Results 71 to 80 of about 123 (106)

Linear Wavelet-Based Estimators of Partial Derivatives of Multivariate Density Function for Stationary and Ergodic Continuous Time Processes. [PDF]

Entropy (Basel)
Didi S, Bouzebda S.
europepmc   +1 more source

APPROXIMATION AND ESTIMATION OF s-CONCAVE DENSITIES VIA RÉNYI DIVERGENCES. [PDF]

Ann Stat, 2016
Han Q, Wellner JA.
europepmc   +1 more source

Inverse-Probability-Weighted Wavelet Estimation of Regression Derivatives Under Missing-at-Random Responses for Stationary Ergodic Processes. [PDF]

Entropy (Basel)
Bouzebda S, Didi S.
europepmc   +1 more source

On convex least squares estimation when the truth is linear. [PDF]

Electron J Stat, 2016
Chen Y, Wellner JA.
europepmc   +1 more source

Constrained Smoothing Splines Revisited

, 1997
In some regression settings one would like to combine the flexibility of nonparametric smoothing with some prior knowledge about the regression curve. Such prior knowledge may come from a physical or economic theory, leading to shape constraints such as ...
Berwin A. Turlach
core  

Minimax Estimation via Wavelets for Indirect Long-Memory Data

, 1997
In this paper we model linear inverse problems with long-range dependence by a fractional Gaussian noise model and study function estimation based on observations from the model. By using two wavelet-vaguelette decompositions, one for the inverse problem
Yazhen Wang
core  

Locus-specific contig assembly in highly-duplicated genomes, using the BAC-RF method. [PDF]

Nucleic Acids Res, 2000
Lin YR, Draye X, Qian X, Ren S, Zhu LH, Tomkins J, Wing RA, Li Z, Paterson AH.   +8 more
europepmc   +1 more source

Strong convergence in nonparametric regression with truncated dependent data

In this paper we derive rates of uniform strong convergence for the kernel estimator of the regression function in a left-truncation model. It is assumed that the lifetime observations with multivariate covariates form a stationary [alpha]-mixing ...
Liang, Han-Ying, Qi, Yongcheng, Li, Deli
core  

Wavelet Regression For Random Uniform Design

, 1997
The current research on wavelet regression has been mostly focused on equispaced samples. In general nonequispaced samples require different treatment.
Lawrence D. Brown, T. Tony Cai
core  

D-optimal designs for two-variable logistic regression model with restricted design space. [PDF]

Commun Stat Theory Methods
Zhai Y, Wang C, Lin HY, Fang Z.
europepmc   +1 more source