INTRODUCING MODEL UNCERTAINTY IN TIME SERIES BOOTSTRAP

It is common in parametric bootstrap to select the model from the data, and then treat it as it were the true model. Kilian (1998) have shown that ignoring the model uncertainty may seriously undermine the coverage accuracy of bootstrap confidence intervals for impulse response estimates which are closely related with multi-step-ahead prediction intervals. In this paper, we propose different ways of introducing the model selection step in the resampling algorithm. We present a Monte Carlo study comparing the finite sample properties of the proposed method with those of alternative methods in the case of prediction intervals.

Stereodivergent, Diels-Alder-initiated organocascades employing α,β-unsaturated acylammonium salts: scope, mechanism, and application.

Chiral α,β-unsaturated acylammonium salts are novel dienophiles enabling enantioselective Diels-Alder-lactonization (DAL) organocascades leading to cis- and trans-fused, bicyclic γ- and δ-lactones from readily prepared dienes, commodity acid chlorides, and a chiral isothiourea organocatalyst under mild conditions. We describe extensions of stereodivergent DAL organocascades to other racemic dienes bearing pendant secondary and tertiary alcohols, and application to a formal synthesis of (+)-dihydrocompactin is described. A combined experimental and computational investigation of unsaturated acylammonium salt formation and the entire DAL organocascade pathway provide a rationalization of the effect of Brønsted base additives and enabled a controllable, diastereodivergent DAL process leading to a full complement of possible stereoisomeric products. Evaluation of free energy and enthalpy barriers in conjunction with experimentally observed temperature effects revealed that the DAL is a rare case of an entropy-controlled diastereoselective process. NMR analysis of diene alcohol-Brønsted base interactions and computational studies provide a plausible explanation of observed stabilization of exo transition-state structures through hydrogen-bonding effects

Forecasting time series with sieve bootstrap

In this paper we consider bootstrap methods for constructing nonparametric prediction intervals for a general class of linear processes. Our approach uses the sieve bootstrap procedure of Biihlmann (1997) based on residual resampling from an autoregressive approximation to the given process. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values given the observed data, assuming that the order of the autoregressive approximation increases with the sample size at a suitable rate and some restrictions about polynomial decay of the coefficients ~ j t:o of the process MA(oo) representation. We present a Monte Carlo study comparing the finite sample properties of the sieve bootstrap with those of alternative methods. Finally, we illustrate the performance of the proposed method with real data examples

Resampling time series by missing values techniques

For strongly dependent data, deleting blocks of observations is expected to produce bias as in the moving block jackknife of KOnsch (1989) and Liu and Singh (1992). We propose an alternative technique which considers the blocks of deleted observations in the blockwise jackknife as missing data which are replaced by missing values estimates incorporating the observations dependence structure. Thus, the variance estimator is a weighted sample variance of the statistic evaluated in a "complete" series. We establish consistency for the variance and distribution of the sample mean. Also we extent this missing values approach to the blockwise bootstrap by assuming some missing observations among two consecutive blocks. We present the results of an extensive Monte Carlo study to evaluate the performance of the proposed methods in finite sample sizes in which it is shown that our proposal produces estimates of the variance of several time series statistics with smaller mean squared error than previous procedures

Forecasting time series with sieve bootstrap.

In this paper we propose bootstrap methods for constructing nonparametric prediction intervals for a general class of linear processes. Our approach uses the AR(∞)-sieve bootstrap procedure based on residual resampling from an autoregressive approximation to the given process. We present a Monte Carlo study comparing the finite sample properties of the sieve bootstrap with those of alternative methods. Finally, we illustrate the performance of the proposed method with a real data example.We would like to thank Mike Wiper, two referees and the coordinating editor for carefully reading that greatly improved the paper. This research was partially supported by the Dirección General de Educación Superior project DGES PB96-0111 and Cátedra de Calidad BBVA.Publicad

Una revisión de los métodos de remuestreo en series temporales.

Desde Efron y Tibshirani (1986), se han propuesto varios métodos de remuestreo para datos temporales. En este artículo, presentamos los principales métodos de remuestreo desarrollados para series temporales, centrándonos en el jackknife por bloques móviles, el bootstrap por bloques móviles, y en el bootstrap para modelos autorregresivos, y proponemos nuevas alternativas para los métodos de remuestreo basados en bloques de observaciones.Publicad

On sieve bootstrap prediction intervals.

In this paper we consider a sieve bootstrap method for constructing nonparametric prediction intervals for a general class of linear processes. We show that the sieve bootstrap provides consistent estimators of the conditional distribution of future values given the observed data.We would like to thank Mike Wiper for his careful reading which greatly improved the paper. This research was partially supported by the CYCIT project BEC 2000-0167 and by the Cátedra de Calidad BBVA.Publicad

Communication and Social Change in the Origins of Modern Political Ideologies

El artículo analiza los vínculos entre el cambio social y la comunicación pública en el pensamiento de John Arbuthnot, Thomas Jefferson y Karl Marx, autores que se encuentran en el origen de las tres ideologías políticas características de la modernidad: conservadora, reformista y revolucionaria, respectivamente. Se pone de relieve su posición frente al cambio, su proyecto de sociedad y los actores sociales protagonistas, todo ello en relación con el papel que otorgan a la comunicación en dichos procesos.This article analyses the links between social change and public communication in the thought of John Arbuthnot, Thomas Jefferson and Karl Marx, authors who are at the origin of the three political ideologies characteristic of modernity: conservative, reformist and revolutionary, respectively. It highlights their stance on change, their social project and the leading social actors they identify, all in relation to the role granted to communication in these processes