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2006
In this chapter we develop further the theory of the correlation method introduced in chapter 7. Consider the expression of the pair correlation function where an ensemble average replaces the average over a time series of experiments on a single system. The pair correlation function defined in eq.
John Ross +2 more
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In this chapter we develop further the theory of the correlation method introduced in chapter 7. Consider the expression of the pair correlation function where an ensemble average replaces the average over a time series of experiments on a single system. The pair correlation function defined in eq.
John Ross +2 more
+5 more sources
Direct Density Derivative Estimation
Neural Computation, 2016Estimating the derivatives of probability density functions is an essential step in statistical data analysis. A naive approach to estimate the derivatives is to first perform density estimation and then compute its derivatives. However, this approach can be unreliable because a good density estimator does not necessarily mean a good density derivative
Sasaki, Hiroaki +3 more
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A Wave-Shaped Deep Neural Network for Smoke Density Estimation
IEEE Transactions on Image Processing, 2020Smoke density estimation from a single image is a totally new but highly ill-posed problem. To solve the problem, we stack several convolutional encoder-decoder structures together to propose a wave-shaped neural network, termed W-Net.
Feiniu Yuan +4 more
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Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks
Computer Vision and Pattern Recognition, 2019Crowd counting has recently attracted increasing interest in computer vision but remains a challenging problem. In this paper, we propose a trellis encoder-decoder network (TEDnet) for crowd counting, which focuses on generating high-quality density ...
Xiaolong Jiang +6 more
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Autoregressive Conditional Density Estimation
International Economic Review, 1994Summary: \textit{R. F. Engle's} ARCH model [Econometrica 50, 987-1007 (1982; Zbl 0491.62099)] is extended to permit parametric specifications for conditional dependence beyond the mean and variance. The suggestion is to model the conditional density with a small number of ``parameters'', and then model these parameters as functions of the conditioning ...
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IMPROVING CELLULAR DENSITY ESTIMATION
In Vitro Cellular & Developmental Biology - Animal, 2002In vitro cultures are being considered as an alternative to agricultural processes for producing valuable secondary metabolites. Most efforts that use differentiated cultures instead of cell suspension cultures have focused on transformed (hairy) roots.
José Guilherme, Chaui-Berlinck +1 more
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Density Distillation for Fast Nonparametric Density Estimation
IEEE Transactions on Neural Networks and Learning Systems, 2023Nonparametric density estimation has been extensively used in various application scenarios and theoretical models. However, the modeling of these powerful methods is inseparable from the sample data and comes at the cost of repeated and intensive kernel calculations, which makes their efficiency greatly affected by the sample scale, data dimension ...
Bopeng Fang, Shifeng Chen, Zhurong Dong
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On parametric density estimation
Biometrika, 1989Let p(x,\(\vartheta)\) be the density of a random variable x. A random sample \(s_ n=(x_ 1,...,x_ n)\) of size n is available from the distribution. By y a future observation from this distribution is denoted. Two distinct methods of estimating p(y\(| \vartheta)\) are known. The estimative method uses \[ p(y| {\hat \vartheta}_ n)=p(y| \vartheta ={\hat \
El-Sayyad, G. M. +2 more
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Generalized Kernel Density Estimator
Theory of Probability & Its Applications, 2000Summary: We introduce a new class of nonparametric density estimators. It includes the classical kernel density estimators as well as the popular Abramson's estimator. We show that the generalized estimators may perform much better than the classical one if the distribution has a heavy tail.
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Model-Based Clustering, Classification, and Density Estimation Using mclust in R
, 2023Luca Scrucca +3 more
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