نتایج جستجو برای: regressive conditional hetroscedasticity

تعداد نتایج: 62799  

Journal: :J. Comb. Theory, Ser. A 1999
Menachem Kojman Saharon Shelah

We give an elementary proof of the fact that regressive Ramsey numbers are Ackermannian. This fact was first proved by Kanamori and McAloon with mathematical logic techniques. Nous vivons encore sous le règne de la logique, voilà, bien entendu, à quoi je voulais en venir. Mais les procédés logiques, de nos jours, ne s’appliquent plus qu’à la résolution de problèmes d’intérêt secondaire. [1, 192...

2016
Lucas W. Davis Christopher R. Knittel

Despite widespread agreement that a carbon tax would be more efficient, many countries use fuel economy standards to reduce transportation-related carbon dioxide emissions. We pair a simple model of the automakers’ profit maximization problem with unusually-rich nationally representative data on vehicle registrations to estimate the distributional impact of U.S. fuel economy standards. The key ...

2016
Mehdi Khashei Mohammad Ali Montazeri Mehdi Bijari

In today’s world, using quantitative methods are very important for financial markets forecast, improvement of decisions and investments. In recent years, various time series forecasting methods have been proposed for financial markets forecasting. In each case, the accuracy of time series methods fundamental to make decision and hence the research for improving the effectiveness of forecasting...

Journal: Iranian Economic Review 2014
Arian Daneshmand Mahnoush Abdollah Milani

The regressive nature of consumption taxes poses a challenge to partisan theory. Using data for up to 20 OECD countries in the period 1970-2003 this article aims to explore the question of whether the idea that social democratic governments typically have to compromise on policy goals and core constituency interests to make themselves more appealing to the median voter necessitates the use of r...

2002
Riadh Kallel Joseph Rynkiewicz

This work concernes the contrast difference test and its asymptotic properties for non linear auto-regressive models. Our approach is based on an application of the parametric bootstrap method. It is a re-sampling method based on the estimate parameters of the models. The resulting methodology is illustrated by simulations of multilayer perceptron models, and an asymptotic justification is give...

2013
Mirjami Jutila Jarmo Prokkola Despina Triantafyllidou

We propose a novel regressive principle to Admission Control (AC) assisted by real-time passive QoS monitoring. This measurement-based AC scheme accepts flows by default, but based on the changes in the network QoS, it makes regressive decisions on the possible flow rejection, thus bringing cognition to the network path. The REgressive Admission Control (REAC) system consists of three modules p...

Journal: :Journal of health economics 2008
Owen O'Donnell Eddy van Doorslaer Ravi P Rannan-Eliya Aparnaa Somanathan Shiva Raj Adhikari Baktygul Akkazieva Deni Harbianto Charu C Garg Piya Hanvoravongchai Alejandro N Herrin Mohammed N Huq Shamsia Ibragimova Anup Karan Soon-man Kwon Gabriel M Leung Jui-fen Rachel Lu Yasushi Ohkusa Badri Raj Pande Rachel Racelis Keith Tin Kanjana Tisayaticom Laksono Trisnantoro Quan Wan Bong-Min Yang Yuxin Zhao

We estimate the distributional incidence of health care financing in 13 Asian territories that account for 55% of the Asian population. In all territories, higher-income households contribute more to the financing of health care. The better-off contribute more as a proportion of ability to pay in most low- and lower-middle-income territories. Health care financing is slightly regressive in thre...

Journal: :Annals of the Institute of Statistical Mathematics 2007

2012
Kohei Arai

In order to evaluate the skin surface temperature (SSST) estimation accuracy with MODIS data, 84 of MODIS scenes together with the match-up data of NCEP/GDAS are used. Through regressive analysis, it is found that 0.305 to 0.417 K of RMSE can be achieved. Furthermore, it also is found that band 29 is effective for atmospheric correction (30.6 to 38.8% of estimation accuracy improvement). If sin...

2012
Iuliana Paraschiv-Munteanu Ioan Tomescu

Learning from data means a process of information extraction from finite size samples in order to estimate an unknown dependency. A series of problems can be modeled in terms of a system that computes according to an unknown rule a response (output) for each input. The paper provides a series of results concerning the learning from data a linear regressive model in a multivariate framework. The...

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