搜索结果: 1-15 共查到“统计学 semiparametric”相关记录33条 . 查询时间(0.056 秒)
Estimation in semiparametric models with missing data
Copulas imputation kernel smoothing missing at random nuisance function partially linear model
2016/1/25
We propose a novel varying coefficient model, called princi-pal varying coefficient model (PVCM), by characterizing the varying coeffi-cients through linear combinations of a few principal functions. ...
Nonparametric and Semiparametric Regressions Subject to Monotonicity Constraints: Estimation and Forecasting
Nonlinearity Nonparametric regression Semiparametric regression Local mono- tonicity Bagging
2016/1/20
This paper considers nonparametric and semiparametric regression models subject to monotonicity constraint. We use bagging as an alternative approach to Hall and Huang(2001). Asymptotic properties of ...
Profiled Forward Regression for Ultrahigh Dimensional Variable Screening in Semiparametric Partially Linear Models
Forward Regression Partially Linear Model Profiled Forward Regres- 9 sion Screening Consistency
2016/1/19
Profiled Forward Regression for Ultrahigh Dimensional Variable Screening in Semiparametric Partially Linear Models.
Bayesian semiparametric analysis for two-phase studies of gene-environment interaction
Biased sampling colorectal cancer Dirichlet prior exposure enriched sampling gene-environment independence jointeffects multivariate categorical distribution spike and slab prior
2013/6/14
The two-phase sampling design is a cost-efficient way of collecting expensive covariate information on a judiciously selected subsample. It is natural to apply such a strategy for collecting genetic d...
A Semiparametric Estimator for Long-Range Dependent Multivariate Processes
Multivariate processes Long-range dependence Semiparametric estimation VARFIMA processes Asymptotic theory
2013/6/14
In this paper we propose a generalization of a class of Gaussian Semiparametric Estimators (GSE) of the fractional differencing parameter for long-range dependent multivariate time series. We generali...
We review the Bayesian theory of semiparametric inference following Bickel and Kleijn (2012) and Kleijn and Knapik (2013). After an overview of efficiency in parametric and semiparametric estimation p...
A General Bernstein--von Mises Theorem in semiparametric models
A General Bernstein von Mises Theorem semiparametric models
2013/6/14
A Bernstein-von Mises theorem is derived for general semiparametric functionals. The result is applied to a variety of semiparametric problems, in i.i.d. and non-i.i.d. situations. In particular, new ...
Critical dimension in profile semiparametric estimation
maximum likelihood local quadratic bracketing spread local concentration
2013/4/28
This paper revisits the classical inference results for profile quasi maximum likelihood estimators (profile MLE) in the semiparametric estimation problem. We mainly focus on two prominent theorems: t...
Real-time semiparametric regression
Approximate Bayesian inference Generalized additive models Meaneld vari-ational Bayes Mixed models Online variational Bayes Penalized splines Wavelets
2012/11/22
We develop algorithms for performing semiparametric regression analysis in real time, with data processed as it is collected and made immediately available via modern telecommunications technologies. ...
New semiparametric stationarity tests based on adaptive multidimensional increment ratio statistics
Gaussian fractionally integrated processes Adaptive semiparametric estimators of the meme-ory parameter test of long-memory stationarity test unit root test.
2012/9/19
In this paper, we show that the adaptive multidimensional increment ratio estimator of the long range memory parameter defined in Bardet and Dola (2012) satisfies acentral limit theorem (CLT in the se...
Dynamic Large Spatial Covariance Matrix Estimation in Application to Semiparametric Model Construction via Variable Clustering: the SCE approach
Time Series Covariance Estimation Regularization, Sparsity
2011/7/6
To better understand the spatial structure of large panels of economic and financial time series and provide a guideline for constructing semiparametric models, this paper first considers estimating a...
Stochastic Search for Semiparametric Linear Regression Models
Stochastic Search Semiparametric Linear Regression Models
2011/7/6
This paper introduces and analyzes a stochastic search method for parameter estimation in linear regression models in the spirit of Beran and Millar (1987).
Semiparametric inference in mixture models with predictive recursion marginal likelihood
Density estimation Dirichlet process mixture empirical Bayes filtering algorithm
2011/7/5
Predictive recursion is an accurate and computationally efficient algorithm for nonparametric estimation of mixing densities in mixture models. In semiparametric mixture models, however, the algorithm...
A semiparametric estimation of copula models based on the method of moments
Moments Copulas Dependence Parametric estimation Archimedean copulas
2011/6/20
Using the classical estimation method of moments, we propose a new semiparametric estima-
tion procedure for multi-parameter copula models. Consistency and asymptotic normality of
the obtained estim...
Semiparametric Bivariate Zero-Inflated Poisson Models with Application to Studies of Abundance for Multiple Species
Benthic fish Bivariate Poisson Hierarchical Bayes Missouri River Pspline Zero-inflated Poisson
2011/6/17
Ecological studies involving counts of abundance, presence-absence or occupancy rates
often produce data having a substantial proportion of zeros. Furthermore, these types of
processes are typically...