Semiparametric Estimation and Inference in Multinomial Choice Models

The purpose of this paper is to incorporate semiparametric alternatives to maximum likelihood estimation and inference in the context of unordered multinomial response data when in practice there is often insufficient information to specify the parametric form of the function linking the observables to the unknown probabilities. We specify the function linking the observables to the unknown probabilities using a very general flexible class of functions belonging to the Pearson system of cumulative distribution equations. In this setting we consider the observations as arising from a multinomial distribution characterized by one of the CDFs in the Pearson system. Given this situation, it is possible to utilize the concept of unbiased estimating functions (EFs), combined with the concept of empirical likelihood (EL) to define an (empirical) likelihood function for the parameter vector based on a nonparametric representation of the sample's PDF. This leads to the concept of maximum empirical likelihood (MEL) estimation and inference, which is analogous to parametric maximum likelihood methods in many respects.Demand and Price Analysis,

A STRUCTURAL-EQUATION GME ESTIMATOR

A generalized maximum entropy estimator is developed for the linear simultaneous equations systems model. We provide results on large and small sample properties of the estimator. Empirical results illustrate efficiency advantages of the generalized maximum entropy estimator proposed in this study over traditional estimators (e.g., 2SLS and 3SLS).Research Methods/ Statistical Methods,

A Decision Framework for Optimal Pairing of Wind and Demand Response Resources

Day-ahead electricity markets do not readily accommodate power from intermittent resources such as wind because of the scheduling difficulties presented by the uncertainty and variability in these resources. Numerous entities have developed methods to improve wind forecasting and thereby reduce the uncertainty in a day-ahead schedule for wind power generation. This paper introduces a decision framework for addressing the inevitable remaining variability resulting from imperfect forecasts. The framework uses a paired resource, such as demand response, gas turbine, or storage, to mitigate the generation scheduling errors due to wind forecast error. The methodology determines the cost-effective percentage, or adjustment factor, of the forecast error to mitigate at each successive market stage, e.g., 1 h and 10 min ahead of dispatch. This framework is applicable to any wind farm in a region with available pairing resources, although the magnitude of adjustment factors will be specific to each region as the factors are related to the statistics of the wind resource and the forecast accuracy at each time period. Historical wind data from New England are used to illustrate and analyze this approach. Results indicate that such resource pairing via the proposed decision framework will significantly reduce the need for an independent system operator to procure additional balancing resources when wind power participates in the markets

Wind Power Uncertainty and Power System Performance

The penetration of wind power into global electric power systems is steadily increasing, with the possibility of 30% to 80% of electrical energy coming from wind within the coming decades. At penetrations below 10% of electricity from wind, the impact of this variable resource on power system operations is manageable with historical operating strategies. As this penetration increases, new methods for operating the power system and electricity markets need to be developed. As part of this process, the expected impact of increased wind penetration needs to be better understood and quantified. This paper presents a comprehensive modeling framework, combining optimal power flow with Monte Carlo simulations used to quantify the impact of high levels of wind power generation in the power system. The impact on power system performance is analyzed in terms of generator dispatch patterns, electricity price and its standard deviation, CO2 emissions and amount of wind power spilled. Simulations with 10%, 20% and 30% wind penetration are analyzed for the IEEE 39 bus test system, with input data representing the New England region. Results show that wind power predominantly displaces natural gas fired generation across all scenarios. The inclusion of increasing amounts of wind can result in price spike events, as the system is required to dispatch down expensive demand in order to maintain the energy balance. These events are shown to be mitigated by the inclusion of demand response resources. Benefits include significant reductions in CO2 emissions, up to 75% reductions at 30% wind penetration, as compared to emissions with no wind integration

Estimating the System Costs of Wind Power Forecast Uncertainty

Uncertainty in forecasts of wind power generation raises concerns of integrating wind power into power system operations and electricity markets at acceptable costs. The analysis presented in this paper uses an optimal power flow (OPF) model in a Monte Carlo Simulation (MCS) framework to estimate the additional cost of power system operation with uncertain output from a wind farm. A base case dispatch is established along with alternate dispatches based upon a probability distribution of real time wind power generation. The cost of the uncertainty in wind power forecasts is then quantified in terms of the difference in production cost between the base case and the cost for system dispatch under scenarios drawn from the distribution of real time wind power generation. Using various regional load levels and ramp capabilities of other generators, the results from the OPF and MCS show that wind power forecast uncertainty for the test system can increase production cost between 2.5% and 11%

A test generation framework for quiescent real-time systems

We present an extension of Tretmans theory and algorithm for test generation for input-output transition systems to real-time systems. Our treatment is based on an operational interpretation of the notion of quiescence in the context of real-time behaviour. This gives rise to a family of implementation relations parameterized by observation durations for quiescence. We define a nondeterministic (parameterized) test generation algorithm that generates test cases that are sound with respect to the corresponding implementation relation. Also, the test generation is exhaustive in the sense that for each non-conforming implementation a test case can be generated that detects the non-conformance

Halotolerant bacteria in the efflorescences of a deteriorated church

7 pages, 6 figures, 3 tables, 18 references.--Proceedings of the 5th International Symposium, celebrado del 5-8, abril, 2000, en Sevilla, España.[EN]: A study on the composition of the efflorescences from the Church of Saint Jerome, Granada, Spain, and their influence on the distribution ofthe bacterial communities was carried out. The composition of the efflorescences varied depending on the location of the sampling point. The colony foming units (cfu) was related with the type of salt, with a clear difference between halite and epsomite/hexahydrite. The most abundant genera were Bacillus and Micrococcus and the abundance of bacilli could be explained by their osmotic adaptation to halophilic environments.[ES]: Se ha determinado la composición de las eflorescencias de la iglesia de San Jerónimo, en Granada, España, y relacionado con la presencia de comunidades específicas de bacterias. Existe una conexión entre el tipo de sales y las comunidades bacterianas; así, la epsomita, la sal más abundante en el templo, origina la selección de comunidades capaces de crecer a concentraciones de hasta,15% de esta sal. Sin embargo, las bacterias que basan su halotolerancia en la halita presentan un crecimiento comparativamente menor y no son significativamente estimuladas por la presencia de epsomita. Los géneros más abundantes son Bacillus y Micrococcus. La abundancia de bacilos se debe a su adaptación osmótica a ambientes salinos.This work was supported by the European Commission, project ENV4-CT98-0705, and the Research Groups RNM-179 and 201 from the Community of Andalusia.Peer reviewe

Toll-like receptor gene polymorphisms are associated with allergic rhinitis: a case control study

10.1186/1471-2350-13-66BMC Medical Genetics13-BMGM

Karakteristik Dan Hasil Uji Marshall Aspal Termodifikasi Dengan Karet Alam Terdepolimerisasi Sebagai Aditif

Aspal termodifikasi polimer merupakan salah satu jenis formula aspal dengan penambahan polimer untuk mendapatkan sifat perkerasan jalan yang lebih baik, yaitu mengurangi deformasi pada perkerasan, meningkatkan ketahanan terhadap retak dan kelekatan pada agregat. Penelitian ini telah dilakukan dengan menggunakan karet alam SIR 20 terdepolimerisasi sebagai aditif pada aspal dengan konsentrasi 3%, 5%, dan 7% b/b. Dari hasil pengujian penetrasi, titik lembek, titik nyala, dan % kehilangan berat setelah pemanasan didapatkan konsentrasi terbaik, yaitu 5%. Data hasil uji Marshall yang terdiri dari stabilitas, pelelehan, stabilitas sisa setelah perendaman, dan hasil bagi Marshall berturut-turut adalah 1135,46 kg, 3,47 mm, 91,78%, dan 327,22 kg/mm. Nilai tersebut telah memenuhi persyaratan SNI untuk aspal polimer (SNI 06-2489-91) dan memiliki sifat yang lebih baik daripada aspal tanpa penambahan aditif (kontrol). Diterima : 17 November 2014; Direvisi : 29 Januari 2015; Disetujui : 7 Mei 2015 How to Cite : Prastanto, H., Cifriadi, A., & Ramadhan, A. (2015). Karakteristik dan hasil uji marshall aspal termodifikasi dengan karet alam terdepolimerisasi sebagai aditif. Jurnal Penelitian Karet, 33(1), 75-82. Retrieved from http://ejournal.puslitkaret.co.id/index.php/jpk/article/view/17