Results 131 to 140 of about 1,708 (192)

Some asymptotic properties of kernel regression estimators of the mode for stationary and ergodic continuous time processes. [PDF]

Rev Mat Complut, 2021
Bouzebda S, Didi S.
europepmc   +1 more source

Efficient Testing Using Surrogate Information. [PDF]

Biom J
Knowlton R, Parast L.
europepmc   +1 more source

On the Reweigted Nadaraya-Watson Estimator of the Conditional Density Function

, 2015
The conditional probability density function plays an important role in statistics. It describes the relationship between two random variables, the dependent variable Y and the independent variable X. In this thesis, we studied the kernel estimation of the conditional density function when it is unknown.
openaire  

Data fusion using weakly aligned sources. [PDF]

J Am Stat Assoc
Li S, Gilbert PB, Duan R, Luedtke A.
europepmc   +1 more source

Relaxed Doubly Robust Estimation in Causal Inference. [PDF]

Stat Theory Relat Fields
Xu T, Zhao J.
europepmc   +1 more source

Dynamic Supervised Principal Component Analysis for Classification. [PDF]

J Comput Graph Stat
Ouyang W, Wu R, Hao N, Zhang HH.
europepmc   +1 more source

Semiparametric analysis of competing risks data with missing causes of failure and covariate measurement error. [PDF]

J Appl Stat
Jayanagasri A, Anjana S.
europepmc   +1 more source

Absolute risk from double nested case-control designs: cause-specific proportional hazards models with and without augmented estimating equations. [PDF]

Biometrics
Lee M, Gail MH.
europepmc   +1 more source

Smoothed L-estimation of Regression Function

The Nadaraya-Watson nonparametric estimator of regression is known to be highly sensitive to the presence of outliers in data.This sensitivity can be reduced, for example, by using local L-estimates of regression.Whereas the local L-estimation is ...
Cizek, P., Tamine, J., Härdle, W.K.
core  

Marginalized LASSO in the low-dimensional difference-based partially linear model for variable selection. [PDF]

J Appl Stat
Norouzirad M, Moura R, Arashi M, Marques FJ.   +3 more
europepmc   +1 more source