On Gamma Regression Residuals
نویسندگان
چکیده مقاله:
In this paper, ‎we propose new residuals for gamma regression models, ‎assuming that both mean and shape parameters follow regression structures. The models are summarized and fitted by applying both classic and Bayesian methods as proposed by Cepeda-Cuervo (2001). The residuals are proposed from properties of the biparametric exponential family of distributions. ‎Simulated and real data sets‎ ‎are analyzed to determine the performance and behavior of the proposed residuals. ‎
منابع مشابه
On the misuse of residuals in ecology: regression of residuals vs. multiple regression
1. Residuals from linear regressions are used frequently in statistical analysis, often for the purpose of controlling for unwanted effects in multivariable datasets. This paper criticizes the practice, building upon recent critiques. 2. Regression of residuals is often used as an alternative to multiple regression, often with the aim of controlling for confounding variables. When correlations ...
متن کاملNonlinear Structure in Regression Residuals
Phase space reconstruction is investigated as a diagnostic tool for determining the structure of detected nonlinear processes in regression residuals. Empirical evidence supporting this approach is provided using simulations from an Ikeda mapping and the S&P 500. Results in the form of phase portraits (e.g., scatter plots of reconstructed dynamical systems) provide qualitative information to di...
متن کاملOn studentized residuals in the quantile regression framework
Although regression quantiles (RQs) are increasingly becoming popular, they are still playing a second fiddle role to the ordinary least squares estimator like their robust counterparts due to the perceived complexity of the robust statistical methodology. In order to make them attractive to statistical practitioners, an endeavor to studentize robust estimators has been undertaken by some resea...
متن کاملRobust Lasso Regression with Student-t Residuals
The lasso, introduced by Robert Tibshirani in 1996, has become one of the most popular techniques for estimating Gaussian linear regression models. An important reason for this popularity is that the lasso can simultaneously estimate all regression parameters as well as select important variables, yielding accurate regression models that are highly interpretable. This paper derives an efficient...
متن کاملA Test for Normality of Observations and Regression Residuals
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive o...
متن کاملStatistical Graphics of Pearson Residuals in Survey Logistic Regression Diagnosis
Survey data logistic regression analysis, as computationally available in SAS SURVEYLOGISTIC procedure, has been widely conducted in survey research practice. A set of diagnostic statistics in the procedure, borrowed from the logistic regression in generalized linear models, is used for model assessment. However, for survey data, the statistical underpinnings of these statistics may need to be ...
متن کاملمنابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ذخیره در منابع من قبلا به منابع من ذحیره شده{@ msg_add @}
عنوان ژورنال
دوره 15 شماره None
صفحات 29- 44
تاریخ انتشار 2016-07
با دنبال کردن یک ژورنال هنگامی که شماره جدید این ژورنال منتشر می شود به شما از طریق ایمیل اطلاع داده می شود.
میزبانی شده توسط پلتفرم ابری doprax.com
copyright © 2015-2023