搜索结果: 46-60 共查到“统计学 Adaptive”相关记录93条 . 查询时间(0.166 秒)
Pointwise Adaptive M-estimation in Nonparametric Regression
adaptation Huber function Lepski's method M-estimation minimax estimation nonparametric regression robust estimation pointwise estimation
2011/6/17
This paper deals with the nonparametric estimation in heteroscedastic
regression Yi = f(Xi) + i; i = 1; : : : ; n, with incomplete information,
i.e. each real random variable i has a density gi wh...
Are adaptive allocation designs beneficial for improving power in binary response trials?
Neyman allocation adaptive design asymptotic power Normal approximation Pitman effi ciency Bahadur effi ciency large deviations
2011/3/24
We consider the classical problem of selecting the best of two treatments in clinical trials with binary response. The target is to find the design that maximizes the power of the relevant test. Many ...
Adaptive Thresholding for Sparse Covariance Matrix Estimation
constrained ℓ 1 minimization covariance matrix Frobenius norm Gaus-sian graphical model rate of convergence precision matrix spectral norm
2011/3/21
In this paper we consider estimation of sparse covariance matrices and propose a thresholding procedure which is adaptive to the variability of individual entries. The estimators are fully data driven...
Adaptive Parallel Tempering for Stochastic Maximum Likelihood Learning of RBMs
Machine Learning (stat.ML) Neural and Evolutionary Computing (cs.NE)
2010/12/17
Restricted Boltzmann Machines (RBM) have attracted a lot of attention of late, as one the principle building blocks of deep networks. Training RBMs remains problematic however, because of the intracti...
Adaptive semiparametric wavelet estimator and goodness-of-fit test for long memory linear processes
Statistics Theory (math.ST)
2010/12/17
This paper is first devoted to study an adaptive wavelet based estimator of the long memory parameter for linear processes in a general semi-parametric frame. This is an extension of Bardet {\it et al...
Adaptive Density Estimation in the Pile-up Model Involving Measurement Errors
Adaptive nonparametric estimation Deconvolution Fluorescence lifetimes
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...
Adaptive estimation of covariance matrices via Cholesky decomposition
Covariance matrix banding Cholesky decomposition
2010/10/19
This paper studies the estimation of a large covariance matrix. We introduce a novel procedure called ChoSelect based on the Cholesky factor of the inverse covariance. This method uses a dimension red...
A multivariate adaptive stochastic search method for dimensionality reduction in classification
Dimensionality reduction classification variable selection
2010/10/19
High-dimensional classification has become an increasingly important problem. In this paper we propose a "Multivariate Adaptive Stochastic Search" (MASS) approach which first reduces the dimension of...
Adaptive estimator of the memory parameter and goodness-of-fit test using a multidimensional increment ratio statistic
Long-memory Gaussian processes goodness-of-fit test estimation of the memory parameter
2010/10/14
The Increment Ratio (IR) statistic was first defined and studied in Surgailis {\it et al.} (2008) for estimating the long-memory parameter either of a stationary or an increment stationary Gaussian p...
Quantile estimation with adaptive importance sampling
Quantile estimation law of iterated logarithm adaptive im-portance sampling stochastic approximation Robbins–Monro
2010/3/11
We introduce new quantile estimators with adaptive importance
sampling. The adaptive estimators are based on weighted samples
that are neither independent nor identically distributed. Using a
new l...
Our article is concerned with adaptive sampling schemes for Bayesian inference that
update the proposal densities using previous iterates. We introduce a copula based
proposal density which is made ...
Prediction and variable selection with the adaptive Lasso
adaptive Lasso prediction restricted eigenvalue thresholding variable selection
2010/3/9
We revisit the adaptive Lasso in a high-dimensional linear model,
and provide bounds for its prediction error and for its number of false positive
selections. We compare the adaptive Lasso with an “...
Adaptive asymptotically efficient estimation in heteroscedastic nonparametric regression
asymptotic bounds adaptive estimation efficient estimation het-eroscedastic regression nonparametric regression Pinsker’s constant
2010/3/10
The paper deals with asymptotic properties of the adaptive proce-
dure proposed in the author paper, 2007, for estimating an unknown
nonparametric regression. We prove that this procedure is asympto...
Adaptive LASSO-type estimation for ergodic diffusion processes
discretely observed diffusion processes model selection oracle proper-ties random fields stochastic differential equations
2010/3/10
The LASSO is a widely used statistical methodology for simultaneous estimation
and variable selection. In the last years, many authors analyzed this technique from
a theoretical and applied point of...
Adaptive estimation for Hawkes processes：application to genome analysis
Hawkes’ process model selection oracle inequalities data-driven penalty minimaxrisk adaptive estimation
2010/3/18
The aim of this paper is to provide a new method for the detection
of either favored or avoided distances between genomic events
along DNA sequences. These events are modeled by a Hawkes’ process.
...