On the problems of using linear models in ecological manipulation experiments: lessons learned from a climate experiment
Sign Up to like & getrecommendations! Published in 2018 at "Ecosphere"
DOI: 10.1002/ecs2.2322
Abstract: Manipulation experiments are often used to investigate ecological and environmental causal relationships and to understand and forecast impacts of anthropogenic pressures on ecosystem functioning. Such manipulation experiments often use factorial designs, and the data are… read more here.
Keywords: temperature; manipulation experiments; climate experiment; soil ... See more keywords
Testing for parametric component of partially linear models with missing covariates
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DOI: 10.1007/s00362-016-0848-6
Abstract: This paper considers the testing problem of partially linear models with missing covariates. The inverse probability weighted restricted estimator for the parametric component under linear constraint is derived and proven to share asymptotically normal distribution.… read more here.
Keywords: parametric component; partially linear; linear models; missing covariates ... See more keywords
A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates
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DOI: 10.1007/s00362-018-1013-1
Abstract: In this paper, a new robust and efficient estimation approach based on local modal regression is proposed for partially linear models with large-dimensional covariates. We show that the resulting estimators for both parametric and nonparametric… read more here.
Keywords: large dimensional; efficient estimation; robust efficient; models large ... See more keywords
The stochastic restricted ridge estimator in generalized linear models
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DOI: 10.1007/s00362-019-01142-7
Abstract: Many researchers have studied restricted estimation in the context of exact and stochastic restrictions in linear regression. Some ideas in linear regression, where the ridge and restricted estimations are the well known, were carried to… read more here.
Keywords: regression; stochastic restrictions; estimator; generalized linear ... See more keywords
Robust and efficient estimating equations for longitudinal data partial linear models and its applications
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DOI: 10.1007/s00362-020-01181-5
Abstract: Composite quantile regression (CQR) is a good alternative of the mean regression, because of its robustness and efficiency. In longitudinal data analysis, correlation structure plays an important role in improving efficiency. However, how to specify… read more here.
Keywords: longitudinal data; partial linear; robust efficient; estimating equations ... See more keywords
Two-dimensional linear models of multilayered anisotropic plates
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DOI: 10.1007/s00707-019-02405-y
Abstract: A two-dimensional model describing the multilayered anisotropic plate deformations is proposed. The plate is assumed to consist of some orthotropic layers with arbitrary orientation of axes relative to the plate frame. The studied multilayered plate… read more here.
Keywords: models multilayered; linear models; plate; dimensional linear ... See more keywords
Asymptotic Property of M Estimator in Classical Linear Models Under Dependent Random Errors
Sign Up to like & getrecommendations! Published in 2018 at "Methodology and Computing in Applied Probability"
DOI: 10.1007/s11009-017-9589-9
Abstract: In this paper, we first establish a useful result on strong convergence for weighted sums of widely orthant dependent (WOD, in short) random variables. Based on the strong convergence that we established and the Bernstein… read more here.
Keywords: random errors; random variables; asymptotic property; dependent random ... See more keywords
Ligand Binding Dynamics for Pre-dimerised G Protein-Coupled Receptor Homodimers: Linear Models and Analytical Solutions
Sign Up to like & getrecommendations! Published in 2018 at "Bulletin of Mathematical Biology"
DOI: 10.1007/s11538-017-0387-x
Abstract: Evidence suggests that many G protein-coupled receptors (GPCRs) are bound together forming dimers. The implications of dimerisation for cellular signalling outcomes, and ultimately drug discovery and therapeutics, remain unclear. Consideration of ligand binding and signalling… read more here.
Keywords: analytical solutions; ligand binding; protein coupled; receptor ... See more keywords
Forecasting inflation in post-oil boom years: A case for regime switches?
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DOI: 10.1007/s12197-017-9410-1
Abstract: In this study, we investigate the relative performance of various non-linear models against that of an autoregressive model in forecasting future inflation. We find that non-linear models have trivial forecast superiority over the univariate autoregressive… read more here.
Keywords: inflation; boom years; post oil; non linear ... See more keywords
Computing semiparametric efficiency bounds in linear models with nonparametric regressors
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DOI: 10.1016/j.econlet.2019.108673
Abstract: We use the computational method proposed by Severini and Tripathi (2001) to obtain semiparametric efficiency bounds in linear models with nonparametric regressors in the form of conditional expectations. Examples include social-interaction models. Explicit efficiency bounds… read more here.
Keywords: semiparametric efficiency; models nonparametric; efficiency bounds; bounds linear ... See more keywords
Multilevel customer segmentation for off-grid solar in developing countries: Evidence from solar home systems in Rwanda and Kenya
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DOI: 10.1016/j.energy.2019.07.058
Abstract: Off-grid solar systems have a number of advantages in developing countries, but they rely on the capacity of private entrepreneurs to develop a reliable customer base and methods for recruiting these customers. This study uses… read more here.
Keywords: grid solar; customer; linear models; developing countries ... See more keywords