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Frequency Tracking and Phasor Estimation Using Least Squares and Total Least Squares AlgorithmsGuo, Hengdao 01 January 2014 (has links)
System stability plays an important role in electric power systems. With the development of electric power system, the scale of the electric grid is now becoming larger and larger, and many renewable energy resources are integrated in the grid. However, at the same time, the stability and safety issues of electric power system are becoming more complicated. Frequency and phasors are two critical parameters of the system stability. Obtaining these two parameters have been great challenges for decades. Researchers have provided various kinds of algorithms for frequency tracking and phasor estimation. Among them, Least Squares (LS) algorithm is one of the most commonly used algorithm. This thesis studies the LS algorithm and the Total Least Squares (TLS) algorithm working on frequency tracking and phasor estimation. In order to test the performance of the two algorithms, some simulations have been made in the Matlab. The Total Vector Error (TVE) is a commonly used performance criteria, and the TVE results of the two algorithms are compared. The TLS algorithm performs better than LS algorithm when the frequencies of all harmonic components are given.
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Globalization, Migration and the U.S. Labor Market for Physicians: The Impact of Immigration on Local WagesCook, Finnie B 05 November 2009 (has links)
The healthcare labor market has experienced some significant changes in the last half century, including the establishment of Medicare and Medicaid in 1965, the emergence of managed care in the 1980s, and the worldwide mobility of labor encouraged by globalization. Currently, more than 25% of physicians working in the U.S. are foreign-born. The existing body of literature related to the impact of immigration on local wages has to date found conflicting results. The purpose of this research is to evaluate the impact of immigration of foreign physicians on local physician wages. This study employs physician survey data from the AMA Physician Masterfile for the years 1997 through 2007 combined with wage data published by the Bureau of Labor Statistics and data from other government sources. Several econometric models are employed to analyze the wage impacts of immigration, including ordinary least squares, fixed effects, two-stage least squares and a first-difference approach to control for endogenous location choice.
The results of this study provide evidence that in the short-run, the impacts of immigration of physicians on area wages is small but positive. In the long run, however, wages adjust and the impact becomes negative and statistically significant, although the magnitude of the impact of a one percentage point increase in the share of immigrant physicians in an area is less than 0.2%. The negative wage effects of immigration tend to be larger for foreign-born physicians educated in the U.S. compared with foreign-born international medical graduates.
The study also finds evidence that the negative effects of immigration tend to be offset by outflows of the lowest paid native physicians. Furthermore, physicians tend to locate in areas where wages are already higher, and foreign-born physicians are more likely than their native counterparts to work in larger cities as opposed to rural areas.
The research has important policy implications in the presence of current debate over immigration law and healthcare reform and in an era of increasing mobility of labor due to globalization.
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Comparison Of Regression Techniques Via Monte Carlo SimulationCan Mutan, Oya 01 June 2004 (has links) (PDF)
The ordinary least squares (OLS) is one of the most widely used methods for modelling the functional relationship between variables. However, this estimation procedure counts on some assumptions and the violation of these assumptions may lead to nonrobust estimates. In this study, the simple linear regression model is investigated for conditions in which the distribution of the error terms is Generalised Logistic. Some robust and nonparametric methods such as modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares, least trimmed squares (LTS), Theil and weighted Theil are compared via computer simulation. In order to evaluate the estimator performance, mean, variance, bias, mean square error (MSE) and relative mean square error (RMSE) are computed.
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Partial Least Squares for Serially Dependent DataSinger, Marco 04 August 2016 (has links)
No description available.
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O valor de marca: uma abordagem de equações estruturais / Brand equity: a structural equation modeling approachD\'Emidio, Marcelo 03 July 2009 (has links)
O presente trabalho propõe um procedimento de valoração de marca a partir de uma modelagem por equações estruturais. Este estudo aponta inicialmente um modelo conceitual de valoração de marca baseado na linha comportamental, ou seja, nas percepções dos consumidores e não no valor monetário da marca. Para aplicação do procedimento proposto, foram escolhidas as marcas das operadoras de telefonia celular Vivo e Claro. A partir da modelagem por equações estruturais, ajustou-se o modelo teórico proposto a cada uma das marcas em questão. Com o modelo ajustado foi possível calcular não apenas o valor de marca para cada um dos consumidores, como todas as variáveis que o compõe. A possibilidade de se calcular o valor de marca para cada consumidor é extremamente inovadora, uma vez que nenhum dos modelos revistos na literatura científica aponta esta funcionalidade. Com a base de dados contendo o valor de marca para cada consumidor entrevistado, foi possível efetuar diversas análises estatísticas, que permitiram compreender de forma profunda quais variáveis mais impactam o valor das marcas, ou ainda quais são seus pontos fortes e fracos. Com isto, foi possível desenhar estratégias de marketing específicas para que cada uma das marcas aumente o seu valor. / The present study brings a procedure that measures brand equity using a structural equation modeling. This thesis proposes a conceptual model that measures brand equity based in a behaviorist approach, i.e., based on the consumers perception instead of monetary brand value. To apply this procedure two cellular phone operator brands were chosen: Vivo and Claro, and then, using structural equation modeling, it was possible to adjust the initial theory model to each brand. From the adjusted model it was possible to measure not only brand equity to each consumer, but all variables that are part of it. The possibility to measure brand equity to each consumer is extremely new, once no other models - reviewed in the scientific literature - pointed this feature. Using the database and the brand value to each interviewed consumer it was possible to make statistic analysis that allowed comprehending deeply which variables impact brand equity, or what are their strong and weak points. Then it was possible to make specific marketing strategies to each brand to increase their equity.
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Model-based calibration of a non-invasive blood glucose monitorShulga, Yelena A 11 January 2006 (has links)
This project was dedicated to the problem of improving a non-invasive blood glucose monitor being developed by the VivaScan Corporation. The company has made some progress in the non-invasive blood glucose device development and approached WPI for a statistical assistance in the improvement of their model in order to predict the glucose level more accurately. The main goal of this project was to improve the ability of the non-invasive blood glucose monitor to predict the glucose values more precisely. The goal was achieved by finding and implementing the best regression model. The methods included ordinary least squared regression, partial least squares regression, robust regression method, weighted least squares regression, local regression, and ridge regression. VivaScan calibration data for seven patients were analyzed in this project. For each of these patients, the individual regression models were built and compared based on the two factors that evaluate the model prediction ability. It was determined that partial least squares and ridge regressions are two best methods among the others that were considered in this work. Using these two methods gave better glucose prediction. The additional problem of data reduction to minimize the data collection time was also considered in this work.
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Estimativa da região de estabilidade via Funções Energia Generalizadas / Estability region estimate using Generalized Energy FunctionsRibeiro, Yuri Cândido da Silva 25 August 2017 (has links)
Os fundamentos teóricos desenvolvidos neste trabalho e que dão suporte aos métodos propostos garantem que as estimativas obtidas sejam sempre conservadoras (no sentido de que elas são sempre subconjuntos da região de estabilidade verdadeira) e, portanto, possuam elevado grau de confiança ao concluir sobre a estabilidade do sistema. Os métodos apresentados consistem em extensões dos métodos Closest UEP e CUEP, utilizados na análise de estabilidade transitória de sistemas elétricos de potência, para sistemas que admitem FEG. Embora os métodos Closest UEP e CUEP forneçam estimativas de forma rápida e precisa, sua aplicação está limitada à existência de uma Função Energia (FE) para o sistema, o que consiste em uma forte limitação. Muitos sistemas não admitem FE e, mesmo quando se pode provar a existência de uma FE, a impossibilidade de exibi-la impede a aplicação dos métodos citados. Outra contribuição deste trabalho consiste em um método computacional que permite a obtenção de uma FEG para sistemas polinomiais. O método apresentado também é aplicado a uma classe de problemas não polinomiais, provenientes da modelagem de sistemas elétricos de potência, mediante uma mudança não linear de variáveis que permite a construção de um sistema polinomial equivalente. Através dos métodos apresentados, visa-se disponibilizar métodos computacionais que permitam a obtenção de estimativas rápidas e precisas e que possam ser aplicados a uma ampla classe de sistemas: aqueles que admitem FEG. Com isso, almeja-se não somente contribuir para o desenvolvimento de métodos para análise de estabilidade de sistemas elétricos de potência mas, também, disponibilizá-los a outras áreas do conhecimento. / In this work, we develop computational methods to estimate stability regions and the relevant part of stability boundary of attracting sets of nonlinear dynamical systems. Such methods are based on Generalized Energy Function (GEF) theory and, therefore, can be applied to a larger class of problems than those based on Energy Functions (EF). The theoretical foundations developed in this work, which support the proposed methods, ensure that the estimates are always conservative (in the sense that they are subsets of the true stability region), providing high confidence level when asserting the stability of a system. The presented methods are extensions of the Closest UEP and the CUEP methods, used in the assessment of stability of electrical power systems, to the systems that admit GEF. Even though the Closest UEP and CUEP methods provide estimates in a fast and accurate way, they are only applicable to systems that admit EFs, which consists in a strong limitation for their usage. Many systems do not admit EF and, even if it is possible to prove the existence of an EF, the impossibility to exhibit it in the form of elementary mathematical functions prevents the application of such methods. Other contribution of this work is a computational method to obtain a GEF for polinomial systems. We also applied the presented method to a class of non polinomial systems arising from electrical power system models, after a nonlinear change of variables that provides an equivalent polinomial system. By means of the proposed methods, we aim to offer computational methods to allow fast and accurate stability region estimates which could be used in a broad class of dynamical systems: those that admit GEF. This way, we plan to contribute for the development of methods used in the assessment of stability of electrical power systems and make such tools available to systems from other areas of science.
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Estimativa da região de estabilidade via Funções Energia Generalizadas / Estability region estimate using Generalized Energy FunctionsYuri Cândido da Silva Ribeiro 25 August 2017 (has links)
Os fundamentos teóricos desenvolvidos neste trabalho e que dão suporte aos métodos propostos garantem que as estimativas obtidas sejam sempre conservadoras (no sentido de que elas são sempre subconjuntos da região de estabilidade verdadeira) e, portanto, possuam elevado grau de confiança ao concluir sobre a estabilidade do sistema. Os métodos apresentados consistem em extensões dos métodos Closest UEP e CUEP, utilizados na análise de estabilidade transitória de sistemas elétricos de potência, para sistemas que admitem FEG. Embora os métodos Closest UEP e CUEP forneçam estimativas de forma rápida e precisa, sua aplicação está limitada à existência de uma Função Energia (FE) para o sistema, o que consiste em uma forte limitação. Muitos sistemas não admitem FE e, mesmo quando se pode provar a existência de uma FE, a impossibilidade de exibi-la impede a aplicação dos métodos citados. Outra contribuição deste trabalho consiste em um método computacional que permite a obtenção de uma FEG para sistemas polinomiais. O método apresentado também é aplicado a uma classe de problemas não polinomiais, provenientes da modelagem de sistemas elétricos de potência, mediante uma mudança não linear de variáveis que permite a construção de um sistema polinomial equivalente. Através dos métodos apresentados, visa-se disponibilizar métodos computacionais que permitam a obtenção de estimativas rápidas e precisas e que possam ser aplicados a uma ampla classe de sistemas: aqueles que admitem FEG. Com isso, almeja-se não somente contribuir para o desenvolvimento de métodos para análise de estabilidade de sistemas elétricos de potência mas, também, disponibilizá-los a outras áreas do conhecimento. / In this work, we develop computational methods to estimate stability regions and the relevant part of stability boundary of attracting sets of nonlinear dynamical systems. Such methods are based on Generalized Energy Function (GEF) theory and, therefore, can be applied to a larger class of problems than those based on Energy Functions (EF). The theoretical foundations developed in this work, which support the proposed methods, ensure that the estimates are always conservative (in the sense that they are subsets of the true stability region), providing high confidence level when asserting the stability of a system. The presented methods are extensions of the Closest UEP and the CUEP methods, used in the assessment of stability of electrical power systems, to the systems that admit GEF. Even though the Closest UEP and CUEP methods provide estimates in a fast and accurate way, they are only applicable to systems that admit EFs, which consists in a strong limitation for their usage. Many systems do not admit EF and, even if it is possible to prove the existence of an EF, the impossibility to exhibit it in the form of elementary mathematical functions prevents the application of such methods. Other contribution of this work is a computational method to obtain a GEF for polinomial systems. We also applied the presented method to a class of non polinomial systems arising from electrical power system models, after a nonlinear change of variables that provides an equivalent polinomial system. By means of the proposed methods, we aim to offer computational methods to allow fast and accurate stability region estimates which could be used in a broad class of dynamical systems: those that admit GEF. This way, we plan to contribute for the development of methods used in the assessment of stability of electrical power systems and make such tools available to systems from other areas of science.
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Hushålls efterfrågan på specifika bostadsrättsattributDalnor Lindström, Ulrica, Tjernell, Carin January 2010 (has links)
<p><strong>Syfte:</strong> Syftet är att försöka urskilja samband mellan hushålls socioekonomiska faktorer och efterfrågan på specifika bostadsattribut. Vår frågeställning är: Finns det samband mellan vilka specifika attribut som efterfrågas hos bostadsrätter och hushålls socioekonomiska faktorer? Vår förhoppning är att åtminstone få en indikation på vad olika typer av hushåll efterfrågar.<strong>Metod: </strong>Denna studie baseras på en databas bestående av bostadsrättsförsäljningar som skett i Gävle under år 2008 samt socioekonomisk information om de hushåll som förvärvat dessa bostadsrätter. För att estimera hushålls efterfrågan på ett specifikt bostadsrättsattribut har en tvåstegsmetod använts. I ett första steg avslöjas de underförstådda marginalpriserna av bostadsrätters egenskaper med hjälp av den hedoniska metoden. Dessa marginalpriser används i ett andra steg där efterfrågeekvationer för enskilda bostadsrättsattribut estimeras. Beräkningarna utförs i statistikprogrammet EViews.<strong>Resultat & slutsats: </strong>Resultatet visar att vissa bostadsrättsattribut kan sammankopplas med hushålls socioekonomiska faktorer. Vidare visar resultatet tydliga men mycket svaga mönster vad gäller efterfrågan på marknaden, trots att prisstrukturen på samma marknad är oerhört utmärkande. Vi kan konstatera att prissättningen på bostadsrätters attribut är väldigt tydlig medan konsumtionen av samma attribut är otydlig.<strong>Förslag till fortsatt forskning:</strong> Intressant vore att jämföra studier av denna typ med hyresmarknadens hyressättningsmodell och se om den utgår från samma värdering av bostadens attribut som det visat sig att hushåll efterfrågar. Ytterligare ett förslag är att skatta en faktisk boendekostnad för samtliga hushåll i datamaterialet och använda disponibel inkomst istället för taxerad förvärvsinkomst i efterfrågefunktionen.<strong>Uppsatsens bidrag: </strong>Studien har visat hur man kan estimera och finna samband mellan bostadsattribut och hushålls socioekonomiska faktorer. Därutöver har problemet med endogenitet behandlats genom instrumentvariabler och en uppdelning av datamaterialet i fyra delområden.</p> / <p><strong>Aim:</strong> The purpose of this study is to try to distinguish a relationship between household socio-economic factors and the demand for specific housing attributes. Our question is: Is there a connection between the specific attributes requested by households and its socio-economic factors? Our hope is to at least get an indication of what different types of households demand.<strong>Method:</strong> This study is based on information of tenant-owner flats sales made in Gävle in 2008 as well as socio-economic information of those households who bought these flats. In order to estimate demand for a specific housing attribute a two-step method is used. In a first step the implicit marginal prices of housing attributes are revealed by the hedonic method. These marginal rates are used in a second step to reveal the specific household demand for individual housing attributes. The calculations are made in the statistical program EViews.<strong>Result & Conclusions: </strong>The result shows that some housing attributes can be linked with household socio-economic factors. The result shows a clear but very weak pattern of demand in the market, despite that the price structure in the same market is extremely remarkable. We note that the prices of housing attributes are very clear while the consumption of the same attributes is unclear.<strong>Suggestions for future research: </strong>It would be interesting to compare the results of this type of study with rental markets rent-model and see if it is based on the same valuation of the dwelling attributes that household’s demand. Another proposal is to estimate the actual housing costs for all of the households in the data and use disposable income rather than actual income in the demand function.<strong>Contribution of the thesis: </strong>The study has revealed how to estimate and identify household demand for specific housing attributes. In addition, the problem of endogeneity has been treated with instrument variables and a separation of the data set into four submarkets.</p>
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Hushålls efterfrågan på specifika bostadsrättsattributDalnor Lindström, Ulrica, Tjernell, Carin January 2010 (has links)
Syfte: Syftet är att försöka urskilja samband mellan hushålls socioekonomiska faktorer och efterfrågan på specifika bostadsattribut. Vår frågeställning är: Finns det samband mellan vilka specifika attribut som efterfrågas hos bostadsrätter och hushålls socioekonomiska faktorer? Vår förhoppning är att åtminstone få en indikation på vad olika typer av hushåll efterfrågar.Metod: Denna studie baseras på en databas bestående av bostadsrättsförsäljningar som skett i Gävle under år 2008 samt socioekonomisk information om de hushåll som förvärvat dessa bostadsrätter. För att estimera hushålls efterfrågan på ett specifikt bostadsrättsattribut har en tvåstegsmetod använts. I ett första steg avslöjas de underförstådda marginalpriserna av bostadsrätters egenskaper med hjälp av den hedoniska metoden. Dessa marginalpriser används i ett andra steg där efterfrågeekvationer för enskilda bostadsrättsattribut estimeras. Beräkningarna utförs i statistikprogrammet EViews.Resultat & slutsats: Resultatet visar att vissa bostadsrättsattribut kan sammankopplas med hushålls socioekonomiska faktorer. Vidare visar resultatet tydliga men mycket svaga mönster vad gäller efterfrågan på marknaden, trots att prisstrukturen på samma marknad är oerhört utmärkande. Vi kan konstatera att prissättningen på bostadsrätters attribut är väldigt tydlig medan konsumtionen av samma attribut är otydlig.Förslag till fortsatt forskning: Intressant vore att jämföra studier av denna typ med hyresmarknadens hyressättningsmodell och se om den utgår från samma värdering av bostadens attribut som det visat sig att hushåll efterfrågar. Ytterligare ett förslag är att skatta en faktisk boendekostnad för samtliga hushåll i datamaterialet och använda disponibel inkomst istället för taxerad förvärvsinkomst i efterfrågefunktionen.Uppsatsens bidrag: Studien har visat hur man kan estimera och finna samband mellan bostadsattribut och hushålls socioekonomiska faktorer. Därutöver har problemet med endogenitet behandlats genom instrumentvariabler och en uppdelning av datamaterialet i fyra delområden. / Aim: The purpose of this study is to try to distinguish a relationship between household socio-economic factors and the demand for specific housing attributes. Our question is: Is there a connection between the specific attributes requested by households and its socio-economic factors? Our hope is to at least get an indication of what different types of households demand.Method: This study is based on information of tenant-owner flats sales made in Gävle in 2008 as well as socio-economic information of those households who bought these flats. In order to estimate demand for a specific housing attribute a two-step method is used. In a first step the implicit marginal prices of housing attributes are revealed by the hedonic method. These marginal rates are used in a second step to reveal the specific household demand for individual housing attributes. The calculations are made in the statistical program EViews.Result & Conclusions: The result shows that some housing attributes can be linked with household socio-economic factors. The result shows a clear but very weak pattern of demand in the market, despite that the price structure in the same market is extremely remarkable. We note that the prices of housing attributes are very clear while the consumption of the same attributes is unclear.Suggestions for future research: It would be interesting to compare the results of this type of study with rental markets rent-model and see if it is based on the same valuation of the dwelling attributes that household’s demand. Another proposal is to estimate the actual housing costs for all of the households in the data and use disposable income rather than actual income in the demand function.Contribution of the thesis: The study has revealed how to estimate and identify household demand for specific housing attributes. In addition, the problem of endogeneity has been treated with instrument variables and a separation of the data set into four submarkets.
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