Results 1 to 10 of about 50 (48)
Variance Function Estimation [PDF]
Journal of the American Statistical Association, 1987 We develops a general theory for variance function estimation in regression. Most methods in common use are included in our development. The general qualitative conclusions are these. First, most variance function estimation procedures can be looked upon as regressions with responses' being transformations of absolute residuals from a preliminary fit ...
Davidian, M., Carroll, R.J.
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Local Polynomial Variance-Function Estimation [PDF]
Technometrics, 1997 The conditional variance function in a heteroscedastic, nonparametric regression model is estimated by linear smoothing of squared residuals. Attention is focussed on local polynomial smoothers. Both the mean and variance functions are assumed to be smooth, but neither is assumed to be in a parametric family. The effect of preliminary estimation of the
D. Ruppert +3 more
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Warped functional analysis of variance [PDF]
Biometrics, 2014 SummaryThis article presents an Analysis of Variance model for functional data that explicitly incorporates phase variability through a time‐warping component, allowing for a unified approach to estimation and inference in presence of amplitude and time variability.
Gervini, Daniel, Carter, Patrick A.
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Kriging with Nonparametric Variance Function Estimation [PDF]
Biometrics, 1999 Summary. A method for fitting regression models to data that exhibit spatial correlation and heteroskedas‐ticity is proposed. It is well known that ignoring a nonconstant variance does not bias least‐squares estimates of regression parameters; thus, data analysts are easily lead to the false belief that moderate heteroskedas‐ticity can generally be ...
Opsomer, Jean +4 more
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MEAN–VARIANCE PORTFOLIO MANAGEMENT WITH FUNCTIONAL OPTIMIZATION [PDF]
International Journal of Theoretical and Applied Finance, 2020 This paper introduces a new functional optimization approach to portfolio optimization problems by treating the unknown weight vector as a function of past values instead of treating them as fixed unknown coefficients in the majority of studies. We first show that the optimal solution, in general, is not a constant function.
KA WAI TSANG, ZHAOYI HE
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The Annals of Statistics, 1989 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Bar-Lev, Shaul K., Bshouty, Daoud
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Variance function of boolean additive convolution [PDF]
Statistics & Probability Letters, 2020 We determine the formula for pseudo-variance function (or variance function V{\nu} in case of existence) under boolean additive convolution ...
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Optimal designs for variance function estimation using sample variances [PDF]
Journal of Statistical Planning and Inference, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Goos, P., Tack, L., Vandebroek, M.
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Variance Functions with Meromorphic Means
The Annals of Probability, 1991 A natural exponential family is characterized by a pair \((\Omega,V)\) where \(\Omega\), the mean domain, is an open interval in \(\mathbb{R}\) and \(V\) is the associated variance function, regarded as a function of the mean. The authors make a further contribution to the problem of characterizing the set of possible pairs \((\Omega,V)\), a question ...
Bar-Lev, Shaul K. +2 more
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Tauber Theory for Infinitely Divisible Variance Functions [PDF]
Bernoulli, 1997 The authors present a kind of Tauber theory for infinitely divisible natural exponential families. The main result states that the variance function of a family is regularly varying if and only if the spectral measure in the Lévy-Khinchin representation is regularly varying. A complete proof of this result is given elsewhere.
Bent Jørgensen +3 more
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