The simulation method offers flexibility to account for processes other than kaon quasielastic scattering, such as K- absorption by one and two nucleons, producing hyperons, and allows consideration of final-state interactions of the K-, the p, and all other primary and secondary particles on their way out of the nucleus, as well as the weak decay of the produced hyperons into pi N. We find a limited sensitivity of the cross section to the strength of the kaon optical potential. We also show a serious drawback in the experimental setup-the requirement for having, together with the energetic proton, at least one charged particle detected in the decay counter surrounding the target-as we find that the shape of the original cross section is appreciably distorted, to the point of invalidating the claims made in the experimental paper on the strength of the kaon nucleus optical.

Elastic scattering of fast electrons and positrons by atoms

Elastic scattering of relativistic electrons and positrons by atoms is considered in the framework of the static field approximation. The scattering field is expressed as a sum of Yukawa terms to allow the use of various approximations. Accurate phase shifts have been computed by combining Bühring¿s power-series method with the WKB and Born approximations. This combined procedure allows the evaluation of differential cross sections for kinetic energies up to several tens of MeV. Numerical results are used to analyze the validity of several approximate methods, namely the first- and second-order Born approximations and the screened Mott formula, which are frequently adopted as the basis of multiple scattering theories and Monte Carlo simulations of electron and positron transport.

n=1/4 domain-growth universality class: Crossover to the n=1/2 class

The kinetic domain-growth exponent is studied by Monte Carlo simulation as a function of temperature for a nonconserved order-parameter model. In the limit of zero temperature, the model belongs to the n=(1/4 slow-growth unversality class. This is indicative of a temporal pinning in the domain-boundary network of mixed-, zero-, and finite-curvature boundaries. At finite temperature the growth kinetics is found to cross over to the Allen-Cahn exponent n=(1/2. We obtain that the pinning time of the zero-curvature boundary decreases rapidly with increasing temperature.

Effective squark/chargino/neutralino couplings: MadGraph implementation

We have included the effective description of squark interactions with charginos/neutralinos in the MadGraph MSSM model. This effective description includes the effective Yukawa couplings, and another logarithmic term which encodes the supersymmetry-breaking. We have performed an extensive test of our implementation analyzing the results of the partial decay widths of squarks into charginos and neutralinos obtained by using FeynArts/FormCalc programs and the new model file in MadGraph. We present results for the cross-section of top-squark production decaying into charginos and neutralinos.

Effective squark/chargino/neutralino couplings: MadGraph implementation

We have included the effective description of squark interactions with charginos/neutralinos in the MadGraph MSSM model. This effective description includes the effective Yukawa couplings, and another logarithmic term which encodes the supersymmetry-breaking. We have performed an extensive test of our implementation analyzing the results of the partial decay widths of squarks into charginos and neutralinos obtained by using FeynArts/FormCalc programs and the new model file in MadGraph. We present results for the cross-section of top-squark production decaying into charginos and neutralinos.

Local noise analysis of a Schottky contact: combined thermionic-emissiondiffusion theory

A theoretical model for the noise properties of Schottky barrier diodes in the framework of the thermionic-emission¿diffusion theory is presented. The theory incorporates both the noise inducedby the diffusion of carriers through the semiconductor and the noise induced by the thermionicemission of carriers across the metal¿semiconductor interface. Closed analytical formulas arederived for the junction resistance, series resistance, and contributions to the net noise localized indifferent space regions of the diode, all valid in the whole range of applied biases. An additionalcontribution to the voltage-noise spectral density is identified, whose origin may be traced back tothe cross correlation between the voltage-noise sources associated with the junction resistance andthose for the series resistance. It is argued that an inclusion of the cross-correlation term as a newelement in the existing equivalent circuit models of Schottky diodes could explain the discrepanciesbetween these models and experimental measurements or Monte Carlo simulations.

Local noise analysis of a Schottky contact: combined thermionic-emissiondiffusion theory

A theoretical model for the noise properties of Schottky barrier diodes in the framework of the thermionic-emission¿diffusion theory is presented. The theory incorporates both the noise inducedby the diffusion of carriers through the semiconductor and the noise induced by the thermionicemission of carriers across the metal¿semiconductor interface. Closed analytical formulas arederived for the junction resistance, series resistance, and contributions to the net noise localized indifferent space regions of the diode, all valid in the whole range of applied biases. An additionalcontribution to the voltage-noise spectral density is identified, whose origin may be traced back tothe cross correlation between the voltage-noise sources associated with the junction resistance andthose for the series resistance. It is argued that an inclusion of the cross-correlation term as a newelement in the existing equivalent circuit models of Schottky diodes could explain the discrepanciesbetween these models and experimental measurements or Monte Carlo simulations.

Creating and using a non-dedicated HPC cluster with ParallelKnoppix

This note describes ParallelKnoppix, a bootable CD that allows econometricians with average knowledge of computers to create and begin using a high performance computing cluster for parallel computing in very little time. The computers used may be heterogeneous machines, and clusters of up to 200 nodes are supported. When the cluster is shut down, all machines are in their original state, so their temporary use in the cluster does not interfere with their normal uses. An example shows how a Monte Carlo study of a bootstrap test procedure may be done in parallel. Using a cluster of 20 nodes, the example runs approximately 20 times faster than it does on a single computer.

User-friendly parallel computations with econometric examples

This paper shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of parallelization is done in a way such that an investigator may use the programs without any knowledge of parallel programming. A bootable CD that allows rapid creation of a cluster for parallel computing is introduced. Examples show that parallelization can lead to important reductions in computational time. Detailed discussion of how the Monte Carlo problem was parallelized is included as an example for learning to write parallel programs for Octave.

Sensitivity of simulation results to competing SAM updates

Recently there has been a renewed research interest in the properties of non survey updates of input-output tables and social accounting matrices (SAM). Along with the venerable and well known scaling RAS method, several alternative new procedures related to entropy minimization and other metrics have been suggested, tested and used in the literature. Whether these procedures will eventually substitute or merely complement the RAS approach is still an open question without a definite answer. The performance of many of the updating procedures has been tested using some kind of proximity or closeness measure to a reference input-output table or SAM. The first goal of this paper, in contrast, is the proposal of checking the operational performance of updating mechanisms by way of comparing the simulation results that ensue from adopting alternative databases for calibration of a reference applied general equilibrium model. The second goal is to introduce a new updatin! g procedure based on information retrieval principles. This new procedure is then compared as far as performance is concerned to two well-known updating approaches: RAS and cross-entropy. The rationale for the suggested cross validation is that the driving force for having more up to date databases is to be able to conduct more current, and hopefully more credible, policy analyses.

A proposal for a new specification for a conditionally heteroskedastic variance model: the Quadratic Moving-Average Conditional Heteroskedasticity and an application to the D. Mark-U.S. dollar Exchange Rate

Ever since the appearance of the ARCH model [Engle(1982a)], an impressive array of variance specifications belonging to the same class of models has emerged [i.e. Bollerslev's (1986) GARCH; Nelson's (1990) EGARCH]. This recent domain has achieved very successful developments. Nevertheless, several empirical studies seem to show that the performance of such models is not always appropriate [Boulier(1992)]. In this paper we propose a new specification: the Quadratic Moving Average Conditional heteroskedasticity model. Its statistical properties, such as the kurtosis and the symmetry, as well as two estimators (Method of Moments and Maximum Likelihood) are studied. Two statistical tests are presented, the first one tests for homoskedasticity and the second one, discriminates between ARCH and QMACH specification. A Monte Carlo study is presented in order to illustrate some of the theoretical results. An empirical study is undertaken for the DM-US exchange rate.

Estimation of dynamic latent variable models using simulated nonparametric moments

Given a model that can be simulated, conditional moments at a trial parameter value can be calculated with high accuracy by applying kernel smoothing methods to a long simulation. With such conditional moments in hand, standard method of moments techniques can be used to estimate the parameter. Since conditional moments are calculated using kernel smoothing rather than simple averaging, it is not necessary that the model be simulable subject to the conditioning information that is used to define the moment conditions. For this reason, the proposed estimator is applicable to general dynamic latent variable models. Monte Carlo results show that the estimator performs well in comparison to other estimators that have been proposed for estimation of general DLV models.