905 resultados para partial least-squares regression
Resumo:
The Maximum Capture problem (MAXCAP) is a decision model that addresses the issue of location in a competitive environment. This paper presents a new approach to determine which store s attributes (other than distance) should be included in the newMarket Capture Models and how they ought to be reflected using the Multiplicative Competitive Interaction model. The methodology involves the design and development of a survey; and the application of factor analysis and ordinary least squares. Themethodology has been applied to the supermarket sector in two different scenarios: Milton Keynes (Great Britain) and Barcelona (Spain).
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We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.
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Time-lapse geophysical measurements are widely used to monitor the movement of water and solutes through the subsurface. Yet commonly used deterministic least squares inversions typically suffer from relatively poor mass recovery, spread overestimation, and limited ability to appropriately estimate nonlinear model uncertainty. We describe herein a novel inversion methodology designed to reconstruct the three-dimensional distribution of a tracer anomaly from geophysical data and provide consistent uncertainty estimates using Markov chain Monte Carlo simulation. Posterior sampling is made tractable by using a lower-dimensional model space related both to the Legendre moments of the plume and to predefined morphological constraints. Benchmark results using cross-hole ground-penetrating radar travel times measurements during two synthetic water tracer application experiments involving increasingly complex plume geometries show that the proposed method not only conserves mass but also provides better estimates of plume morphology and posterior model uncertainty than deterministic inversion results.
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The analysis of multiexponential decays is challenging because of their complex nature. When analyzing these signals, not only the parameters, but also the orders of the models, have to be estimated. We present an improved spectroscopic technique specially suited for this purpose. The proposed algorithm combines an iterative linear filter with an iterative deconvolution method. A thorough analysis of the noise effect is presented. The performance is tested with synthetic and experimental data.
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Whereas numerical modeling using finite-element methods (FEM) can provide transient temperature distribution in the component with enough accuracy, it is of the most importance the development of compact dynamic thermal models that can be used for electrothermal simulation. While in most cases single power sources are considered, here we focus on the simultaneous presence of multiple sources. The thermal model will be in the form of a thermal impedance matrix containing the thermal impedance transfer functions between two arbitrary ports. Eachindividual transfer function element ( ) is obtained from the analysis of the thermal temperature transient at node ¿ ¿ after a power step at node ¿ .¿ Different options for multiexponential transient analysis are detailed and compared. Among the options explored, small thermal models can be obtained by constrained nonlinear least squares (NLSQ) methods if the order is selected properly using validation signals. The methods are applied to the extraction of dynamic compact thermal models for a new ultrathin chip stack technology (UTCS).
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Objective: Health status measures usually have an asymmetric distribution and present a highpercentage of respondents with the best possible score (ceiling effect), specially when they areassessed in the overall population. Different methods to model this type of variables have beenproposed that take into account the ceiling effect: the tobit models, the Censored Least AbsoluteDeviations (CLAD) models or the two-part models, among others. The objective of this workwas to describe the tobit model, and compare it with the Ordinary Least Squares (OLS) model,that ignores the ceiling effect.Methods: Two different data sets have been used in order to compare both models: a) real datacomming from the European Study of Mental Disorders (ESEMeD), in order to model theEQ5D index, one of the measures of utilities most commonly used for the evaluation of healthstatus; and b) data obtained from simulation. Cross-validation was used to compare thepredicted values of the tobit model and the OLS models. The following estimators werecompared: the percentage of absolute error (R1), the percentage of squared error (R2), the MeanSquared Error (MSE) and the Mean Absolute Prediction Error (MAPE). Different datasets werecreated for different values of the error variance and different percentages of individuals withceiling effect. The estimations of the coefficients, the percentage of explained variance and theplots of residuals versus predicted values obtained under each model were compared.Results: With regard to the results of the ESEMeD study, the predicted values obtained with theOLS model and those obtained with the tobit models were very similar. The regressioncoefficients of the linear model were consistently smaller than those from the tobit model. In thesimulation study, we observed that when the error variance was small (s=1), the tobit modelpresented unbiased estimations of the coefficients and accurate predicted values, specially whenthe percentage of individuals wiht the highest possible score was small. However, when theerrror variance was greater (s=10 or s=20), the percentage of explained variance for the tobitmodel and the predicted values were more similar to those obtained with an OLS model.Conclusions: The proportion of variability accounted for the models and the percentage ofindividuals with the highest possible score have an important effect in the performance of thetobit model in comparison with the linear model.
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The cichlids of East Africa are renowned as one of the most spectacular examples of adaptive radiation. They provide a unique opportunity to investigate the relationships between ecology, morphological diversity, and phylogeny in producing such remarkable diversity. Nevertheless, the parameters of the adaptive radiations of these fish have not been satisfactorily quantified yet. Lake Tanganyika possesses all of the major lineages of East African cichlid fish, so by using geometric morphometrics and comparative analyses of ecology and morphology, in an explicitly phylogenetic context, we quantify the role of ecology in driving adaptive speciation. We used geometric morphometric methods to describe the body shape of over 1000 specimens of East African cichlid fish, with a focus on the Lake Tanganyika species assemblage, which is composed of more than 200 endemic species. The main differences in shape concern the length of the whole body and the relative sizes of the head and caudal peduncle. We investigated the influence of phylogeny on similarity of shape using both distance-based and variance partitioning methods, finding that phylogenetic inertia exerts little influence on overall body shape. Therefore, we quantified the relative effect of major ecological traits on shape using phylogenetic generalized least squares and disparity analyses. These analyses conclude that body shape is most strongly predicted by feeding preferences (i.e., trophic niches) and the water depths at which species occur. Furthermore, the morphological disparity within tribes indicates that even though the morphological diversification associated with explosive speciation has happened in only a few tribes of the Tanganyikan assemblage, the potential to evolve diverse morphologies exists in all tribes. Quantitative data support the existence of extensive parallelism in several independent adaptive radiations in Lake Tanganyika. Notably, Tanganyikan mouthbrooders belonging to the C-lineage and the substrate spawning Lamprologini have evolved a multitude of different shapes from elongated and Lamprologus-like hypothetical ancestors. Together, these data demonstrate strong support for the adaptive character of East African cichlid radiations.
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Intensity-modulated radiotherapy (IMRT) treatment plan verification by comparison with measured data requires having access to the linear accelerator and is time consuming. In this paper, we propose a method for monitor unit (MU) calculation and plan comparison for step and shoot IMRT based on the Monte Carlo code EGSnrc/BEAMnrc. The beamlets of an IMRT treatment plan are individually simulated using Monte Carlo and converted into absorbed dose to water per MU. The dose of the whole treatment can be expressed through a linear matrix equation of the MU and dose per MU of every beamlet. Due to the positivity of the absorbed dose and MU values, this equation is solved for the MU values using a non-negative least-squares fit optimization algorithm (NNLS). The Monte Carlo plan is formed by multiplying the Monte Carlo absorbed dose to water per MU with the Monte Carlo/NNLS MU. Several treatment plan localizations calculated with a commercial treatment planning system (TPS) are compared with the proposed method for validation. The Monte Carlo/NNLS MUs are close to the ones calculated by the TPS and lead to a treatment dose distribution which is clinically equivalent to the one calculated by the TPS. This procedure can be used as an IMRT QA and further development could allow this technique to be used for other radiotherapy techniques like tomotherapy or volumetric modulated arc therapy.
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PURPOSE: To compare different techniques for positive contrast imaging of susceptibility markers with MRI for three-dimensional visualization. As several different techniques have been reported, the choice of the suitable method depends on its properties with regard to the amount of positive contrast and the desired background suppression, as well as other imaging constraints needed for a specific application. MATERIALS AND METHODS: Six different positive contrast techniques are investigated for their ability to image at 3 Tesla a single susceptibility marker in vitro. The white marker method (WM), susceptibility gradient mapping (SGM), inversion recovery with on-resonant water suppression (IRON), frequency selective excitation (FSX), fast low flip-angle positive contrast SSFP (FLAPS), and iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) were implemented and investigated. RESULTS: The different methods were compared with respect to the volume of positive contrast, the product of volume and signal intensity, imaging time, and the level of background suppression. Quantitative results are provided, and strengths and weaknesses of the different approaches are discussed. CONCLUSION: The appropriate choice of positive contrast imaging technique depends on the desired level of background suppression, acquisition speed, and robustness against artifacts, for which in vitro comparative data are now available.
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BACKGROUND: Evidence regarding the effectiveness of oral vitamin B12 in patients with serum vitamin B12 levels between 125-200 pM/l is lacking. We compared the effectiveness of one-month oral vitamin B12 supplementation in patients with a subtle vitamin B12 deficiency to that of a placebo. METHODS: This multicentre (13 general practices, two nursing homes, and one primary care center in western Switzerland), parallel, randomised, controlled, closed-label, observer-blind trial included 50 patients with serum vitamin B12 levels between 125-200 pM/l who were randomized to receive either oral vitamin B12 (1000 μg daily, N = 26) or placebo (N = 24) for four weeks. The institution's pharmacist used simple randomisation to generate a table and allocate treatments. The primary outcome was the change in serum methylmalonic acid (MMA) levels after one month of treatment. Secondary outcomes were changes in total homocysteine and serum vitamin B12 levels. Blood samples were centralised for analysis and adherence to treatment was verified by an electronic device (MEMS; Aardex Europe, Switzerland). Trial registration: ISRCTN 22063938. RESULTS: Baseline characteristics and adherence to treatment were similar in both groups. After one month, one patient in the placebo group was lost to follow-up. Data were evaluated by intention-to-treat analysis. One month of vitamin B12 treatment (N = 26) lowered serum MMA levels by 0.13 μmol/l (95%CI 0.06-0.19) more than the change observed in the placebo group (N = 23). The number of patients needed to treat to detect a metabolic response in MMA after one month was 2.6 (95% CI 1.7-6.4). A significant change was observed for the B12 serum level, but not for the homocysteine level, hematocrit, or mean corpuscular volume. After three months without active treatment (at four months), significant differences in MMA levels were no longer detected. CONCLUSIONS: Oral vitamin B12 treatment normalised the metabolic markers of vitamin B12 deficiency. However, a one-month daily treatment with 1000 μg oral vitamin B12 was not sufficient to normalise the deficiency markers for four months, and treatment had no effect on haematological signs of B12 deficiency.
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Relaxation rates provide important information about tissue microstructure. Multi-parameter mapping (MPM) estimates multiple relaxation parameters from multi-echo FLASH acquisitions with different basic contrasts, i.e., proton density (PD), T1 or magnetization transfer (MT) weighting. Motion can particularly affect maps of the apparent transverse relaxation rate R2(*), which are derived from the signal of PD-weighted images acquired at different echo times. To address the motion artifacts, we introduce ESTATICS, which robustly estimates R2(*) from images even when acquired with different basic contrasts. ESTATICS extends the fitted signal model to account for inherent contrast differences in the PDw, T1w and MTw images. The fit was implemented as a conventional ordinary least squares optimization and as a robust fit with a small or large confidence interval. These three different implementations of ESTATICS were tested on data affected by severe motion artifacts and data with no prominent motion artifacts as determined by visual assessment or fast optical motion tracking. ESTATICS improved the quality of the R2(*) maps and reduced the coefficient of variation for both types of data-with average reductions of 30% when severe motion artifacts were present. ESTATICS can be applied to any protocol comprised of multiple 2D/3D multi-echo FLASH acquisitions as used in the general research and clinical setting.
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The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.
Resumo:
The factor structure of a back translated Spanish version (Lega, Caballo and Ellis, 2002) of the Attitudes and Beliefs Inventory (ABI) (Burgess, 1990) is analyzed in a sample of 250 university students.The Spanish version of the ABI is a 48-items self-report inventory using a 5-point Likert scale that assesses rational and irrational attitudes and beliefs. 24-items cover two dimensions of irrationality: a) areas of content (3 subscales), and b) styles of thinking (4 subscales).An Exploratory Factor Analysis (Parallel Analysis with Unweighted Least Squares method and Promin rotation) was performed with the FACTOR 9.20 software (Lorenzo-Seva and Ferrando, 2013).The results reproduced the main four styles of irrational thinking in relation with the three specific contents of irrational beliefs. However, two factors showed a complex configuration with important cross-loadings of different items in content and style. More analyses are needed to review the specific content and style of such items.
Resumo:
Osakemarkkinoilta on jo useiden vuosien ajan julkaistu lukuisia tutkimuksia, joissa on esitetty havaintoja ajallisesta säännönmukaisuudesta osakkeiden hinnoissa, joita ei pystytä selittämään markkinakohtaisilla fundamenteilla. Nämä niin kutsutut kalenterianomaliat esiintyvät tyypillisesti ajallisissa käännepisteissä, kuten vuoden, kuukauden tai viikon vaihtuessa seuraavaksi. Myös erilaisten katkosten, kuten juhlapyhien, kaupankäyntirutiineissa on havaittu aiheuttavan anomalioita. Tutkimuksen tavoitteena oli tutkia osakemarkkinoilla havaittujen kalenterianomalioiden esiintymistä pohjoismaisilla sähkömarkkinoilla. Tutkitut anomaliat olivat viikonpäivä- kuukausi-, kuunvaihde- ja juhlapyhäanomalia. Näiden lisäksi tutkittiin tuottojen käyttäytymistä optioiden erääntymispäivien läheisyydessä. Yksittäisten tuotteiden sijasta tarkastelut suoritettiin sesonki- ja kvartaalituotteista muodostetuilla vuosituotteilla. Testauksessa käytettiin pienimmän neliösumman menetelmää, huomioidenheteroskedastisuuden, autokorrelaation ja multikollineaarisuuden vaikutukset. Pelkkien kalenterimuuttujien lisäksi testit suoritettiin regressiomalleilla, joissa lisäselittäjinä käytettiin spot-hintaa, päästöoikeuden hintaa ja/tai sade-ennusteita. Tarkastelujakso koostui vuosista 1998-2006.