Results 21 to 30 of about 534,560 (282)
Generalized Covariance Estimator
Journal of Business & Economic Statistics, 2022 We consider a class of semi-parametric dynamic models with independent identically distributed errors, including the nonlinear mixed causal-noncausal Vector Autoregressive (VAR), Double-Autoregressive (DAR) and stochastic volatility models. To estimate the parameters characterizing the (nonlinear) serial dependence, we introduce a generic Generalized ...
Gourieroux, Christian, Jasiak, Joann
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Intuitive covariation estimation [PDF]
Memory & Cognition, 1986 Six experiments concerned people's ability to estimate the degree and sign of covariation represented in a bivariate distribution of stimuli with which they had just been presented as a series of pairs of stimuli. The stimuli were pairs of numbers, pairs of lines of variable lengths, or word-line pairs.
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ETF Basket-Adjusted Covariance estimation
Journal of Econometrics, 2023 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boudt, Kris +3 more
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Shrinkage Estimation of the Power Spectrum Covariance Matrix [PDF]
, 2008 We seek to improve estimates of the power spectrum covariance matrix from a limited number of simulations by employing a novel statistical technique known as shrinkage estimation.
Adrian C. Pope +14 more
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Covariance-Aware Private Mean Estimation Without Private Covariance Estimation
, 2021 We present two sample-efficient differentially private mean estimators for $d$-dimensional (sub)Gaussian distributions with unknown covariance. Informally, given $n \gtrsim d/α^2$ samples from such a distribution with mean $μ$ and covariance $Σ$, our estimators output $\tildeμ$ such that $\| \tildeμ- μ\|_Σ \leq α$, where $\| \cdot \|_Σ$ is the ...
Brown, Gavin +4 more
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Knowledge-Aided Structured Covariance Matrix Estimator Applied for Radar Sensor Signal Detection
Sensors, 2019 This study deals with the problem of covariance matrix estimation for radar sensor signal detection applications with insufficient secondary data in non-Gaussian clutter. According to the Euclidean mean, the authors combined an available prior covariance
Naixin Kang, Zheran Shang, Qinglei Du
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Covariance Estimation: The GLM and Regularization Perspectives [PDF]
, 2011 Finding an unconstrained and statistically interpretable reparameterization of a covariance matrix is still an open problem in statistics. Its solution is of central importance in covariance estimation, particularly in the recent high-dimensional data ...
Pourahmadi, Mohsen
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Entropy, 2019 This paper discusses the effects of introducing nonlinear interactions and noise-filtering to the covariance matrix used in Markowitz’s portfolio allocation model, evaluating the technique’s performances for daily data from seven financial ...
Yaohao Peng +3 more
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When do improved covariance matrix estimators enhance portfolio optimization? An empirical comparative study of nine estimators [PDF]
, 2010 The use of improved covariance matrix estimators as an alternative to the sample estimator is considered an important approach for enhancing portfolio optimization.
Lillo, Fabrizio +3 more
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Variational Bayes for Regime-Switching Log-Normal Models
Entropy, 2014 The power of projection using divergence functions is a major theme in information geometry. One version of this is the variational Bayes (VB) method. This paper looks at VB in the context of other projection-based methods in information geometry.
Hui Zhao, Paul Marriott
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