Stressing the Boundaries of Mobile Accessibility

Mobile devices gather the communication capabilities as no other gadget. Plus, they now comprise a wider set of applications while still maintaining reduced size and weight. They have started to include accessibility features that enable the inclusion of disabled people. However, these inclusive efforts still fall short considering the possibilities of such devices. This is mainly due to the lack of interoperability and extensibility of current mobile operating systems (OS). In this paper, we present a case study of a multi-impaired person where access to basic mobile applications was provided in an applicational basis. We outline the main flaws in current mobile OS and suggest how these could further empower developers to provide accessibility components. These could then be compounded to provide system-wide inclusion to a wider range of (multi)-impairments.Comment: 3 pages, two figures, ACM CHI 2013 Mobile Accessibility Worksho

Method for simulating non-linear stochastic differential equations in R¹

Very few specific stochastic differential equations have explicitly known solutions. The most common procedure to obtain a simulated path of a solution is based on a discretization of the stochastic differential equations. However, there are some cases where the discrete-time discretization cannot be used. In this article, we propose a new method to simulate the solution of a non-linear stochastic differential equation, which, in principle, is exempt from error of simulation and can be widely applied including in cases where the discrete-time discretization cannot be used.info:eu-repo/semantics/publishedVersio

A new model for multivariate Markov chains

We propose a new model for multivariate Markov chains of order one or higher on the basis of the mixture transition distribution (MTD) model. We call it the MTD-Probit. The proposed model presents two attractive features: it is completely free of constraints, thereby facilitating the estimation procedure, and it is more precise at estimating the transition probabilities of a multivariate or higher-order Markov chain than the standard MTD model.info:eu-repo/semantics/publishedVersio

Nonparametric density forecast based on time- and state-domain

We propose a new nonparametric density forecast based on time- and state-domain smoothing. We analyze some of its asymptotic properties and provide an empirical illustration.info:eu-repo/semantics/publishedVersio

Structural change test in duration of bull and bear markets

We propose a recursive test to analyze structural changes in duration of bull and bear markets. Using the Dow Jones Industrial Average index, we detected a single structural break in the bull market duration in April, 1942.info:eu-repo/semantics/publishedVersio

Stationary processes that look like random walks : the bounded random walk process in discrete and continuous time

Several economic and financial time series are bounded by an upper and lower finite limit (e.g., interest rates). It is not possible to say that these time series are random walks because random walks are limitless with probability one (as time goes to infinity). Yet, some of these time series behave just like random walks. In this paper we propose a new approach that takes into account these ideas. We propose a discrete-time and a continuous-time process (diffusion process) that generate bounded random walks. These paths are almost indistinguishable from random walks, although they are stochastically bounded by an upper and lower finite limit. We derive for both cases the ergodic conditions, and for the diffusion process we present a closed expression for the stationary distribution. This approach suggests that many time series with random walk behavior can in fact be stationarity processes.info:eu-repo/semantics/publishedVersio

Transition density and simulated likelihood estimation for time-inhomogeneous diffusions

We propose a method to estimate the transition density of a non-linear time-inhomogeneous diffusion. Expressing the transition density as a functional of a Brownian bridge, allows us to estimate the density through Monte Carlo simulations with any level of precision. We show how these transition density estimates can be effectively used to estimate the parameters of the time-inhomogeneous diffusion and the conditional moments of the process. In this paper we prove that our method is asymptotically equivalent to the maximum likelihood estimator and more reliable than the closed-form approximation approach largely used in the literature.info:eu-repo/semantics/publishedVersio

A new technique for simulating the likelihood of stochastic differential equations

This article presents a new simulation-based technique for estimating the likelihood of stochastic differential equations. This technique is based on a result of Dacunha-Castelle and Florens-Zmirou. These authors proved that the transition densities of a nonlinear diffusion process with a constant diffusion coefficient can be written in a closed form involving a stochastic integral. We show that this stochastic integral can be easily estimated through simulations and we prove a convergence result. This simulator for the transition density is used to obtain the simulated maximum likelihood (SML) estimator. We show through some Monte Carlo experiments that our technique is highly computationally efficient and the SML estimator converges rapidly to the maximum likelihood estimatorinfo:eu-repo/semantics/publishedVersio

Processes with volatility-induced stationarity : an application for interest rates

In this article we propose a model in discrete and continuous time that incorporates explicitly a technical trading rule in the specification of the volatility. The proposed discrete-time model is an alternative to GARCH-type processes. We derive conditions for the covariance and strict stationarity of the discrete-time process and we study the estimation and inference problems. We also analyze the conditions under which the discrete-time process converges in distribution to a diffusion process. To illustrate the proposed model and compare it with the GARCH specification, we analyze the daily closing stock prices of two major U.S. companies (Microsoft and Oracle), two stock indices (DAX and NASDAQ) and two U.S. Dollar exchange rates (Euro and Sterling).info:eu-repo/semantics/publishedVersio

Nonparametric estimation of second-order stochastic differential equations

We propose nonparametric estimators of the infinitesimal coefficients associated with second-order stochastic differential equations. We show that under appropriate conditions, the proposed estimators are consistent. Also, we state conditions ensuring the asymptotic normality of these estimators. We conclude our pa with a Monte Carlo experiment in which we assess the response of the nonparametric estimators with respect to the step of discretization.info:eu-repo/semantics/publishedVersio