搜索结果: 1-15 共查到“理论统计学 density”相关记录49条 . 查询时间(0.096 秒)
Maximum-Likelihood Estimation For Diffusion Processes Via Closed-Form Density Expansions
asymptotic expansion diffusion discrete observation maximum-likelihood estimation transition density
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2016/1/25
This paper proposes a widely applicable method of approximate maximum-likelihood estimation for multivariate diffusion process from discretely sampled data. A closed-form asymptotic expansion for tran...
Limit theorems for kernel density estimators under dependent samples
Kernel density estimator consistency convergence rate mixing rate
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2013/6/14
In this paper, we construct a moment inequality for mixing dependent random variables, it is of independent interest. As applications, the consistency of the kernel density estimation is investigated....
Efficient Density Estimation via Piecewise Polynomial Approximation
Efficient Density Estimation Piecewise Polynomial Approximation
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2013/6/14
We give a highly efficient "semi-agnostic" algorithm for learning univariate probability distributions that are well approximated by piecewise polynomial density functions. Let $p$ be an arbitrary dis...
Probit transformation for kernel density estimation on the unit interval
transformation kernel density estimator boundary bias local likelihood density estimation local log-polynomial density estimation
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2013/4/27
Kernel estimation of a probability density function supported on the unit interval has proved difficult, because of the well known boundary bias issues a conventional kernel density estimator would ne...
Robust Kernel Density Estimation
outlier reproducing kernel feature space kernel trick
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2011/7/19
We propose a method for nonparametric density estimation that exhibits robustness to contamination of the training sample. This method achieves robustness by combining a traditional kernel density est...
Density Estimation and Classification via Bayesian Nonparametric Learning of Affine Subspaces
Dimension reduction Classi er Variable selection Nonparametric Bayes
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2011/6/20
It is now practically the norm for data to be very high dimensional in areas such as genetics, machine
vision, image analysis and many others. When analyzing such data, parametric models are often to...
Concentration Inequalities and Confidence Bands for Needlet Density Estimators on Compact Homogeneous Manifolds
Concentration Inequalities Confidence Bands Density Estimators
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2011/3/21
Let $X_1,...,X_n$ be a random sample from some unknown probability density $f$ defined on a compact homogeneous manifold $\mathbf M$ of dimension $d \ge 1$. Consider a 'needlet frame' $\{\phi_{j \eta}...
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors
Adaptive nonparametric estimation Deconvolution Fluorescence lifetimes
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2010/11/8
Motivated by fluorescence lifetime measurements this paper considers the problem of nonparametric density estimation in the pile-up model. Adaptive nonparametric estimators are proposed for the pile-u...
Asymptotics and optimal bandwidth selection for highest density region estimation
Density contour density level set kernel density estimator
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2010/10/14
We study kernel estimation of highest-density regions (HDR). Our main contributions are two-fold. First, we derive a uniform-in-bandwidth asymptotic approximation to a risk that is appropriate for HD...
Nonparametric kernel estimation of the probability density function of regression errors using estimated residuals
Kernel density estimation Leave-one-out kernel estimator Two-steps estimator
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2010/10/14
This paper deals with the nonparametric density estimation of the regression error term assuming its independence with the covariate. The difference between the feasible estimator which uses the estim...
Approaches for Multi-step Density Forecasts with Application to Aggregated Wind Power
Non-Gaussian time series logistic transformation exponentialsmoothing truncated normal distribution ARIMA-GARCH model
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2010/3/11
The generation of multi-step density forecasts for non-Gaussian
data mostly relies on Monte-Carlo simulations which are computa-
tionally intensive. Using aggregated wind power in Ireland, we study
...
Defining probability density for a distribution of random functions
Density estimation dimension eigenfunction eigenvalue functionaldata analysis kernel methods log-density estimation nonparametric statistics
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2010/3/11
The notion of probability density for a random function is not
as straightforward as in finite-dimensional cases. While a probability
density function generally does not exist for functional data, w...
Confidence bands in density estimation
Adaptive estimation limit theorem density estimation extremes Gaussian processes wavelet estimators kernel estimators
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2010/3/11
we construct adaptive confidence bands that are honest for all densities
in a “generic” subset of the union of t-H¨older balls, 0 < t r,
where r is a fixed but arbitrary integer. The exceptional (...
Nonparametric estimation of the mixing density using polynomials
Nonparametric estimation mixing density polynomials
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2010/3/10
We consider the problem of estimating the mixing density f from n i.i.d. observations distributed according to amixture density with unknown mixing distribution. In contrast with finite mixtures model...
Statistical tests for whether a given set of independent,identically distributed draws does not come from a specified probability density
Kolmogorov-Smirnov nonparametric goodness-of-fit outlier distributionfunction nonincreasing rearrangement
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2010/3/9
We discuss several tests for whether a given set of independent and identically
distributed (i.i.d.) draws does not come from a specified probability density function.
The most commonly used are Kol...