882 resultados para the least squares distance method
Resumo:
During the past 15 years, a number of initiatives have been undertaken at national level to develop ocean forecasting systems operating at regional and/or global scales. The co-ordination between these efforts has been organized internationally through the Global Ocean Data Assimilation Experiment (GODAE). The French MERCATOR project is one of the leading participants in GODAE. The MERCATOR systems routinely assimilate a variety of observations such as multi-satellite altimeter data, sea-surface temperature and in situ temperature and salinity profiles, focusing on high-resolution scales of the ocean dynamics. The assimilation strategy in MERCATOR is based on a hierarchy of methods of increasing sophistication including optimal interpolation, Kalman filtering and variational methods, which are progressively deployed through the Syst`eme d’Assimilation MERCATOR (SAM) series. SAM-1 is based on a reduced-order optimal interpolation which can be operated using ‘altimetry-only’ or ‘multi-data’ set-ups; it relies on the concept of separability, assuming that the correlations can be separated into a product of horizontal and vertical contributions. The second release, SAM-2, is being developed to include new features from the singular evolutive extended Kalman (SEEK) filter, such as three-dimensional, multivariate error modes and adaptivity schemes. The third one, SAM-3, considers variational methods such as the incremental four-dimensional variational algorithm. Most operational forecasting systems evaluated during GODAE are based on least-squares statistical estimation assuming Gaussian errors. In the framework of the EU MERSEA (Marine EnviRonment and Security for the European Area) project, research is being conducted to prepare the next-generation operational ocean monitoring and forecasting systems. The research effort will explore nonlinear assimilation formulations to overcome limitations of the current systems. This paper provides an overview of the developments conducted in MERSEA with the SEEK filter, the Ensemble Kalman filter and the sequential importance re-sampling filter.
Resumo:
The quadratic, cubic, and quartic force field of HCN has been calculated by a least squares refinement to fit the most recent observed data on the vibration-rotation constants of HCN, DCN and H13CN. All of the observed parameters are fitted within their standard errors of observation. The corresponding parameters for other isotopic species are calculated. For HCP and DCP the more limited data available have been fitted to an anharmonic force field using constraints based on comparison with HCN. Using this force field the zero-point rotational constants B0 have been corrected to obtain the equilibrium constants Be, and hence the equilibrium structure has been determined to be re(CH) = 1•0692(7)A, and re(CP) = 1•5398(2)A.
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Vibration-rotation spectra of HOCl have been measured at a resolution of 0.05 cm−1 to determine vibration rotation constants, and 35–37 Cl isotope shifts in the vibration frequencies. The spectrum of DOCl has also been recorded, and a preliminary analysis for the band origins has been made. The vibrational frequency data and centrifugal distortion constants have been used to determine the harmonic force field in a least-squares refinement; the force field obtained also gives a good fit to data on the vibrational contributions to the inertial defect. The equilibrium rotational constants of HOCl have been obtained, and an equilibrium structure has been estimated.
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Vibration rotation spectra of HO15 NO and DO15 NO have been measured at a resolution of 0•04 cm-1 to determine the isotopic shifts in the vibrational band origins. These have been used together with recently determined data on the vibrational band origins, Coriolis constants, and centrifugal distorition constants, to determine the harmonic force field of both cis and trans nitrous acid in least squares refinement calculations. The results are discussed in relation to recent ab initio calculations, the inertia defects, and the torsional potential function.
Resumo:
The anisotropic and isotropic components of the ν2, ν5 rotation-vibrational Raman bands of 13CH3F were obtained separately. The two upper states are coupled by a strong second-order Coriolis resonance. The anisotropic spectrum was analyzed by means of a program system due to R. Escribano. A contour simulation and a least-squares fit of 233 assigned transitions yielded values for ν5, ΔA5, ΔA2, and Aζ5a, 5b(z). The 13C shifts of ν2 and ν5 were obtained from the isotropic spectrum.
Resumo:
The theory of harmonic force constant refinement calculations is reviewed, and a general-purpose program for force constant and normal coordinate calculations is described. The program, called ASYM20. is available through Quantum Chemistry Program Exchange. It will work on molecules of any symmetry containing up to 20 atoms and will produce results on a series of isotopomers as desired. The vibrational secular equations are solved in either nonredundant valence internal coordinates or symmetry coordinates. As well as calculating the (harmonic) vibrational wavenumbers and normal coordinates, the program will calculate centrifugal distortion constants, Coriolis zeta constants, harmonic contributions to the α′s. root-mean-square amplitudes of vibration, and other quantities related to gas electron-diffraction studies and thermodynamic properties. The program will work in either a predict mode, in which it calculates results from an input force field, or in a refine mode, in which it refines an input force field by least squares to fit observed data on the quantities mentioned above. Predicate values of the force constants may be included in the data set for a least-squares refinement. The program is written in FORTRAN for use on a PC or a mainframe computer. Operation is mainly controlled by steering indices in the input data file, but some interactive control is also implemented.
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In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.
Resumo:
The influence matrix is used in ordinary least-squares applications for monitoring statistical multiple-regression analyses. Concepts related to the influence matrix provide diagnostics on the influence of individual data on the analysis - the analysis change that would occur by leaving one observation out, and the effective information content (degrees of freedom for signal) in any sub-set of the analysed data. In this paper, the corresponding concepts have been derived in the context of linear statistical data assimilation in numerical weather prediction. An approximate method to compute the diagonal elements of the influence matrix (the self-sensitivities) has been developed for a large-dimension variational data assimilation system (the four-dimensional variational system of the European Centre for Medium-Range Weather Forecasts). Results show that, in the boreal spring 2003 operational system, 15% of the global influence is due to the assimilated observations in any one analysis, and the complementary 85% is the influence of the prior (background) information, a short-range forecast containing information from earlier assimilated observations. About 25% of the observational information is currently provided by surface-based observing systems, and 75% by satellite systems. Low-influence data points usually occur in data-rich areas, while high-influence data points are in data-sparse areas or in dynamically active regions. Background-error correlations also play an important role: high correlation diminishes the observation influence and amplifies the importance of the surrounding real and pseudo observations (prior information in observation space). Incorrect specifications of background and observation-error covariance matrices can be identified, interpreted and better understood by the use of influence-matrix diagnostics for the variety of observation types and observed variables used in the data assimilation system. Copyright © 2004 Royal Meteorological Society
Resumo:
Structure activity relationships (SARs) are presented for the gas-phase reactions of RO2 with HO2, and the self- and cross-reactions of RO2. For RO2+HO2 the SAR is based upon a correlation between the logarithm of the measured rate coefficient and a calculated ionisation potential for the molecule R-CH=CH2, R being the same group in both the radical and molecular analogue. The correlation observed is strong and only for one RO2 species does the measured rate coefficient deviate by more than a factor of two from the linear least-squares regression line. For the self- and cross-reactions of RO2 radicals, the SAR is based upon a correlation between the logarithm of the measured rate coefficient and the calculated electrostatic potential (ESP) at the equivalent carbon atom in the RH molecule to which oxygen is attached in RO2, again R being the same group in the molecule and the radical. For cases where R is a simple alkyl-group, a strong linear correlation observed. For RO2 radicals which contain lone pair-bearing substituents and for which the calculated ESP<-0.05 self-reaction rate coefficients appear to be insensitive to the value of the ESP. For RO2 of this type with ESP>-0.05 a linear relationship between log k and the ESP is again observed. Using the relationships, 84 out of the 85 rate coefficients used to develop the SARs are predicted to within a factor of three of their measured values. A relationship is also presented that allows the prediction of the Arrhenius parameters for the self-reactions of simple alkyl RO2 radicals. On the basis of the correlations, predictions of room-temperature rate coefficients are made for a number of atmospherically important peroxyl-peroxyl radical reactions. (C) 2003 Elsevier Ltd. All rights reserved.
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The relationships between wheat protein quality and baking properties of 20 flour samples were studied for two breadmaking processes; a hearth bread test and the Chorleywood Bread Process (CBP). The strain hardening index obtained from dough inflation measurements, the proportion of unextractable polymeric protein, and mixing properties were among the variables found to be good indicators of protein quality and suitable for predicting potential baking quality of wheat flours. By partial least squares regression, flour and dough test variables were able to account for 71-93% of the variation in crumb texture, form ratio and volume of hearth loaves made using optimal mixing and fixed proving times. These protein quality variables were, however, not related to the volume of loaves produced by the CBP using mixing to constant work input and proving to constant height. On the other hand, variation in crumb texture of CBP loaves (54-55%) could be explained by protein quality. The results underline that the choice of baking procedure and loaf characteristics is vital in assessing the protein quality of flours. (C) 2003 Elsevier Ltd. All rights reserved.
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A method is described for the analysis of deuterated and undeuterated alpha-tocopherol in blood components using liquid chromatography coupled to an orthogonal acceleration time-of-flight (TOF) mass spectrometer. Optimal ionisation conditions for undeuterated (d0) and tri- and hexadeuterated (d3 or d6) alpha-tocopherol standards were found with negative ion mode electrospray ionisation. Each species produced an isotopically resolved single ion of exact mass. Calibration curves of pure standards were linear in the range tested (0-1.5 muM, 0-15 pmol injected). For quantification of d0 and d6 in blood components following a standard solvent extraction, a stable-isotope-labelled internal standard (d3-alpha-tocopherol) was employed. To counter matrix ion suppression effects, standard response curves were generated following identical solvent extraction procedures to those of the samples. Within-day and between-day precision were determined for quantification of d0- and d6-labelled alpha-tocopherol in each blood component and both averaged 3-10%. Accuracy was assessed by comparison with a standard high-performance liquid chromatography (HPLC) method, achieving good correlation (r(2) = 0.94), and by spiking with known concentrations of alpha-tocopherol (98% accuracy). Limits of detection and quantification were determined to be 5 and 50 fmol injected, respectively. The assay was used to measure the appearance and disappearance of deuterium-labelled alpha-tocopherol in human blood components following deuterium-labelled (d6) RRR-alpha-tocopheryl acetate ingestion. The new LC/TOFMS method was found to be sensitive, required small sample volumes, was reproducible and robust, and was capable of high throughput when large numbers of samples were generated. Copyright (C) 2003 John Wiley Sons, Ltd.
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In this paper new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness, including three algorithms using combined A- or D-optimality or PRESS statistic (Predicted REsidual Sum of Squares) with regularised orthogonal least squares algorithm respectively. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalisation scheme in orthogonal least squares or regularised orthogonal least squares has been extended such that the new algorithms are computationally efficient. A numerical example is included to demonstrate effectiveness of the algorithms. Copyright (C) 2003 IFAC.
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A unified approach is proposed for sparse kernel data modelling that includes regression and classification as well as probability density function estimation. The orthogonal-least-squares forward selection method based on the leave-one-out test criteria is presented within this unified data-modelling framework to construct sparse kernel models that generalise well. Examples from regression, classification and density estimation applications are used to illustrate the effectiveness of this generic sparse kernel data modelling approach.
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A basic principle in data modelling is to incorporate available a priori information regarding the underlying data generating mechanism into the modelling process. We adopt this principle and consider grey-box radial basis function (RBF) modelling capable of incorporating prior knowledge. Specifically, we show how to explicitly incorporate the two types of prior knowledge: the underlying data generating mechanism exhibits known symmetric property and the underlying process obeys a set of given boundary value constraints. The class of orthogonal least squares regression algorithms can readily be applied to construct parsimonious grey-box RBF models with enhanced generalisation capability.
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We provide a system identification framework for the analysis of THz-transient data. The subspace identification algorithm for both deterministic and stochastic systems is used to model the time-domain responses of structures under broadband excitation. Structures with additional time delays can be modelled within the state-space framework using additional state variables. We compare the numerical stability of the commonly used least-squares ARX models to that of the subspace N4SID algorithm by using examples of fourth-order and eighth-order systems under pulse and chirp excitation conditions. These models correspond to structures having two and four modes simultaneously propagating respectively. We show that chirp excitation combined with the subspace identification algorithm can provide a better identification of the underlying mode dynamics than the ARX model does as the complexity of the system increases. The use of an identified state-space model for mode demixing, upon transformation to a decoupled realization form is illustrated. Applications of state-space models and the N4SID algorithm to THz transient spectroscopy as well as to optical systems are highlighted.