搜索结果: 1-12 共查到“经济统计学 regression”相关记录12条 . 查询时间(0.169 秒)
High Dimensional Stochastic Regression with Latent Factors, Endogeneity and Nonlinearity
α-mixing dimension reduction instrument variables nonstationarity time series
2016/1/26
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors, a linear com-bination of some ...
Estimation of fixed effects panel regression models with separable and nonseparable space-time filters
Panel data Spatial cointegration Explosive roots Fixed e¤ects
2016/1/25
This paper considers a quasi-maximum likelihood estimation for a linear panel data model with time and individual …xed e¤ects, where the disturbances have dynamic and spatial correlations which might ...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data Multivariate Analysis
2016/1/20
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Estimation of fixed effects panel regression models with separable and nonseparable space-time filters
Spatial autoregression Panel data Spatial cointegration Explosive roots Fixed e¤ects
2016/1/20
This paper considers a quasi-maximum likelihood estimation for a linear panel data model with time and individual …xed e¤ects, where the disturbances have dynamic and spatial correlations which might ...
Boosted Varying-Coefficient Regression Models for Product Demand Prediction
Boosting gradient descent tree-based regression varying-coefficient model
2015/8/21
Estimating the aggregated market demand for a product in a dynamic market is critical to manufacturers and retailers. Motivated by the need for a statistical demand prediction model for laptop pricing...
Consistency of Multidimensional Convex Regression
nonparametric regression multidimensional convex functions asymptotic properties consistency
2015/7/6
Convex regression is concerned with computing the best fit of a convex function to a data set of n observations in which the independent variable is (possibly) multidimensional. Such regression ...
Efficient Gaussian Process Regression for Large Data Sets
Bayesian Compressive Sensing Dimension Reduction
2011/7/6
Gaussian processes (GPs) are widely used in nonparametric regression, classification and spatio-temporal modeling, motivated in part by a rich literature on theoretical properties.
Rates of convergence for nearest neighbor estimators with the smoother regression function
Regression Nonparametric estimation Nearest neighbor Rate of conver-gence
2011/3/25
In regression analysis one wants to estimate the regression function from a data. In this paper we consider the rate of convergence for the nearest neighbor estimator in case that the regression funct...
Some results on random design regression with long memory errors and predictors
memory errors predictors random design
2011/3/24
This paper studies nonparametric regression with long memory (LRD) errors and predictors. First, we formulate general conditions which guarantee the standard rate of convergence for a nonparametric ke...
A dynamic hybrid model based on wavelets and fuzzy regression for time series estimation
Financial time series Wavelet decomposition Fuzzy regression SP500 index
2011/3/25
In the present paper, a fuzzy logic based method is combined with wavelet decomposition to develop a step-by-step dynamic hybrid model for the estimation of financial time series. Empirical tests on ...
Tight conditions for consistent variable selection in high dimensional nonparametric regression
variable selection high dimensional nonparametric regression
2011/3/22
We address the issue of variable selection in the regression model with very high ambient dimension, i.e., when the number of covariates is very large. The main focus is on the situation where the nu...
Nonparametric regression with filtered data
censoring counting process theory hazard functions kernel estimation local linear estimation truncation
2011/3/21
We present a general principle for estimating a regression function nonparametrically, allowing for a wide variety of data filtering, for example, repeated left truncation and right censoring. Both th...