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ACCURATE PARAMETER ESTIMATION FOR WAVE EQUATION
"... Abstractâ€”Waves arise in many physical phenomena which have applications such as describing the voltage along a transmission line and medical imaging modality of elastography. In this paper, estimating the parameters for two forms of lossy wave equations, which correspond to multimode and multidime ..."
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dimensional waves, are tackled. By exploiting the linear prediction property of the noisefree signals, an iterative quadratic maximum likelihood (IQML) approach is devised for accurate parameter estimation. Simulation results show that the estimation performance of the proposed IQML algorithms can attain
Accurate Parameter Estimation for an Articulatory Speech Synthesizer with an Improved Neural Network Mapping
"... Neural network (NN) applications have recently been employed to extract the parameters of an articulatory speech synthesizer from a given speech signal. Results from these attempts showed that a single NN is insucient to cover all of the possible congurations uniquely. Moreover, apart from their co ..."
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for the eect of the input distribution characteristics on neural learning has been detailed elsewhere [3]. Empirical results for a more correct estimation of articulatory speech synthesizer parameters through exploiting the behavior of the Back Propagation (BP) algorithm are focused on here. 1.
Research Article Accurate Parameter Estimation for Unbalanced ThreePhase System
"... which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Smart grid is an intelligent power generation and control console in modern electricity networks, where the unbalanced threephase power system is the commonly used model. Here ..."
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. Here, parameter estimation for this system is addressed. After converting the threephase waveforms into a pair of orthogonal signals via the
Accurate parameter estimation for star formation history in galaxies using SDSS spectra
, 2009
"... Determining the physical parameters of large samples of galaxies is crucial to constrain our knowledge of the complicated physical processes that govern the formation and evolution of these systems. Ultimately, we seek methods that ..."
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Cited by 1 (1 self)
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Determining the physical parameters of large samples of galaxies is crucial to constrain our knowledge of the complicated physical processes that govern the formation and evolution of these systems. Ultimately, we seek methods that
A Simple, Fast, and Accurate Algorithm to Estimate Large Phylogenies by Maximum Likelihood
, 2003
"... The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The ..."
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Cited by 2109 (30 self)
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The increase in the number of large data sets and the complexity of current probabilistic sequence evolution models necessitates fast and reliable phylogeny reconstruction methods. We describe a new approach, based on the maximumlikelihood principle, which clearly satisfies these requirements. The core of this method is a simple hillclimbing algorithm that adjusts tree topology and branch lengths simultaneously. This algorithm starts from an initial tree built by a fast distancebased method and modifies this tree to improve its likelihood at each iteration. Due to this simultaneous adjustment of the topology and branch lengths, only a few iterations are sufficient to reach an optimum. We used extensive and realistic computer simulations to show that the topological accuracy of this new method is at least as high as that of the existing maximumlikelihood programs and much higher than the performance of distancebased and parsimony approaches. The reduction of computing time is dramatic in comparison with other maximumlikelihood packages, while the likelihood maximization ability tends to be higher. For example, only 12 min were required on a standard personal computer to analyze a data set consisting of 500 rbcL sequences with 1,428 base pairs from plant plastids, thus reaching a speed of the same order as some popular distancebased and parsimony algorithms. This new method is implemented in the PHYML program, which is freely available on our web page:
Answering the Skeptics: Yes, Standard Volatility Models Do Provide Accurate Forecasts
"... Volatility permeates modern financial theories and decision making processes. As such, accurate measures and good forecasts of future volatility are critical for the implementation and evaluation of asset and derivative pricing theories as well as trading and hedging strategies. In response to this, ..."
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Cited by 553 (47 self)
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, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility at the daily and lower frequencies using ARCH and stochastic volatility type models. Most of these studies find highly significant insample parameter estimates and pronounced intertemporal
Accurate Unlexicalized Parsing
 IN PROCEEDINGS OF THE 41ST ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS
, 2003
"... We demonstrate that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar. Indeed, its ..."
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Cited by 1026 (70 self)
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We demonstrate that an unlexicalized PCFG can parse much more accurately than previously shown, by making use of simple, linguistically motivated state splits, which break down false independence assumptions latent in a vanilla treebank grammar. Indeed, its
Powerlaw distributions in empirical data
 ISSN 00361445. doi: 10.1137/ 070710111. URL http://dx.doi.org/10.1137/070710111
, 2009
"... Powerlaw distributions occur in many situations of scientific interest and have significant consequences for our understanding of natural and manmade phenomena. Unfortunately, the empirical detection and characterization of power laws is made difficult by the large fluctuations that occur in the t ..."
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Cited by 589 (7 self)
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in the tail of the distribution. In particular, standard methods such as leastsquares fitting are known to produce systematically biased estimates of parameters for powerlaw distributions and should not be used in most circumstances. Here we describe statistical techniques for making accurate parameter
The Mathematics of Statistical Machine Translation: Parameter Estimation
 COMPUTATIONAL LINGUISTICS
, 1993
"... ..."
Estimation and Inference in Econometrics
, 1993
"... The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas o ..."
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Cited by 1151 (3 self)
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The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas of bootstrap inference. The paper discusses Monte Carlo tests, several types of bootstrap test, and bootstrap confidence intervals. Although bootstrapping often works well, it does not do so in every case.
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