Forecasting linear dynamical systems using subspace methods

A new procedure to predict with subspace methods is presented in this paper. It is based on combining multiple forecasts obtained from setting a range of values for a specic parameter that is typically xed by the user in the subspace methods literature. An algorithm to compute these predictions and to obtain a suitable number of combinations is provided. The procedure is illustrated by forecasting the German gross domestic product.Forecasting, Subspace methods, Combining forecasts.

Estimating the system order by subspace methods

This paper discusses how to determine the order of a state-space model. To do so, we start by revising existing approaches and find in them three basic shortcomings: i) some of them have a poor performance in short samples, ii) most of them are not robust and iii) none of them can accommodate seasonality. We tackle the first two issues by proposing new and refined criteria. The third issue is dealt with by decomposing the system into regular and seasonal sub-systems. The performance of all the procedures considered is analyzed through Monte Carlo simulations

Unit Roots and Cointegrating Matrix Estimation using Subspace Methods

We propose a new procedure to detect unit roots based on subspace methods. It has three main original features. First, the same method can be applied to single or multiple time series. Second, it employs a flexible family of information criteria, which loss functions can be adapted to the statistical properties of the data. Last, it does not require the specification of a stochastic process for the series analyzed. Also, we provide a consistent estimator of the cointegrating rank and the cointegrating matrix. Simulation exercises show that the procedure has good finite sample properties. An example illustrates its application to real time series.State-space models, subspace methods, unit roots, cointegration.

ESTIMATING THE SYSTEM ORDER BY SUBSPACE METHODS

This paper discusses how to determine the order of a state-space model. To do so, we start by revising existing approaches and find in them three basic shortcomings: i) some of them have a poor performance in short samples, ii) most of them are not robust and iii) none of them can accommodate seasonality. We tackle the first two issues by proposing new and refined criteria. The third issue is dealt with by decomposing the system into regular and seasonal sub-systems. The performance of all the procedures considered is analyzed through Monte Carlo simulations.

From general State-Space to VARMAX models

Fixed coecients State-Space and VARMAX models are equivalent, meaning that they are able to represent the same linear dynamics, being indistinguishable in terms of overall fit. However, each representation can be specifically adequate for certain uses, so it is relevant to be able to choose between them. To this end, we propose two algorithms to go from general State-Space models to VARMAX forms. The first one computes the coeficients of a standard VARMAX model under some assumptions while the second, which is more general, returns the coeficients of a VARMAX echelon. These procedures supplement the results already available in the literature allowing one to obtain the State-Space model matrices corresponding to any VARMAX. The paper also discusses some applications of these procedures by solving several theoretical and practical problems.State-Space, VARMAX models, Canonical forms, Echelon.

Fast estimation methods for time series models in state-space form

We propose two fast, stable and consistent methods to estimate time series models expressed in their equivalent state-space form. They are useful both, to obtain adequate initial conditions for a maximum-likelihood iteration, or to provide final estimates when maximum-likelihood is considered inadequate or costly. The state-space foundation of these procedures implies that they can estimate any linear fixed-coefficients model, such as ARIMA, VARMAX or structural time series models. The computational and finitesample performance of both methods is very good, as a simulation exercise shows.State-space models, subspace methods, Kalman Filter, system identification.

Vegetation monitoring by remote sensing: Progress in calibrating a radiometric index and its application in the Gourma, Mali

Evaluates relationship between NDVI (nomalized difference vegetation index) and above-ground biomass, between maximum NDVI and end-of-growing season biomass; and between the integral of the NDVI curve or NDVI increments overtime and actual biomass. Describes atmospheric interference and technical problems affecting the special vegetation index

Desterritorialización y reterritorialización metropolitana : la ciudad de México

Este trabajo se orienta a la comprensión de las formas que está tomando la relación de la sociedad metropolitana con su espacio. Para ello, analizamos dos grupos sociales: las nuevas burguesías y los sectores populares más pauperizados de la periferia metropolitana de la ciudad de México, ambos involucrados, directa e indirectamente, en procesos globales y locales. El análisis de las burguesías se centra en las prácticas y estrategias de estos actores, fuertemente globalizados y aparentemente desprendidos de los territorios por los cuales transitan, y por eso fuertemente móviles en el territorio. El análisis de los sectores populares más pauperizados lo hacemos desde el territorio periférico (la forma de vivirlos, otorgarles significados, construir un imaginario sobre ellos), porque precisamente la globalización los ha confinado en territorio periférico: están casi fijos, aunque la falta de movilidad territorial no necesariamente implica sentido de pertenencia por el lugar.Aquest treball s'orienta a la comprensió de les formes que adquireix la relació de la societat metropolitana amb el seu espai. Per això analitzem dos grups socials: les noves burgesies i els sectors populars més pobres de la perifèria metropolitana de la ciutat de Mèxic, tots dos implicats, directament i indirectament, en processos globals i locals. L'anàlisi de les burgesies se centra en les pràctiques i estratègies d'aquests actors, fortament globalitzats i aparentment despresos dels territoris pels quals transiten, i per això fortament mòbils en el territori. L'anàlisi dels sectors populars més pauperitzats el fem des del territori perifèric (la forma de viure'ls, atorgar-los significats, construir-ne un imaginari), ja que precisament la globalització els ha confinats en territori perifèric: estan gairebé fixos, encara que la manca de mobilitat territorial no implica necessàriament sentit de pertinença al lloc.Cet article vise la compréhension des formes que prend la relation de la société métropolitaine à son espace. Pour ce faire, nous analyserons deux groupes sociaux: les nouvelles bourgeoisies et les secteurs populaires les plus pauvres de la périphérie métropolitaine de Mexico, tous deux touchés, directement et indirectement, par les processus mondiaux et locaux. L'analyse des bourgeoisies se centre sur leurs pratiques et leurs stratégies; elles sont fortement mondialisées et apparement déliées des territoires le long desquels elles circulent, et de ce fait, fortement mobiles dans le territoire. Quant à l'analyse des secteurs les plus pauvres, nous la faisons depuis le territoire périphérique, la façon de le vivre, de lui octroyer du sens, de construire un imaginaire, parce que c'est précisement la mondialisation qui les a confiné dan ce territoire périphérique: ils demeurent quasi fixes, même si le manque de mobilité n'implique pas forcément un sens d'appartenance au territoire.This paper is oriented to understand the forms of the metropolitan society relation regarding its space. Therefore we are analyzing two social groups: The new bourgeoisies and the poorest popular sector of the metropolitan periphery, both directly and indirectly involved in local and global process. The bourgeoisie's analysis is centered on the practices and strategies of those actors, strongly globalized and apparently mobile along the territory. On the other hand, the analysis of the poorest popular sectors is build from the peripherical territory, the way of living it, from the way of giving it a signification or to build an imaginary, precisely because the globalization has confined them in a peripherical territory: Those social sectors are almost fixed, even if the lack of territorial mobility doesn't imply a sense of being part of the place