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Observed Process (observed + process)
Selected AbstractsReasoning about non-linear AR models using expectation maximizationJOURNAL OF FORECASTING, Issue 6-7 2003M. ArnoldArticle first published online: 19 SEP 200 Abstract A simplified version of the expectation maximization (EM) algorithm is applied to search for optimal state sequences in state-dependent AR models whereby no prior knowledge about the state equation is necessary. These sequences can be used to draw conclusions about functional dependencies between the observed process and estimated AR coefficients. Consequently this approach is especially helpful in the identification of functional,coefficient AR models where the coefficients are controlled by the process itself. The approximation of regression functions in first-order non-linear AR models and the localization of multiple thresholds in self-exciting threshold autoregressive models are demonstrated as examples.,Copyright © 2003 John Wiley & Sons, Ltd. [source] Ion chemistry in germane/fluorocompounds gaseous mixtures: a mass spectrometric and theoretical studyJOURNAL OF MASS SPECTROMETRY (INCORP BIOLOGICAL MASS SPECTROMETRY), Issue 10 2008Paola Antoniotti Abstract The ion,molecule reactions occurring in GeH4/NF3, GeH4/SF6, and GeH4/SiF4 gaseous mixtures have been investigated by ion trap mass spectrometry and ab initio calculations. While the NFx+ (x = 1,3) react with GeH4 mainly by the exothermic charge transfer, the open-shell Ge+ and GeH2+ undergo the efficient F-atom abstraction from NF3 and form GeF+ and FGeH2+ as the only ionic products. The mechanisms of these two processes are quite similar and involve the formation of the fluorine-coordinated complexes GeFNF2+ and H2GeFNF2+, their subsequent crossing to the significantly more stable isomers FGeNF2+ and FGeH2NF2+, and the eventual dissociation of these ions into GeF+ (or FGeH2+) and NF2. The closed-shell GeH+ and GeH3+ are instead much less reactive towards NF3, and the only observed process is the less efficient formation of GeF+ from GeH+. The theoretical investigation of this unusual H/F exchange reaction suggests the involvement of vibrationally-hot GeH+. Passing from NF3 to SF6 and SiF4, the average strength of the MF bond increases from 70 to 79 and 142 kcal mol,1, and in fact the only process observed by reacting GeHn+ (n = 0,3) with SF6 and SiF4 is the little efficient F-atom abstraction from SF6 by Ge+. Irrespective of the experimental conditions, we did not observe any ionic product of GeN, GeS, or GeSi connectivity. This is in line with the previously observed exclusive formation of GeF+ from the reaction between Ge+ and CF compounds such as CH3F. Additionally observed processes include in particular the conceivable formation of the elusive thiohypofluorous acid FSH from the reaction between SF+ and GeH4. Copyright © 2008 John Wiley & Sons, Ltd. [source] Semiparametric estimation by model selection for locally stationary processesJOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 5 2006Sébastien Van Bellegem Summary., Over recent decades increasingly more attention has been paid to the problem of how to fit a parametric model of time series with time-varying parameters. A typical example is given by autoregressive models with time-varying parameters. We propose a procedure to fit such time-varying models to general non-stationary processes. The estimator is a maximum Whittle likelihood estimator on sieves. The results do not assume that the observed process belongs to a specific class of time-varying parametric models. We discuss in more detail the fitting of time-varying AR(p) processes for which we treat the problem of the selection of the order p, and we propose an iterative algorithm for the computation of the estimator. A comparison with model selection by Akaike's information criterion is provided through simulations. [source] First-Order Autoregressive Processes with Heterogeneous PersistenceJOURNAL OF TIME SERIES ANALYSIS, Issue 3 2003JOANN JASIAK Abstract. We propose a semi-nonparametric method of identification and estimation for Gaussian autoregressive processes with stochastic autoregressive coefficients. The autoregressive coefficient is considered as a latent process with either a moving average or regime switching representation. We develop a consistent estimator of the distribution of the autoregressive coefficient based on nonlinear canonical decomposition of the observed process. The approach is illustrated by simulations. [source] Moment based regression algorithms for drift and volatility estimation in continuous-time Markov switching modelsTHE ECONOMETRICS JOURNAL, Issue 2 2008Robert J. Elliott Summary, We consider a continuous time Markov switching model (MSM) which is widely used in mathematical finance. The aim is to estimate the parameters given observations in discrete time. Since there is no finite dimensional filter for estimating the underlying state of the MSM, it is not possible to compute numerically the maximum likelihood parameter estimate via the well known expectation maximization (EM) algorithm. Therefore in this paper, we propose a method of moments based parameter estimator. The moments of the observed process are computed explicitly as a function of the time discretization interval of the discrete time observation process. We then propose two algorithms for parameter estimation of the MSM. The first algorithm is based on a least-squares fit to the exact moments over different time lags, while the second algorithm is based on estimating the coefficients of the expansion (with respect to time) of the moments. Extensive numerical results comparing the algorithm with the EM algorithm for the discretized model are presented. [source] Model-Checking Techniques Based on Cumulative ResidualsBIOMETRICS, Issue 1 2002D. Y. Lin Summary. Residuals have long been used for graphical and numerical examinations of the adequacy of regression models. Conventional residual analysis based on the plots of raw residuals or their smoothed curves is highly subjective, whereas most numerical goodness-of-fit tests provide little information about the nature of model misspecification. In this paper, we develop objective and informative model-checking techniques by taking the cumulative sums of residuals over certain coordinates (e.g., covariates or fitted values) or by considering some related aggregates of residuals, such as moving sums and moving averages. For a variety of statistical models and data structures, including generalized linear models with independent or dependent observations, the distributions of these stochastic processes under the assumed model can be approximated by the distributions of certain zero-mean Gaussian processes whose realizations can be easily generated by computer simulation. Each observed process can then be compared, both graphically and numerically, with a number of realizations from the Gaussian process. Such comparisons enable one to assess objectively whether a trend seen in a residual plot reflects model misspecification or natural variation. The proposed techniques are particularly useful in checking the functional form of a covariate and the link function. Illustrations with several medical studies are provided. [source] Monocyclic 1,2,3-Triazin-4(3H)-ones: Synthesis, Structure and Photochemical BehaviourEUROPEAN JOURNAL OF ORGANIC CHEMISTRY, Issue 13 2006Angela Maria Celli Abstract Oxidation of the easily available 1-(alkylamino)pyrazolones allows the preparation of the title compounds, which are a new class of heterocycles, in good yields. The structure of these compounds is assigned on the basis of HR mass spectroscopy and sodium borohydride reduction to (Z,E)-2-methyl-3-phenyl- N -(1-phenylethyl)acrylamide. Ring contraction/rearrangement to 2-alkyl- 2H -1,2,3-triazole is observed under UV irradiation. A possible mechanistic rationalisation of the observed processes is proposed.(© Wiley-VCH Verlag GmbH & Co. KGaA, 69451 Weinheim, Germany, 2006) [source] Spatial knowledge diffusion through collaborative networks,PAPERS IN REGIONAL SCIENCE, Issue 3 2007Corinne Autant-Bernard The theory of endogenous growth and the geography and growth synthesis both consider that local growth and spatial concentration of economic activities emanate from localised knowledge spillovers (Lucas 1988; Martin and Ottaviano 1999). Since the end of the 1980's, the spatial dimension of knowledge diffusion has been investigated from an empirical point of view, and the existence and role of local spillovers has been generally confirmed (see among others Jaffe 1989; Audretsch and Feldman 1996). The concern that now arises is to unravel the mechanisms underlying and explaining the geographical knowledge spillovers. The aim of this special issue is to present the latest new findings on such questions and to identify some new lines of research for future work. Before presenting the content of this special issue, we very briefly review the main results of the empirical literature on the geography of innovation. We also explain the context of this special issue by pointing out some of the limitations faced by this literature and, by stressing the complex dynamic and network dimensions of the observed processes of production and diffusion of knowledge. [source] | ||||||||||||||||