Results 21 to 30 of about 795 (93)

Sparse Conformal Predictors [PDF]

, 2009
Conformal predictors, introduced by Vovk et al. (2005), serve to build prediction intervals by exploiting a notion of conformity of the new data point with previously observed data.
Hebiri, Mohamed
core   +5 more sources

Statistical estimation in the proportional hazards model with risk set sampling [PDF]

, 2004
Thomas' partial likelihood estimator of regression parameters is widely used in the analysis of nested case-control data with Cox's model. This paper proposes a new estimator of the regression parameters, which is consistent and asymptotically normal ...
Chen, Kani
core   +2 more sources

Selection of tuning parameters in bridge regression models via Bayesian information criterion

, 2012
We consider the bridge linear regression modeling, which can produce a sparse or non-sparse model. A crucial point in the model building process is the selection of adjusted parameters including a regularization parameter and a tuning parameter in bridge
A Antoniadis, AE Hoerl, C Park, C-H Zhang, CM Hurvich, CM Hurvich, G McDonald, G Schwarz, H Zou, H Zou, J Fan, J Fan, J Huang, J Huang, J Lv, JE Frank, K Knight, L Tierney, M Ishiguro, M Yuan, N Sugiura, P Bühlmann, P Craven, PHC Eilers, R Tibshirani, S Konishi, Shuichi Kawano, T Shimamura, WJ Fu, Y Liu   +29 more
core   +1 more source

Energy yield database management system based on solar photovoltaic cell using internet of things technology

e-Prime: Advances in Electrical Engineering, Electronics and Energy
This study investigates the performance of solar cell electric power generation, focusing on data collected from Prince of Songkla University, Surat Thani Campus, analyzing the Mean Squared Error (MSE) for each phase consisting of Phase A: 0.00133, Phase
Nathaphon Boonnam, Orachon Lanteng
doaj   +1 more source

A matrix approach to compare BLUEs under a linear regression model and its two competing restricted models with applications

Demonstratio Mathematica
Suppose that a weakly singular linear regression model M{\mathscr{M}} and its two competing restricted models M1{{\mathscr{M}}}_{1} and M2{{\mathscr{M}}}_{2} are given.
Ren Xingwei
doaj   +1 more source

Orthogonalized smoothing for rescaled spike and slab models

, 2008
Rescaled spike and slab models are a new Bayesian variable selection method for linear regression models. In high dimensional orthogonal settings such models have been shown to possess optimal model selection properties.
Ishwaran, Hemant, Papana, Ariadni
core   +1 more source

Some theoretical foundations for the design and analysis of randomized experiments

Journal of Causal Inference
Neyman’s seminal work in 1923 has been a milestone in statistics over the century, which has motivated many fundamental statistical concepts and methodology.
Shi Lei, Li Xinran
doaj   +1 more source

On the history and use of some standard statistical models

, 2008
This paper tries to tell the story of the general linear model, which saw the light of day 200 years ago, and the assumptions underlying it. We distinguish three principal stages (ignoring earlier more isolated instances). The model was first proposed in
Lehmann, E. L.
core   +1 more source

Almost sure convergence for weighted sums of pairwise PQD random variables

, 2018
We obtain Marcinkiewicz-Zygmund strong laws of large numbers for weighted sums of pairwise positively quadrant dependent random variables stochastically dominated by a random variable $X \in \mathscr{L}_{p}$, $1 \leqslant p < 2$.
da Silva, João Lita
core   +1 more source

Regression(s) discontinuity: Using bootstrap aggregation to yield estimates of RD treatment effects

Journal of Causal Inference
Following Efron (2014), we propose an algorithm for estimating treatment effects for use by researchers employing a regression-discontinuity (RD) design.
Long Mark C., Rooklyn Jordan
doaj   +1 more source