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Improved confidence intervals for nonlinear mixed-effects and nonparametric regression models
Annals of the Institute of Statistical MathematicsStatistical inference for high dimensional parameters (HDPs) can be based on their intrinsic correlation; that is, parameters that are close spatially or temporally tend to have more similar values.
Nan Zheng, N. Cadigan
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Social Science Research Network
We use nonparametric methods to compute the environmental inefficiency of 100 countries over the period 1990-2017 on the macro-level. The inefficiency is expressed as the potential reduction of GHG emissions, holding economic output constant.
L. Fait +3 more
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We use nonparametric methods to compute the environmental inefficiency of 100 countries over the period 1990-2017 on the macro-level. The inefficiency is expressed as the potential reduction of GHG emissions, holding economic output constant.
L. Fait +3 more
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A note on Nonparametric Confidence Interval for a Shift Parameter for Cauchy distribution
, 2007In this article an application of a kernel based nonparametric approach in constructing a large sample nonparametric confidence interval for a shift parameter is considered. The method is illustrated using the Cauchy distribution as a location model. The
L. Odongo
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Communications in statistics. Simulation and computation, 2019
In medical studies, we usually are interested in comparing the treatment effects of the drug according to the difference of two median survival times.
Yu-Mei Chang, P. Shen, Yuanyuan Tang
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In medical studies, we usually are interested in comparing the treatment effects of the drug according to the difference of two median survival times.
Yu-Mei Chang, P. Shen, Yuanyuan Tang
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Biostatistics
Mediation analysis is a useful tool in investigating how molecular phenotypes such as gene expression mediate the effect of exposure on health outcomes.
Zhichao Xu +4 more
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Mediation analysis is a useful tool in investigating how molecular phenotypes such as gene expression mediate the effect of exposure on health outcomes.
Zhichao Xu +4 more
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Nonparametric Bootstrap Confidence Intervals for High-Quantiles of Heavy-Tailed Distributions
, 2018In risk management areas such as reinsurance, the need often arises to construct a confidence interval for a quantile in the tail of the distribution; for example, there is high probability that the sample maximum lies near or below the quantile.
S. Litvinova, M. Silvapulle
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Nonparametric Additive Models for Billion Observations
Journal of Computational And Graphical StatisticsThe nonparametric additive model (NAM) is a widely used nonparametric regression method. Nevertheless, due to the high computational burden, classic statistical techniques for fitting NAMs are not well-equipped to handle massive data with billions of ...
Mengyu Li, Jingyi Zhang, Cheng Meng
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A novel nonparametric confidence interval for differences of proportions for correlated binary data
Statistical Methods in Medical Research, 2018Chongyang Duan +4 more
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A nonparametric confidence interval for the trimmed mean
, 2002Min Tsao, Julie Zhou
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Nonparametric confidence intervals for ranked set samples
Computational statistics (Zeitschrift), 2017Santu Ghosh +2 more
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