Results 11 to 20 of about 1,761 (95)
Application of one-step method to parameter estimation in ODE models. [PDF]
Stat Neerl, 2018 In this paper, we study application of Le Cam's one‐step method to parameter estimation in ordinary differential equation models. This computationally simple technique can serve as an alternative to numerical evaluation of the popular non‐linear least squares estimator, which typically requires the use of a multistep iterative algorithm and repetitive ...
Dattner I, Gugushvili S.
europepmc +2 more sources
Large deviations for exchangeable observations with applications
International Journal of Mathematics and Mathematical Sciences, Volume 2004, Issue 55, Page 2947-2958, 2004., 2004 We first prove some large deviation results for a mixture of i.i.d. random variables. Compared with most of the known results in the literature, our results are built on relaxing some restrictive conditions that may not be easy to be checked in certain typical cases.
Jinwen Chen
wiley +1 more source
Dependence Modeling, 2013 We study the impact of certain transformations within the class of Archimedean copulas. We give some admissibility conditions for these transformations, and define some equivalence classes for both transformations and generators of Archimedean copulas ...
Di Bernardino Elena, Rullière Didier
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A survey of limit laws for bootstrapped sums
International Journal of Mathematics and Mathematical Sciences, Volume 2003, Issue 45, Page 2835-2861, 2003., 2003 Concentrating mainly on independent and identically distributed (i.i.d.) real‐valued parent sequences, we give an overview of first‐order limit theorems available for bootstrapped sample sums for Efron′s bootstrap. As a light unifying theme, we expose by elementary means the relationship between corresponding conditional and unconditional bootstrap ...
Sándor Csörgő, Andrew Rosalsky
wiley +1 more source
Smooth backfitting in additive inverse regression [PDF]
, 2013 We consider the problem of estimating an additive regression function in an inverse regres- sion model with a convolution type operator. A smooth backfitting procedure is developed and asymptotic normality of the resulting estimator is established ...
Bissantz, Nicolai +2 more
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On the eigenvalues of the spatial sign covariance matrix in more than two dimensions [PDF]
, 2016 Acknowledgments Alexander Dürre was supported in part by the Collaborative Research Grant 823 of the German Research Foundation. David E. Tyler was supported in part by the National Science Foundation grant DMS-1407751. A visit of Daniel Vogel to David E.
Dürre, Alexander +2 more
core +2 more sources
Empirical likelihood for quantile regression models with response data missing at random
Open Mathematics, 2017 This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random.
Luo S., Pang Shuxia
doaj +1 more source
Quadratic functional estimation in inverse problems [PDF]
, 2009 We consider in this paper a Gaussian sequence model of observations $Y_i$, $i\geq 1$ having mean (or signal) $\theta_i$ and variance $\sigma_i$ which is growing polynomially like $i^\gamma$, $\gamma >0$.
Butucea, Cristina, Méziani, Katia
core +5 more sources
Nonparametric Bayesian inference for multidimensional compound Poisson processes [PDF]
, 2015 Given a sample from a discretely observed multidimensional compound Poisson process, we study the problem of nonparametric estimation of its jump size density $r_0$ and intensity $\lambda_0$.
Gugushvili, Shota +2 more
core +3 more sources
Variable importance for causal forests: breaking down the heterogeneity of treatment effects
Journal of Causal InferenceCausal random forests provide efficient estimates of heterogeneous treatment effects. However, forest algorithms are also well-known for their black-box nature, and therefore, do not characterize how input variables are involved in treatment effect ...
Bénard Clément, Josse Julie
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