نتایج جستجو برای: least squares monte carlo method
تعداد نتایج: 1994221 فیلتر نتایج به سال:
This paper concerns the Monte Carlo method in pricing American-style options under the general class of exponential Lévy models. Traditionally, one must store all the intermediate asset prices so that they can be used for the backward pricing in the least squares algorithm. Therefore the storage requirement grows like O(mn), where m is the number of time steps and n is the number of simulated p...
Political scientists often and increasingly analyze time-series cross-sectional (TSCS) data. These data come with signficant problems, such as accounting for unobserved variation across sample units and appropriately specifying dynamics. Furthermore, even though fixed-effects (or least squares dummy variable (LSDV) models) can address unit heterogeneity, least squares (LS) estimation of modelds...
Since MEG and EEG inverse problems are "illposed" (i.e., solutions cannot be uniquely determined), additional information such as fMRI and PET activation data can be used to impose additional constraints [1]-[6]. For example, fMRI data were used to fix the locations of equivalent current dipoles at activation areas [1][2][5] or to give higher weights for finding dipoles at activation areas [3][...
The estimation of average-power dissipation of a circuit through exhaustive simulation is impractical due to the large number of primary inputs and their combinations. In this brief, two algorithms based on least square estimation are proposed for determining the average power dissipation in complementary metal–oxide–semiconductor (CMOS) circuits. Least square estimation converges faster by att...
The Monte Carlo – Library Least-Squares (MCLLS) approach has now been developed, implemented, and tested for solving the inverse problem of EDXRF sample analysis. It consists of a linear library least-squares (LLS) code and a comprehensive Monte Carlo code named CEARXRF that is capable of calculating the unknown sample spectrum, all the elemental library spectra in the sample, and the different...
A highway system development involves huge irreversible investments, and requires rigorous modeling and analysis before the implementation decision is made. This decision-making process is embedded with multiple uncertainties due to changes in political, social, and environmental contexts. In this paper, we present a multistage stochastic model for decision making in highway development, operat...
Credit risk transition probabilities between aggregate portfolio classes constitute a very useful tool when individual transition data are not available. Jones (2005) estimates Markovian Credit Transition Matrices using an adjusted least squares method. Given the arguments of Judge and Takayama (1966) a least squares estimator under inequality constraints is consistent but has unknown distribut...
The operations of merchant energy trading in wholesale markets across different locations and current and future dates can be represented as a network where storage and transport trades compete for the capacity of storage and transport assets. We study the tradeoff between storage and transport trading for a network with a single storage asset and multiple transport assets, a realistic situatio...
In this paper, we study the asymptotic distributions for least-squares (OLS), fully modi ed (FM), and dynamic OLS (DOLS) estimators in cointegrated regression models in panel data. We show that the OLS, FM, and DOLS estimators are all asymptotically normally distributed. However, the asymptotic distribution of the OLS estimator is shown to have a non-zero mean. Monte Carlo results examine the s...
Power estimation is an important issue in digital VLSI circuit design. The estimation of average power dissipation of a circuit through exhaustive simulation is impractical due to the large number of primary inputs and their combinations. In this paper, two algorithms based on least square estimation are proposed for determining the average power dissipation in CMOS circuits. Least square estim...
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