Spatio-temporal epidemic modelling using additive-multiplicative intensity models

An extension of the stochastic susceptible-infectious-recovered (SIR) model is proposed in order to accommodate a regression context for modelling infectious disease surveillance data. The proposal is based on a multivariate counting process specified by conditional intensities, which contain an additive epidemic component and a multiplicative endemic component. This allows the analysis of endemic infectious diseases by quantifying risk factors for infection by external sources in addition to infective contacts. Simulation from the model is straightforward by Ogata's modified thinning algorithm. Inference can be performed by considering the full likelihood of the stochastic process with additional parameter restrictions to ensure non-negative conditional intensities. As an illustration we analyse data provided by the Federal Research Centre for Virus Diseases of Animals, Wusterhausen, Germany, on the incidence of the classical swine fever virus in Germany during 1993-2004

Impact factors

In this paper we discuss sensitivity of forecast with respect to the information set considered in prediction; we define a sensitivit measure called impact factor, IF. We calculate this measure in VAR processes integrated of order 0, 1 and 2. For VAR processes this measure is as simple function of the impulse response coefficients. For integrated VAR systems this measure is shown to have a direct interpretation in terms of long-run forecasts. Various applications of this concept are reviewed, including one on the interpretation and effectiveness of economics policies and one on the sensitivity of forecasts with respect to data revisions. A unified approach to inference on the IF is given, showing under what circumstances standard asymptotic inference can be conducted also in systems integrated of order 1 and 2.Forecasting, cointegration, dynamic multipliers, (Generalized) impulse responses, VAR.

Classification and repeatability studies of transient electromagnetic measurements with respect to the development of CO2-monitoring techniques

The mitigation of greenhouse gases, like CO2 is a challenging aspect for our society. A strategy to hamper the constant emission of CO2 is utilizing carbon capture and storage technologies. CO2 is sequestrated in subsurface reservoirs. However, these reservoirs harbor the risk of leakage and appropriate geophysical monitoring methods are needed. A crucial aspect of monitoring is the assignment of measured data to certain events occurring. Especially if changes in the measured data are small, suitable statistical methods are needed. In this thesis, a new statistical workflow based on cluster analysis is proposed to detect similar transient electromagnetic signals. The similarity criteria dynamic time warping, the autoregressive distance, and the normalized root-mean-square distance are investigated and evaluated with respect to the classic Euclidean norm. The optimal number of clusters is determined using the gap statistic and visualized with multidimensional scaling. To validate the clustering results, silhouette values are used. The statistical workflow is applied to a synthetic data set, a long-term monitoring data set and a repeat measurement at a pilot CO2-sequestration site in Brooks, Alberta

Modeling violations of the race model inequality in bimodal paradigms: co-activation from decision and non-decision components

The redundant-signals paradigm (RSP) is designed to investigate response behavior in perceptual tasks in which response-relevant targets are defined by either one or two features, or modalities. The common finding is that responses are speeded for redundantly compared to singly defined targets. This redundant-signals effect (RSE) can be accounted for by race models if the response times do not violate the race model inequality (RMI). When there are violations of the RMI, race models are effectively excluded as a viable account of the RSE. The common alternative is provided by co-activation accounts, which assume that redundant target signals are integrated at some processing stage. However, “co-activation” has mostly been only indirectly inferred and the accounts have only rarely been explicitly modeled; if they were modeled, the RSE has typically been assumed to have a decisional locus. Yet, there are also indications in the literature that the RSE might originate, at least in part, at a non-decisional or motor stage. In the present study, using a distribution analysis of sequential-sampling models (ex-Wald and Ratcliff Diffusion model), the locus of the RSE was investigated for two bimodal (audio-visual) detection tasks that strongly violated the RMI, indicative of substantial co-activation. Three model variants assuming different loci of the RSE were fitted to the quantile reaction time proportions: a decision, a non-decision, and a combined variant both to vincentized group as well as individual data. The results suggest that for the two bimodal detection tasks, co-activation has a shared decisional and non-decisional locus. These findings point to the possibility that the mechanisms underlying the RSE depend on the specifics (task, stimulus, conditions, etc.) of the experimental paradigm

New alternative statistic for testing several independent samples of correlation matrices in high dimension data

Jennrich Jennrich statistic is one of the existing statistics which is used for testing the equality of several independent samples of correlation matrices. The statistic is gaining considerable importance in several areas of economics and financial markets. In these research areas, the number of variables, p, is usually larger than the sample size, n, which is known as high dimension data p > n. Subsequently, the estimation of correlation and covariance determinant will breakdown due to singularity problem. When this happens, Jennrich statistic is unable to function as the calculation involves the inversion of correlation matrix. Therefore, to resolve the aforementioned problem, this study develops an alternative statistic for testing several independent samples of correlation matrices in high dimension data. For this reason, the algebraic approach on the basis of vec operator, commutation matrix and Frobenius norm of upper-off-diagonal elements are used to derive the new asymptotic distribution for the new alternative statistic, namely * Z statistic. Simulation study was conducted by considering different number of variables, sample sizes, and correlation shifts to evaluate the performance of the new statistic. In addition, real data on Asia Pacific currencies structure during the Tohoku earthquake were applied to validate the new * Z statistic. The power of the * Z statistic is compared with the existing Jennrich statistic, and * T statistic through simulation study. As a result, the power of * Z statistic dominates the power of Jennrich statistic and * T statistic in all conditions, especially, when the shift in correlation matrix is at least 0.3 As a conclusion, the theoretical and simulation results are established and supported by desirable power of test. Meanwhile, investigation on real data indicates that the new alternative statistic can accommodate high dimension data

An empirical examination of a multilateral target zone model

En este documento estimamos el modelo de bandas multilaterales de tipos de cambio de Serrat (1994) usando un metodo de simulacion de la metodologia de momentos. En contraste con los ampliamente comentados escasos resultados de los modelos de bandas bilaterales de tipos de cambio y otros modelos no lineales de tipos de cambio, el modelo multilateral se adapta muy bien a los datos del SME. Tambien utilizamos ejercicios de simulacion de Monte|Carlo para evaluar la consistencia de nuestro test frente a hipotesis alternativas. Asimismo, podemos explicar los resultados negativos de los trabajos empiricos previos en el contexto del modelo. Asi que, las percepciones adicionales dadas por el modelo multilateral resultan de extrema relevancia empirica. Estan guiadas por los parametros que reflejan el grado de cooperacion entre las autoridades monetarias para mantener el regimen, lo que ha sido descuidado por los trabajos teoricos y empiricos previos. (ast) (igg