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Causal Inference on Time Series using Structural Equation Models
Causal Inference Time Series Structural Equation Models
2012/9/19
Causal inference uses observations to infer the causal structure of the data generating system.We study a class of functional models that we call Time Series Models with Independent Noise (TiMINo). Th...
Modelling outliers and structural breaks in dynamic linear models with a novel use of a heavy tailed prior for the variances: An alternative to the Inverted Gamma
Modelling outliers structural breaks Inverted Gamma
2011/7/19
In this paper we propose a new wider class of hypergeometric heavy tailed priors that are given as the convolution of a Student-t density for the location parameter and a Scaled Beta2 prior for the va...
New multivariate central limit theorems in linear structural and functional error-in-variables models
explanatory variables domain of attraction of the normal law multivariate Student statistic positive definite matrix
2009/9/16
This paper deals simultaneously with linear structural and functional error-in-variables models (SEIVM and FEIVM), revisiting in this context generalized and modified least squares estimators of the s...
Central limit theorems in linear structural error-in-variables models with explanatory variables in the domain of attraction of the normal law
central limit theorem domain of attraction of the normal law large-sample approximate confidence interval self-normalization Studentization
2009/9/16
Linear structural error-in-variables models with univariate observations are revisited for studying modified least squares estimators of the slope and intercept. New marginal central limit theorems (C...
Causal inference in longitudinal studies with history-restricted marginal structural models
causal inference counterfactual marginal structural model longitudinal study IPTW G-computation Double Robust
2009/9/16
A new class of Marginal Structural Models (MSMs), History-Restricted MSMs (HRMSMs), was recently introduced for longitudinal data for the purpose of defining causal parameters which may often be bette...
Structural shrinkage of nonparametric spectral estimators for multivariate time series
structural shrinkage nonparametric spectral estimators multivariate time series
2009/9/16
In this paper we investigate the performance of periodogram based estimators of the spectral density matrix of possibly high-dimensional time series. We suggest and study shrinkage as a remedy against...