989 resultados para Squares


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The 3700 A - 3000 A absorption spectra of CH3CHO and its isotopic compounds such as CH3CDO, CD3CHO and CD3CDO were studied in the gas phase at room temperature and low temperatures. The low resolution spectra of the compounds were recorded by a 1.5 m Baush and Lomb grating spectrograph. The high resolution spectra were recorded by a Ebert spectrograph with the Echelle grating and the holographic grating separately. The multiple reflection cells were used to achieve the long path length. The pressure-path length used for the absorption spectrum of CH 3CHO was up to 100 mm Hg )( 91 . 43mo The emission spectrum and the excitation spectrum of CH3CHO were also recorded in this research. The calculated satellite band patterns \vhich were ob-tailied by the method of Lewis were used to compare with the observed near UV absorption spectrum of acetaldehyde. These calculated satellite band patterns belonged to two cases: namely, the barriers-in-phase case and the barriers- out-of-phase case. Each of the calculated patterns corresponded to a stable conformation of acetaldehyde in the excited state . The comparisons showed that the patterns in the observed absorption spectra corresponded to the H-H eclipsed conformations of acetaldehyde in the excited state . The least squares fitting analysis showed that the barrier heights in the excited state were higher than in the ground state. Finally, the isotopic shifts for the isotopic compounds of acetaldehyde were compared to the compounds with the similar deuterium substitution.

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Jet-cooled, laser-induced phosphorescence excitation spectra (LIP) of thioacetaldehyde CH3CHS, CH3CDS, CD3CHS and CD3CDS have been observed over the region 15800 - 17300 cm"^ in a continuous pyrolysis jet. The vibronic band structure of the singlet-triplet n -* n* transition were attributed to the strong coupling of the methyl torsion and aldehydic hydrogen wagging modes . The vibronic peaks have been assigned in terms of two upper electronic state (T^) vibrations; the methyl torsion mode v^g, and the aldehydic hydrogen wagging mode v^^. The electronic origin O^a^ is unequivocally assigned as follows: CH3CHS (16294.9 cm"'' ), CH3CDS (16360.9 cm"'' ), CD3CHS (16299.7 cm"^ ), and CD3CDS (16367.2 cm"'' ). To obtain structural and dynamical information about the two electronic states, potential surfaces V(e,a) for the 6 (methyl torsion) and a (hydrogen wagging) motions were generated by ab initio quantum mechanical calculations with a 6-3 IG* basis in which the structural parameters were fully relaxed. The kinetic energy coefficients BQ(a,e) , B^(a,G) , and the cross coupling term B^(a,e) , were accurately represented as functions of the two active coordinates, a and 9. The calculations reveal that the molecule adopts an eclipsed conformation for the lower Sq electronic state (a=0°,e=0"') with a barrier height to internal rotation of 541.5 cm"^ which is to be compared to 549.8 cm"^ obtained from the microwave experiment. The conformation of the upper T^ electronic state was found to be staggered (a=24 . 68° ,e=-45. 66° ) . The saddle point in the path traced out by the aldehyde wagging motion was calculated to be 175 cm"^ above the equilibrium configuration. The corresponding maxima in the path taken by methyl torsion was found to be 322 cm'\ The small amplitude normal vibrational modes were also calculated to aid in the assignment of the spectra. Torsional-wagging energy manifolds for the two states were derived from the Hamiltonian H(a,e) which was solved variationally using an extended two dimensional Fourier expansion as a basis set. A torsionalinversion band spectrum was derived from the calculated energy levels and Franck-Condon factors, and was compared with the experimental supersonic-jet spectra. Most of the anomalies which were associated with the interpretation of the observed spectrum could be accounted for by the band profiles derived from ab initio SCF calculations. A model describing the jet spectra was derived by scaling the ab initio potential functions. The global least squares fitting generates a triplet state potential which has a minimum at (a=22.38° ,e=-41.08°) . The flatter potential in the scaled model yielded excellent agreement between the observed and calculated frequency intervals.

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A simple, low-cost concentric capillary nebulizer (CCN) was developed and evaluated for ICP spectrometry. The CCN could be operated at sample uptake rates of 0.050-1.00 ml min'^ and under oscillating and non-oscillating conditions. Aerosol characteristics for the CCN were studied using a laser Fraunhofter diffraction analyzer. Solvent transport efficiencies and transport rates, detection limits, and short- and long-term stabilities were evaluated for the CCN with a modified cyclonic spray chamber at different sample uptake rates. The Mg II (280.2nm)/l\/lg 1(285.2nm) ratio was used for matrix effect studies. Results were compared to those with conventional nebulizers, a cross-flow nebulizer with a Scott-type spray chamber, a GemCone nebulizer with a cyclonic spray chamber, and a Meinhard TR-30-K3 concentric nebulizer with a cyclonic spray chamber. Transport efficiencies of up to 57% were obtained for the CCN. For the elements tested, short- and long-term precisions and detection limits obtained with the CCN at 0.050-0.500 ml min'^ are similar to, or better than, those obtained on the same instrument using the conventional nebulizers (at 1.0 ml min'^). The depressive and enhancement effects of easily ionizable element Na, sulfuric acid, and dodecylamine surfactant on analyte signals with the CCN are similar to, or better than, those obtained with the conventional nebulizers. However, capillary clog was observed when the sample solution with high dissolved solids was nebulized for more than 40 min. The effects of data acquisition and data processing on detection limits were studied using inductively coupled plasma-atomic emission spectrometry. The study examined the effects of different detection limit approaches, the effects of data integration modes, the effects of regression modes, the effects of the standard concentration range and the number of standards, the effects of sample uptake rate, and the effect of Integration time. All the experiments followed the same protocols. Three detection limit approaches were examined, lUPAC method, the residual standard deviation (RSD), and the signal-to-background ratio and relative standard deviation of the background (SBR-RSDB). The study demonstrated that the different approaches, the integration modes, the regression methods, and the sample uptake rates can have an effect on detection limits. The study also showed that the different approaches give different detection limits and some methods (for example, RSD) are susceptible to the quality of calibration curves. Multicomponents spectral fitting (MSF) gave the best results among these three integration modes, peak height, peak area, and MSF. Weighted least squares method showed the ability to obtain better quality calibration curves. Although an effect of the number of standards on detection limits was not observed, multiple standards are recommended because they provide more reliable calibration curves. An increase of sample uptake rate and integration time could improve detection limits. However, an improvement with increased integration time on detection limits was not observed because the auto integration mode was used.

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Emerging markets have received wide attention from investors around the globe because of their return potential and risk diversification. This research examines the selection and timing performance of Canadian mutual funds which invest in fixed-income and equity securities in emerging markets. We use (un)conditional two- and five-factor benchmark models that accommodate the dynamics of returns in emerging markets. We also adopt the cross-sectional bootstrap methodology to distinguish between ‘skill’ and ‘luck’ for individual funds. All the tests are conducted using a comprehensive data set of bond and equity emerging funds over the period of 1989-2011. The risk-adjusted measures of performance are estimated using the least squares method with the Newey-West adjustment for standard errors that are robust to conditional heteroskedasticity and autocorrelation. The performance statistics of the emerging funds before (after) management-related costs are insignificantly positive (significantly negative). They are sensitive to the chosen benchmark model and conditional information improves selection performance. The timing statistics are largely insignificant throughout the sample period and are not sensitive to the benchmark model. Evidence of timing and selecting abilities is obtained in a small number of funds which is not sensitive to the fees structure. We also find evidence that a majority of individual funds provide zero (very few provide positive) abnormal return before fees and a significantly negative return after fees. At the negative end of the tail of performance distribution, our resampling tests fail to reject the role of bad luck in the poor performance of funds and we conclude that most of them are merely ‘unlucky’.

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Abstract Background Children have been shown to have higher lactate (LaTh) and ventilatory (VeTh) thresholds than adults, which might be explained by lower levels of type-II motor-unit (MU) recruitment. However, the electromyographic threshold (EMGTh), regarded as indicating the onset of accelerated type-II MU recruitment, has been investigated only in adults. Purpose To compare the relative exercise intensity at which the EMGTh occurs in boys versus men. Methods Participants were 21 men (23.4 ± 4.1 years) and 23 boys (11.1 ± 1.1 years), with similar habitual physical activity and peak oxygen consumption (VO2pk) (49.7 ± 5.5 vs. 50.1 ± 7.4 ml kg−1 min−1, respectively). Ramped cycle ergometry was conducted to volitional exhaustion with surface EMG recorded from the right and left vastus lateralis muscles throughout the test (~10 min). The composite right–left EMG root mean square (EMGRMS) was then calculated per pedal revolution. The EMGTh was then determined as the exercise intensity at the point of least residual sum of squares for any two regression line divisions of the EMGRMS plot. Results EMGTh was detected in 20/21 of the men (95.2 %) and only in 18/23 of the boys (78.3 %). The boys’ EMGTh was significantly higher than the men’s (86.4 ± 9.6 vs. 79.7 ± 10.0 % of peak power output at exhaustion; p < 0.05). The pattern was similar when EMGTh was expressed as percentage of VO2pk. Conclusions The boys’ higher EMGTh suggests delayed and hence lesser utilization of type-II MUs in progressive exercise, compared with men. The boys–men EMGTh differences were of similar magnitude as those shown for LaTh and VeTh, further suggesting a common underlying factor.

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Digital Terrain Models (DTMs) are important in geology and geomorphology, since elevation data contains a lot of information pertaining to geomorphological processes that influence the topography. The first derivative of topography is attitude; the second is curvature. GIS tools were developed for derivation of strike, dip, curvature and curvature orientation from Digital Elevation Models (DEMs). A method for displaying both strike and dip simultaneously as colour-coded visualization (AVA) was implemented. A plug-in for calculating strike and dip via Least Squares Regression was created first using VB.NET. Further research produced a more computationally efficient solution, convolution filtering, which was implemented as Python scripts. These scripts were also used for calculation of curvature and curvature orientation. The application of these tools was demonstrated by performing morphometric studies on datasets from Earth and Mars. The tools show promise, however more work is needed to explore their full potential and possible uses.

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This paper studies seemingly unrelated linear models with integrated regressors and stationary errors. By adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by feasible generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. Simulation results suggest that this new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of purchasing power parity (PPP) among the G-7 countries. The test based on the efficient estimates rejects the PPP hypothesis for most countries.

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This paper proposes finite-sample procedures for testing the SURE specification in multi-equation regression models, i.e. whether the disturbances in different equations are contemporaneously uncorrelated or not. We apply the technique of Monte Carlo (MC) tests [Dwass (1957), Barnard (1963)] to obtain exact tests based on standard LR and LM zero correlation tests. We also suggest a MC quasi-LR (QLR) test based on feasible generalized least squares (FGLS). We show that the latter statistics are pivotal under the null, which provides the justification for applying MC tests. Furthermore, we extend the exact independence test proposed by Harvey and Phillips (1982) to the multi-equation framework. Specifically, we introduce several induced tests based on a set of simultaneous Harvey/Phillips-type tests and suggest a simulation-based solution to the associated combination problem. The properties of the proposed tests are studied in a Monte Carlo experiment which shows that standard asymptotic tests exhibit important size distortions, while MC tests achieve complete size control and display good power. Moreover, MC-QLR tests performed best in terms of power, a result of interest from the point of view of simulation-based tests. The power of the MC induced tests improves appreciably in comparison to standard Bonferroni tests and, in certain cases, outperforms the likelihood-based MC tests. The tests are applied to data used by Fischer (1993) to analyze the macroeconomic determinants of growth.

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In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.

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This paper considers various asymptotic approximations in the near-integrated firstorder autoregressive model with a non-zero initial condition. We first extend the work of Knight and Satchell (1993), who considered the random walk case with a zero initial condition, to derive the expansion of the relevant joint moment generating function in this more general framework. We also consider, as alternative approximations, the stochastic expansion of Phillips (1987c) and the continuous time approximation of Perron (1991). We assess how these alternative methods provide or not an adequate approximation to the finite-sample distribution of the least-squares estimator in a first-order autoregressive model. The results show that, when the initial condition is non-zero, Perron's (1991) continuous time approximation performs very well while the others only offer improvements when the initial condition is zero.

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We study the problem of testing the error distribution in a multivariate linear regression (MLR) model. The tests are functions of appropriately standardized multivariate least squares residuals whose distribution is invariant to the unknown cross-equation error covariance matrix. Empirical multivariate skewness and kurtosis criteria are then compared to simulation-based estimate of their expected value under the hypothesized distribution. Special cases considered include testing multivariate normal, Student t; normal mixtures and stable error models. In the Gaussian case, finite-sample versions of the standard multivariate skewness and kurtosis tests are derived. To do this, we exploit simple, double and multi-stage Monte Carlo test methods. For non-Gaussian distribution families involving nuisance parameters, confidence sets are derived for the the nuisance parameters and the error distribution. The procedures considered are evaluated in a small simulation experi-ment. Finally, the tests are applied to an asset pricing model with observable risk-free rates, using monthly returns on New York Stock Exchange (NYSE) portfolios over five-year subperiods from 1926-1995.

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It is well known that standard asymptotic theory is not valid or is extremely unreliable in models with identification problems or weak instruments [Dufour (1997, Econometrica), Staiger and Stock (1997, Econometrica), Wang and Zivot (1998, Econometrica), Stock and Wright (2000, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. One possible way out consists here in using a variant of the Anderson-Rubin (1949, Ann. Math. Stat.) procedure. The latter, however, allows one to build exact tests and confidence sets only for the full vector of the coefficients of the endogenous explanatory variables in a structural equation, which in general does not allow for individual coefficients. This problem may in principle be overcome by using projection techniques [Dufour (1997, Econometrica), Dufour and Jasiak (2001, International Economic Review)]. AR-types are emphasized because they are robust to both weak instruments and instrument exclusion. However, these techniques can be implemented only by using costly numerical techniques. In this paper, we provide a complete analytic solution to the problem of building projection-based confidence sets from Anderson-Rubin-type confidence sets. The latter involves the geometric properties of “quadrics” and can be viewed as an extension of usual confidence intervals and ellipsoids. Only least squares techniques are required for building the confidence intervals. We also study by simulation how “conservative” projection-based confidence sets are. Finally, we illustrate the methods proposed by applying them to three different examples: the relationship between trade and growth in a cross-section of countries, returns to education, and a study of production functions in the U.S. economy.

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Many unit root and cointegration tests require an estimate of the spectral density function at frequency zero at some process. Kernel estimators based on weighted sums of autocovariances constructed using estimated residuals from an AR(1) regression are commonly used. However, it is known that with substantially correlated errors, the OLS estimate of the AR(1) parameter is severely biased. in this paper, we first show that this least squares bias induces a significant increase in the bias and mean-squared error of kernel-based estimators.

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Différentes méthodes ayant pour objectif une utilisation optimale d'antennes radio-fréquences spécialisées en imagerie par résonance magnétique sont développées et validées. Dans un premier temps, il est démontré qu'une méthode alternative de combinaison des signaux provenant des différents canaux de réception d'un réseau d'antennes mène à une réduction significative du biais causé par la présence de bruit dans des images de diffusion, en comparaison avec la méthode de la somme-des-carrés généralement utilisée. Cette réduction du biais engendré par le bruit permet une amélioration de l'exactitude de l'estimation de différents paramètres de diffusion et de diffusion tensorielle. De plus, il est démontré que cette méthode peut être utilisée conjointement avec une acquisition régulière sans accélération, mais également en présence d'imagerie parallèle. Dans une seconde perspective, les bénéfices engendrés par l'utilisation d'une antenne d'imagerie intravasculaire sont étudiés. Suite à une étude sur fantôme, il est démontré que l'imagerie par résonance magnétique intravasculaire offre le potentiel d'améliorer significativement l'exactitude géométrique lors de mesures morphologiques vasculaires, en comparaison avec les résultats obtenus avec des antennes de surface classiques. Il est illustré qu'une exactitude géométrique comparable à celle obtenue grâce à une sonde ultrasonique intravasculaire peut être atteinte. De plus, plusieurs protocoles basés sur une acquisition de type balanced steady-state free-precession sont comparés dans le but de mettre en évidence différentes relations entre les paramètres utilisés et l'exactitude géométrique obtenue. En particulier, des dépendances entre la taille du vaisseau, le rapport signal-sur-bruit à la paroi vasculaire, la résolution spatiale et l'exactitude géométrique atteinte sont mises en évidence. Dans une même optique, il est illustré que l'utilisation d'une antenne intravasculaire permet une amélioration notable de la visualisation de la lumière d'une endoprothèse vasculaire. Lorsque utilisée conjointement avec une séquence de type balanced steady-state free-precession utilisant un angle de basculement spécialement sélectionné, l'imagerie par résonance magnétique intravasculaire permet d'éliminer complètement les limitations normalement engendrées par l'effet de blindage radio-fréquence de l'endoprothèse.

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On étudie l’application des algorithmes de décomposition matricielles tel que la Factorisation Matricielle Non-négative (FMN), aux représentations fréquentielles de signaux audio musicaux. Ces algorithmes, dirigés par une fonction d’erreur de reconstruction, apprennent un ensemble de fonctions de base et un ensemble de coef- ficients correspondants qui approximent le signal d’entrée. On compare l’utilisation de trois fonctions d’erreur de reconstruction quand la FMN est appliquée à des gammes monophoniques et harmonisées: moindre carré, divergence Kullback-Leibler, et une mesure de divergence dépendente de la phase, introduite récemment. Des nouvelles méthodes pour interpréter les décompositions résultantes sont présentées et sont comparées aux méthodes utilisées précédemment qui nécessitent des connaissances du domaine acoustique. Finalement, on analyse la capacité de généralisation des fonctions de bases apprises par rapport à trois paramètres musicaux: l’amplitude, la durée et le type d’instrument. Pour ce faire, on introduit deux algorithmes d’étiquetage des fonctions de bases qui performent mieux que l’approche précédente dans la majorité de nos tests, la tâche d’instrument avec audio monophonique étant la seule exception importante.