Variance estimation for semiparametric regression models by local averaging
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DOI: 10.1007/s11749-017-0553-3
Abstract: Variance estimation is a fundamental problem in statistical modelling and plays an important role in the inferences after model selection and estimation. In this paper, we focus on several nonparametric and semiparametric models and propose… read more here.
Keywords: estimation; estimation semiparametric; local averaging; variance estimation ... See more keywords
Generating probabilistic predictions using mean-variance estimation and echo state network
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DOI: 10.1016/j.neucom.2016.09.064
Abstract: In conventional time series prediction techniques, uncertainty associated with predictions are usually ignored. Probabilistic predictors, on the other hand, can measure the uncertainty in predictions, to provide better supports for decision-making processes. A dynamic probabilistic… read more here.
Keywords: echo state; mean variance; variance estimation; variance ... See more keywords
Variance estimation based on blocked 3×2 cross-validation in high-dimensional linear regression
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DOI: 10.1080/02664763.2020.1780571
Abstract: In high-dimensional linear regression, the dimension of variables is always greater than the sample size. In this situation, the traditional variance estimation technique based on ordinary least squares constantly exhibits a high bias even under… read more here.
Keywords: cross validation; model; variance estimation; variance ... See more keywords
Variance estimation for sparse ultra-high dimensional varying coefficient models
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DOI: 10.1080/03610926.2018.1429627
Abstract: ABSTRACT This paper considers the problem of variance estimation for sparse ultra-high dimensional varying coefficient models. We first use B-spline to approximate the coefficient functions, and discuss the asymptotic behavior of a naive two-stage estimator… read more here.
Keywords: estimation sparse; ultra high; coefficient; sparse ultra ... See more keywords
Variance estimation for the average treatment effects on the treated and on the controls
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DOI: 10.1177/09622802221142532
Abstract: Common causal estimands include the average treatment effect, the average treatment effect of the treated, and the average treatment effect on the controls. Using augmented inverse probability weighting methods, parametric models are judiciously leveraged to… read more here.
Keywords: average treatment; treatment effect; treatment; variance estimation ... See more keywords
Synthesizing effects for multiple outcomes per study using robust variance estimation versus the three-level model
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DOI: 10.3758/s13428-018-1156-y
Abstract: Primary studies increasingly report information that can be used to provide multiple effect sizes. Of interest in this study, primary studies might compare a treatment and a control group on multiple related outcomes that result… read more here.
Keywords: robust variance; outcomes per; study; variance estimation ... See more keywords