:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Moriyama, Taku, Maesono, Yoshihiko
Format:	Preprint
Published:	2016
Subjects:	Statistics Theory
Online Access:	https://arxiv.org/abs/1611.08049
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Smoothed nonparametric two-sample tests
by: Moriyama, Taku, et al.
Published: (2017)

Smoothed nonparametric tests and their properties
by: Maesono, Yoshihiko, et al.
Published: (2016)

A new method of joint nonparametric estimation of probability density and its support
by: Moriyama, Taku
Published: (2017)

On large bandwidth matrix values kernel smoothed estimators for multi-index models
by: Moriyama, Taku
Published: (2026)

A semiparametric probability distribution estimator of sample maximums
by: Moriyama, Taku
Published: (2022)

Parametric and nonparametric probability distribution estimators of sample maximum
by: Moriyama, Taku
Published: (2021)

On tail inference in iid settings with nonnegative extreme value index
by: Moriyama, Taku
Published: (2024)

Nonparametric hazard rate estimation with associated kernels and minimax bandwidth choice
by: Breuil, Luce, et al.
Published: (2025)

The out-of-sample prediction error of the square-root-LASSO and related estimators
by: Olea, José Luis Montiel, et al.
Published: (2022)

Asymmetric conformal prediction with penalized kernel sum-of-squares
by: Allain, Louis, et al.
Published: (2026)

Proportional asymptotics of piecewise exponential proportional hazards models
by: Massa, Emanuele
Published: (2025)

Control variates for variance-reduced ratio of means estimators
by: Bocquet-Nouaille, Louison, et al.
Published: (2025)

Scalable and adaptive prediction bands with kernel sum-of-squares
by: Allain, Louis, et al.
Published: (2025)

A non-asymptotic theory of Kernel Ridge Regression: deterministic equivalents, test error, and GCV estimator
by: Misiakiewicz, Theodor, et al.
Published: (2024)

Plug-in error bounds for a mixing density estimate in $R^d,$ and for its derivatives
by: Yatracos, Yannis G.
Published: (2015)

A note on kernel density estimators with optimal bandwidths
by: Hjort, Nils Lid, et al.
Published: (2026)

Estimation of the complier causal hazard ratio under dependent censoring
by: Crommen, Gilles, et al.
Published: (2025)

Manifolds with kinks and the asymptotic behavior of the graph Laplacian operator with Gaussian kernel
by: Pal, Susovan, et al.
Published: (2025)

Second order asymptotics for the number of times an estimator is more than epsilon from its target value
by: Hjort, Nils Lid, et al.
Published: (2026)

Subscedastic weighted least squares estimates
by: Bryan, Jordan, et al.
Published: (2024)

Non-asymptotic two-sample kernel testing with the spectrally truncated normalized MMD
by: Lacroix, Perrine, et al.
Published: (2026)

Measure transport with kernel mean embeddings
by: Wang, L., et al.
Published: (2024)

On the errors committed by sequences of estimator functionals
by: Grønneberg, Steffen, et al.
Published: (2026)

Adaptive tail index estimation: minimal assumptions and non-asymptotic guarantees
by: Lederer, Johannes, et al.
Published: (2025)

A non-asymptotic upper bound in prediction for the PLS estimator
by: Castelli, Luca, et al.
Published: (2024)

Application of nonparametric approach to extreme value inference in distribution estimation of sample maximum and its properties
by: T. Moriyama
Published: (2025)

On the number of modes of Gaussian kernel density estimators
by: Geshkovski, Borjan, et al.
Published: (2024)

Signal-to-noise ratio aware minimaxity and higher-order asymptotics
by: Guo, Yilin, et al.
Published: (2022)

With random regressors, least squares inference is robust to correlated errors with unknown correlation structure
by: Zhang, Zifeng, et al.
Published: (2024)

Consistency of the bootstrap for asymptotically linear estimators based on machine learning
by: Tang, Zhou, et al.
Published: (2024)

On the pointwise and sup-norm errors for local regression estimators
by: Bettinger, Jérémy, et al.
Published: (2025)

On Conditional least squares estimation for the AD(1,n) model
by: Alaya, Mohamed Ben, et al.
Published: (2024)

Nonparametric estimation of sliced inverse regression by the $ k$-nearest neighbors kernel method
by: Mintogo, Luran Bengono, et al.
Published: (2025)

Local convergence rates of the nonparametric least squares estimator with applications to transfer learning
by: Schmidt-Hieber, Johannes, et al.
Published: (2022)

Asymptotics for power posterior mean estimation
by: Ray, Ruchira, et al.
Published: (2023)

Uniform mean estimation for monotonic processes
by: Clerico, Eugenio, et al.
Published: (2025)

Improved dependence on coherence in eigenvector and eigenvalue estimation error bounds
by: Yan, Hao, et al.
Published: (2025)

Nelson-Aalen kernel estimator to the tail index of right censored Pareto-type data
by: Guesmia, Nour Elhouda, et al.
Published: (2025)

Maximum likelihood estimation of mean functions for Gaussian processes under small noise asymptotics
by: Kobayashi, Mitsuki, et al.
Published: (2025)

Consistent least squares estimation in population-size-dependent branching processes
by: Braunsteins, Peter, et al.
Published: (2022)