Results 31 to 40 of about 3,251,267 (306)
Sparse Semi-Functional Partial Linear Single-Index Regression
Proceedings, 2018 The variable selection problem is studied in the sparse semi-functional partial linear model, with single-index type influence of the functional covariate in the response. The penalized least squares procedure is employed for this task.
Silvia Novo +2 more
doaj +1 more source
Current status linear regression
, 2017 We construct $\sqrt{n}$-consistent and asymptotically normal estimates for the finite dimensional regression parameter in the current status linear regression model, which do not require any smoothing device and are based on maximum likelihood estimates (
Groeneboom, Piet, Hendrickx, Kim
core +1 more source
Scaled Sparse Linear Regression
, 2012 Scaled sparse linear regression jointly estimates the regression coefficients and noise level in a linear model. It chooses an equilibrium with a sparse regression method by iteratively estimating the noise level via the mean residual square and scaling ...
Sun, Tingni, Zhang, Cun-Hui
core +1 more source
Using Simulation In Teaching Simple Linear Regression [PDF]
مجلة جامعة الانبار للعلوم الصرفة, 2012 This paper aims to use simulation in teaching simple linear regression, computer stimulation can be used to teach complicated statistical concepts in linear regression more quickly and effectively than traditional lecture alone.
ALBRIA A., ISAM K. ALANI, AHMED H. ALANI
doaj +1 more source
Population Ecology, EarlyView.Population size and dynamics fundamentally shape speciation by influencing genetic drift, founder events, and adaptive potential. Small populations may speciate rapidly due to stronger drift, whereas large populations harbor more genetic diversity, which can alter divergence trajectories. We highlight theoretical models that incorporate population size
Ryo Yamaguchi +3 more
wiley +1 more source
Truthful Linear Regression [PDF]
, 2015 We consider the problem of fitting a linear model to data held by individuals who are concerned about their privacy. Incentivizing most players to truthfully report their data to the analyst constrains our design to mechanisms that provide a privacy ...
Cummings, Rachel +2 more
core +3 more sources
Functional linear regression that's interpretable
, 2009 Regression models to relate a scalar $Y$ to a functional predictor $X(t)$ are becoming increasingly common. Work in this area has concentrated on estimating a coefficient function, $\beta(t)$, with $Y$ related to $X(t)$ through $\int\beta(t)X(t) dt ...
James, Gareth M., Wang, Jing, Zhu, Ji
core +2 more sources
FEBS Letters, EarlyView.Single‐cell RNA sequencing reveals an opposite role of SLPI in basal tumors based on metastatic spread, along with shared activation of specific regulons in cancer cells and mature luminal lactocytes, as well as downregulation of MALAT1 and NEAT1 in the latter.
Pietro Ancona +4 more
wiley +1 more source
Fuzzy Linear Regression of Rainfall-Altitude Relationship
Proceedings, 2018 Classical linear regression has been used to measure the relationship between rainfall data and altitude in different meteorological stations, in order to evaluate a linear relation.
Christos Tzimopoulos +3 more
doaj +1 more source
Regression with Linear Factored Functions
, 2015 Many applications that use empirically estimated functions face a curse of dimensionality, because the integrals over most function classes must be approximated by sampling.
CM Bishop +12 more
core +1 more source