Semiparametric random coefficient regression models
Copyright policy )Semiparametric random coefficient regression models
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
- University of California, Berkeley United States
coefficient distributions, goodness-of-fit tests, heteroscedastic errors, confidence regions, Linear regression; mixed models, Asymptotic distribution theory in statistics, deconvolution, prediction regions, Nonparametric tolerance and confidence regions, linearized bootstrap, minimum distance estimates, empirical characteristic function, random effects, errors-in-variables, semiparametric, random coefficient regression model, Nonparametric hypothesis testing
coefficient distributions, goodness-of-fit tests, heteroscedastic errors, confidence regions, Linear regression; mixed models, Asymptotic distribution theory in statistics, deconvolution, prediction regions, Nonparametric tolerance and confidence regions, linearized bootstrap, minimum distance estimates, empirical characteristic function, random effects, errors-in-variables, semiparametric, random coefficient regression model, Nonparametric hypothesis testing
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).6 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!