The Analysis of interval censoring and double censoring via Markov chain Monte Carlo methods

L'An��lisi de la superviv��ncia s'utilitza en diferents camps per analitzar el temps transcorregut entre dos esdeveniments. El que distingeix l'an��lisi de la superviv��ncia d'altres ��rees de l'estad��stica ��s que les dades normalment estan censurades. La censura en un interval apareix quan l'esdeveniment final d'inter��s no ��s directament observable i nom��s se sap que el temps de fallada est�� en un interval concret. Un esquema de censura m��s complex encara apareix quan tant el temps inicial com el temps final estan censurats en un interval. Aquesta situaci�� s'anomena doble censura. En aquest article donem una descripci�� formal d'un m��tode bayes�� param��tric per a l'an��lisi de dades censurades en un interval i dades doblement censurades aix�� com unes indicacions clares de la seva utilitzaci�� o pr��ctica. La metodologia proposada s'ilustra amb dades d'una cohort de pacients hemof��lics que es varen infectar amb el virus VIH a principis dels anys 1980's.

Panel index VAR models: Specification, Estimation, Testing and Leading Indicators

This paper proposes a method to conduct inference in panel VAR models with cross unit interdependencies and time variations in the coefficients. The approach can be used to obtain multi-unit forecasts and leading indicators and to conduct policy analysis in a multiunit setups. The framework of analysis is Bayesian and MCMC methods are used to estimate the posterior distribution of the features of interest. The model is reparametrized to resemble an observable index model and specification searches are discussed. As an example, we construct leading indicators for inflation and GDP growth in the Euro area using G-7 information.

Estimating multi-country VAR models

This paper describes a methodology to estimate the coefficients, to test specification hypothesesand to conduct policy exercises in multi-country VAR models with cross unit interdependencies, unit specific dynamics and time variations in the coefficients. The framework of analysis is Bayesian: a prior flexibly reduces the dimensionality of the model and puts structure on the time variations; MCMC methods are used to obtain posterior distributions; and marginal likelihoods to check the fit of various specifications. Impulse responses and conditional forecasts are obtained with the output of MCMC routine. The transmission of certain shocks across countries is analyzed.

Disentangling the formation of contrasting tree line physiognomies combining model selection and Bayesian parameterization for simulation models.

Alpine tree-line ecotones are characterized by marked changes at small spatial scales that may result in a variety of physiognomies. A set of alternative individual-based models was tested with data from four contrasting Pinus uncinata ecotones in the central Spanish Pyrenees to reveal the minimal subset of processes required for tree-line formation. A Bayesian approach combined with Markov chain Monte Carlo methods was employed to obtain the posterior distribution of model parameters, allowing the use of model selection procedures. The main features of real tree lines emerged only in models considering nonlinear responses in individual rates of growth or mortality with respect to the altitudinal gradient. Variation in tree-line physiognomy reflected mainly changes in the relative importance of these nonlinear responses, while other processes, such as dispersal limitation and facilitation, played a secondary role. Different nonlinear responses also determined the presence or absence of krummholz, in agreement with recent findings highlighting a different response of diffuse and abrupt or krummholz tree lines to climate change. The method presented here can be widely applied in individual-based simulation models and will turn model selection and evaluation in this type of models into a more transparent, effective, and efficient exercise.

Monte Carlo simulation of interface alloying

An Ising-like model, with interactions ranging up to next-nearest-neighbor pairs, is used to simulate the process of interface alloying. Interactions are chosen to stabilize an intermediate "antiferromagnetic" ordered structure. The dynamics proceeds exclusively by atom-vacancy exchanges. In order to characterize the process, the time evolution of the width of the intermediate ordered region and the diffusion length is studied. Both lengths are found to follow a power-law evolution with exponents depending on the characteristic features of the model.

Monte Carlo Study of the Growth of L12 ordered domains in fcc A3B binary alloys

A Monte Carlo study of the late time growth of L12-ordered domains in a fcc A3B binary alloy is presented. The energy of the alloy has been modeled by a nearest-neighbor interaction Ising Hamiltonian. The system exhibits a fourfold degenerated ground state and two kinds of interfaces separating ordered domains: flat and curved antiphase boundaries. Two different dynamics are used in the simulations: the standard atom-atom exchange mechanism and the more realistic vacancy-atom exchange mechanism. The results obtained by both methods are compared. In particular we study the time evolution of the excess energy, the structure factor and the mean distance between walls. In the case of atom-atom exchange mechanism anisotropic growth has been found: two characteristic lengths are needed in order to describe the evolution. Contrarily, with the vacancyatom exchange mechanism scaling with a single length holds. Results are contrasted with existing experiments in Cu3Au and theories for anisotropic growth.

Magnetic microstructures from magnetic force microscopy and Monte Carlo simulation in CoFe-Ag-Cu granular films

CoFe-Ag-Cu granular films, prepared by rf sputtering, displayed magnetic domain microstructures for ferromagnetic concentrations above about 32% at, and below the percolation threshold. All samples have a fcc structure with an (111) texture perpendicular to the film plane. Magnetic force microscopy (MFM) showed a variety of magnetic domain microstructures, extremely sensitive to the magnetic history of the sample, which arise from the balance of the ferromagnetic exchange, the dipolar interactions and perpendicular magnetocrystalline anisotropy, MFM images indicate that in virgin samples, magnetic bubble domains with an out-of-plane component of the magnetization are surrounded by a quasicontinuous background of opposite magnetization domains. The application of a magnetic field in different geometries drastically modifies the microstructure of the system in the remanent state: i) for an in-plane field, the MFM images show that most of the magnetic moments are aligned along the film plane, ii) for an out-of-plane field, the MFM signal increases about one order of magnitude, and out-of-plane striped domains with alternating up and down magnetization are stabilized. Numerical simulations show that a variety of metastable domain structures (similar to those observed experimentally) can be reached, depending on magnetic history, in systems with competing perpendicular anisotropy, exchange and dipolar interactions.

Monte Carlo study of a kinetic lattice model with random diffusion of disorder

We report Monte Carlo results for a nonequilibrium Ising-like model in two and three dimensions. Nearest-neighbor interactions J change sign randomly with time due to competing kinetics. There follows a fast and random, i.e., spin-configuration-independent diffusion of Js, of the kind that takes place in dilute metallic alloys when magnetic ions diffuse. The system exhibits steady states of the ferromagnetic (antiferromagnetic) type when the probability p that J>0 is large (small) enough. No counterpart to the freezing phenomena found in quenched spin glasses occurs. We compare our results with existing mean-field and exact ones, and obtain information about critical behavior.

Monte Carlo simulation of x-ray spectra generated by kilo-electron-volt electrons

We present a general algorithm for the simulation of x-ray spectra emitted from targets of arbitrary composition bombarded with kilovolt electron beams. Electron and photon transport is simulated by means of the general-purpose Monte Carlo code PENELOPE, using the standard, detailed simulation scheme. Bremsstrahlung emission is described by using a recently proposed algorithm, in which the energy of emitted photons is sampled from numerical cross-section tables, while the angular distribution of the photons is represented by an analytical expression with parameters determined by fitting benchmark shape functions obtained from partial-wave calculations. Ionization of K and L shells by electron impact is accounted for by means of ionization cross sections calculated from the distorted-wave Born approximation. The relaxation of the excited atoms following the ionization of an inner shell, which proceeds through emission of characteristic x rays and Auger electrons, is simulated until all vacancies have migrated to M and outer shells. For comparison, measurements of x-ray emission spectra generated by 20 keV electrons impinging normally on multiple bulk targets of pure elements, which span the periodic system, have been performed using an electron microprobe. Simulation results are shown to be in close agreement with these measurements.

Simulaci��n Monte Carlo de las dosis en tumores de pulm��n en tratamientos de radioterapia estereot��xica extracraneal

Estudio elaborado a partir de una estancia en el Karolinska University Hospital, Suecia, entre marzo y junio del 2006. En la radioterapia estereot��xica extracraneal (SBRT) de tumores de pulm��n existen principalmente dos problemas en el c��lculo de la dosis con los sistemas de planificaci��n disponibles: la precisi��n limitada de los algoritmos de c��lculo en presencia de tejidos con densidades muy diferentes y los movimientos debidos a la respiraci��n del paciente durante el tratamiento. El objetivo de este trabajo ha sido llevar a cabo la simulaci��n con el c��digo Monte Carlo PENELOPE de la distribuci��n de dosis en tumores de pulm��n en casos representativos de tratamientos con SBRT teniendo en cuenta los movimientos respiratorios y su comparaci��n con los resultados de varios planificadores. Se han estudiado casos representativos de tratamientos de SBRT en el Karolinska University Hospital. Los haces de radiaci��n se han simulado mediante el c��digo PENELOPE y se han usado para la obtenci��n de los resultados MC de perfiles de dosis. Los resultados obtenidos para el caso est��tico (sin movimiento respiratorio ) ponen de manifiesto que, en comparaci��n con la MC, la dosis (Gy/MU) calculada por los planificadores en el tumor tiene una precisi��n del 2-3%. En la zona de interfase entre tumor y tejido pulmonar los planificadores basados en el algoritmo PB sobrestiman la dosis en un 10%, mientras que el algoritmo CC la subestima en un 3-4%. Los resultados de la simulaci��n mediante MC de los movimientos respiratorios indican que los resultados de los planificadores son suficientemente precisos en el tumor, aunque en la interfase hay una mayor subestimaci��n de la dosis en comparaci��n con el caso est��tico. Estos resultados son compatibles con la experiencia cl��nica adquirida durante 15 a��os en el Karolinska University Hospital. Los resultados se han publicado en la revista Acta Oncologica.

Estimation of the probability of congestion using Monte Carlo method in OPS networks

In networks with small buffers, such as optical packet switching based networks, the convolution approach is presented as one of the most accurate method used for the connection admission control. Admission control and resource management have been addressed in other works oriented to bursty traffic and ATM. This paper focuses on heterogeneous traffic in OPS based networks. Using heterogeneous traffic and bufferless networks the enhanced convolution approach is a good solution. However, both methods (CA and ECA) present a high computational cost for high number of connections. Two new mechanisms (UMCA and ISCA) based on Monte Carlo method are proposed to overcome this drawback. Simulation results show that our proposals achieve lower computational cost compared to enhanced convolution approach with an small stochastic error in the probability estimation

A Monte Carlo-Based Fiber Tracking Algorithm using Diffusion Tensor MRI

Diffusion tensor magnetic resonance imaging, which measures directional information of water diffusion in the brain, has emerged as a powerful tool for human brain studies. In this paper, we introduce a new Monte Carlo-based fiber tracking approach to estimate brain connectivity. One of the main characteristics of this approach is that all parameters of the algorithm are automatically determined at each point using the entropy of the eigenvalues of the diffusion tensor. Experimental results show the good performance of the proposed approach

Error and complexity of random walk Monte Carlo radiosity

The author studies the error and complexity of the discrete random walk Monte Carlo technique for radiosity, using both the shooting and gathering methods. The author shows that the shooting method exhibits a lower complexity than the gathering one, and under some constraints, it has a linear complexity. This is an improvement over a previous result that pointed to an O(n log n) complexity. The author gives and compares three unbiased estimators for each method, and obtains closed forms and bounds for their variances. The author also bounds the expected value of the mean square error (MSE). Some of the results obtained are also shown

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent ���essential zeros��� or because it is below detection limit ���rounded zeros. Because the second kind of zeros is usually understood as ���a trace too small to measure���, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMart��n-Fern��ndez, Barcel��-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts ���and thus the metric properties��� should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Mart��n-Fern��ndez, Barcel��-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Mart��n-Fern��ndez, Barcel��-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is ���natural��� in the sense thatit recovers the ���true��� composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

A Monte Carlo method for accelerating the computation of animated radiosity sequences

Realistic rendering animation is known to be an expensive processing task when physically-based global illumination methods are used in order to improve illumination details. This paper presents an acceleration technique to compute animations in radiosity environments. The technique is based on an interpolated approach that exploits temporal coherence in radiosity. A fast global Monte Carlo pre-processing step is introduced to the whole computation of the animated sequence to select important frames. These are fully computed and used as a base for the interpolation of all the sequence. The approach is completely view-independent. Once the illumination is computed, it can be visualized by any animated camera. Results present significant high speed-ups showing that the technique could be an interesting alternative to deterministic methods for computing non-interactive radiosity animations for moderately complex scenarios