Results 81 to 90 of about 278 (169)

Nonparametric inference based on panel count data

, 2010
Bayesian estimation, Generalized least-squares, Mean function, Markov model, Nonparametric comparison, Nonparametric maximum likelihood, Nonparametric maximum pseudo-likelihood, Panel count data, Rate function, 62G05, 62G20, 62N02, 62N03,
N. Balakrishnan, Xingqiu Zhao, Jianguo Sun   +2 more
core   +1 more source

On optimal portfolio diversification with respect to extreme risks

Portfolio optimization, Risk management, Diversification effects, Multivariate extremes, 62G32, 62G05, 62G20, 62P05, C13, C14, G11,
Ludger Rüschendorf, Georg Mainik
core   +1 more source

The cost of not knowing the radius

, 2008
Symmetric location and contamination, Infinitesimal asymmetric neighborhoods, Total variation, contamination, Asymptotically linear estimators, Influence curves, Maximum asymptotic variance and mean square error, Relative risk, Inefficiency, Least ...
Peter Ruckdeschel, Ruckdeschel, Peter, Rieder, Helmut, Matthias Kohl, Kohl, Matthias, Helmut Rieder   +5 more
core   +1 more source

Neyman meets causal machine learning: Experimental evaluation of individualized treatment rules

Journal of Causal Inference
A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today’s ...
Li Michael Lingzhi, Imai Kosuke
doaj   +1 more source

An overview of nonparametric contributions to the problem of functional estimation from biased data

Biased sampling, density estimation, length-biased data, nonparametric inference, regression estimation, semiparametric models, weighted distributions, Primary:62G05, Secondary:62G06,62G07,62D05,
José Alcalá, José Cristóbal
core   +1 more source

Multivariate L-estimation

Approximate likelihood depth, asymptotic normality, equivariance, multivariate order statistics, Primary 62G05, secondary 62G20,
Luis García-Escudero, Simon Sheather, Andrew Wood, Alfonso Gordaliza, Joseph McKean, Ricardo Fraiman, Jean Meloche, Xuming He, Christopher Small, Víctor Yohai, Ricardo Maronna, R. Fraiman   +11 more
core   +1 more source

Strong laws for weighted sums of widely orthant dependent random variables and applications

Open Mathematics
In this study, the strong law of large numbers and the convergence rate for weighted sums of non-identically distributed widely orthant dependent random variables are established.
Zhu Yong, Wang Wei, Chen Kan
doaj   +1 more source

Optimal bandwidth estimators of kernel density functionals for contaminated data. [PDF]

J Appl Stat, 2021
Gündüz N, Aydın C.
europepmc   +1 more source

Can We Estimate the Density's Derivative with Suroptimal Rate?

Mathematics Subject Classficiations (1991): 62G05., Nonparametric estimation, suroptimal rate, parametric rate, Gaussian process.,
A. Lucas
core   +1 more source

Variable importance for causal forests: breaking down the heterogeneity of treatment effects

Journal of Causal Inference
Causal 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
doaj   +1 more source