Gaussian distribution
Melipona GARBAGE BEES RELEASE THEIR CARGO ACCORDING TO A GAUSSIAN DISTRIBUTION
... a Gaussian distribution is not gen- eral to all meliponid species; workers of Lestri- melitta limao, the pirate bee for instance, release the garbage right in front of the ...
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Degradation modeling for reliability analysis with time-dependent structure based on the inverse gaussian distribution
... lifetime distribution without actually observing ...Gaussian distribution. Initially, we introduced the inverse Gaussian deterioration rate model for degradation data and a study of its ...
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Detecting physically unrealistic outliers in ACE-FTS atmospheric measurements
... The often used method for detecting outliers of employing the MAD does not explicitly make use of a PDF, but, in or- der for it to be useful, it does make an implicit assumption that the PDF is approximately symmetric ...
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Braz. J. Phys. vol.38 número4
... double Gaussian in the metal- semiconductor (MS) contacts can be attributed to the nature of their inhomogeneities in the two ...second Gaussian distribution at very low temperatures may possibly ...
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The influence of the new ECMWF Ensemble Prediction System resolution on wind power forecast accuracy and uncertainty estimation
... a Gaussian distribution; the ratio between the RMSE, calculated on the training period between measured wind speed and the MOS-corrected ensemble mean, and the mean of the standard deviation of the ensemble ...
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Non-Gaussian Stochastic Volatility Model with Jumps via Gibbs Sampler
... A simple model designed to describe high volatility assets behavior was developed by Schwartz and Smith (2000) [22]. Their model consists of decomposing the asset log returns in the short-term deviation in prices and the ...
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PREDICTIVE ANALYTICS VIA GAUSSIAN PROCESSES AND STATISTICAL AUDIT VIA GAUSSIAN MIXTURES IN
... a Gaussian process is completely determined by its mean and covariance functions, which reduces the amount of parameters to be specified since only the first and second order moments of the process are ...
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Bayesian calibration of simultaneity in audiovisual temporal order judgments.
... a Gaussian distribution biased toward ‘‘sound first’’ (blue solid Gaussian curve in Figure 2A; mean 6 SD, –80680 ms); and in the light-first condition, stimulation intervals were selected from a ...
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Defective Models for Cure Rate Modeling
... Another way to model cure rates is to use defective distributions, as explored in this thesis. Defective distributions are characterized by having probability density functions which integrate to values less than 1 when ...
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VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS
... component distribution of the extracted speech feature ...multiple Gaussian distributions describing the single state so as to conform to the ANN model and also to enable the model capture more variations ...
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Optimal exercise strategies for operational risk insurance via multiple stopping times
... Loss Distribution Approach (LDA) framework which involves modelling annual losses via a compound ...Inverse-Gaussian distribution and two generic types of insur- ance mitigation, we are able to ...
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Multi-compartment T2 relaxometry using a spatially constrained multi-Gaussian model.
... single Gaussian distribution was found to outperform monoexponential models in brain tissue [19] – here we have extended this to multiple ...of Gaussian shape is motivated by simplicity and the fact ...
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Level density for deformations of the Gaussian orthogonal ensemble
... Our method extends that of Wigner f22g, who showed, by assuming that terms containing patterns of unlinked binary associations dominate the averages of the traces of powers of matrices, that the level density for certain ...
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Analytical evaluation of nonlinear effects in MC-CDMA signals
... proximately Gaussian-distributed at the subcarrier level [7], D k eq is also approximately Gaussian-distributed, even when the number of users is ...ideal Gaussian channel is approximately given ...
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Current Transformer Saturation Detection Using Gaussian Mixture Models
... and provide better flexibility and precision in modeling the underlying statistics of sample data. For an S-class pattern recognition system, a set of GMMs { 1 , 2 ,..., S } are associated with S classes. A random ...
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A GAUSSIAN PROCESS BASED MULTI-PERSON INTERACTION MODEL
... The remainder of this paper is structured as follows: First we review the related work on the topic of visual multi-pedestrian tracking with a focus on approaches that investigate motion con- text, and on the topic of ...
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João Beleza Teixeira Seixas e Sousa
... A common problem that arises in mathematical finance when using models with parameters estimated from market data, available until a certain time, is that of checking the necessity of using new parameters as newer data ...
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Braz. J. Phys. vol.37 número3A
... The NA49 experiment at CERN SPS has acquired a huge data set of Pb+Pb events over a broad range of energy and centrality during the last several years. This high statistics data set, coupled with a state-of-the-art ...
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Image Classifying Registration for Gaussian & Bayesian Techniques: A Review
... posterior distribution of model parameters. The posterior distribution can best be understood as a weighted average between knowledge about the parameters before data is observed (which is represented by ...
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Recurrent gaussian processes and robust dynamical modeling
... The aforementioned restrictions could hinder the GP-RLARX model’s capability to learn more complex dynamics from outlier-corrupted data. Bearing this in mind, we can extend GP-RLARX by including an additional GP to model ...
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