Results 221 to 230 of about 706,502 (262)

Random weightingT-statistics in linear regression models

Acta Mathematica Sinica, 1995
Summary: We have constructed a random weighting statistic to approximate the distribution of the Studentized least square estimator in a linear regresion model with ideal accuracy \(o(n^{- 1/2})\). Thus, we have provided a more practical distribution approximation method.
Shi, Jian, Zheng, Zhongguo
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Random effects in ordinal regression models

Computational Statistics & Data Analysis, 1996
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Tutz, Gerhard, Hennevogl, Wolfgang
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Problems in regression modeling of randomized clinical trials

Int. Journal of Clinical Pharmacology and Therapeutics, 2005
Data modeling can be applied to improving the precision of clinical studies and multiple regression modeling is increasingly used for this purpose.To assess the uncertainties and risks of misinterpretations commonly encountered in regression analyses and rarely communicated in research papers.Regression analyses add uncertainties to the data in the ...
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LEARNING RANDOM MODEL TREES FOR REGRESSION

International Journal of Computers and Applications, 2011
AbstractRegression is one of the most important tasks in real-world data mining applications. Among a large number of regression models, model tree is an excellent regression model. In this paper, we single out an improved model tree algorithm via introducing randomness into the process of building model trees.
Chaoqun Li, Hongwei Li
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Regression models for Boolean random sets

Journal of Applied Statistics, 2006
Abstract In this paper we consider the regression problem for random sets of the Boolean-model type. Regression modeling of the Boolean random sets using some explanatory variables are classified according to the type of these variables as propagation, growth or propagation-growth models.
M. Khazaee, K. Shafie
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Regression models for positive random variables

Journal of Econometrics, 1990
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McDonald, James B., Butler, Richard J.
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Formulation of Fuzzy Random Regression Model

2011
In real-world regression analysis, statistical data may be linguistically imprecise or vague. Given the co-existence of stochastic and fuzzy uncertainty, real data cannot be characterized by using only the formalism of random variables.
Junzo Watada, Shuming Wang, Witold Pedrycz   +2 more
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Weighted Random Regression Models and Dropouts

Drug Information Journal, 2004
In studies with repeated measurements, one of the popular primary interests is the comparison of the rates of change in a response variable between groups. The random regression model (RRM) has been offered as a potential solution to statistical problems posed by dropouts in clinical trials.
Chul Ahn, Sin-Ho Jung, Seung-Ho Kang
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Bayesian model selection for logistic regression models with random intercept

Computational Statistics & Data Analysis, 2012
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Helga Wagner, Christine Duller
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Semiparametric random coefficient regression models

Annals of the Institute of Statistical Mathematics, 1993
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