Performing Legitimate Parametric Regression Analysis without Knowing the True Underlying Random Mechanisms

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/27780

Title:	Performing Legitimate Parametric Regression Analysis without Knowing the True Underlying Random Mechanisms
Authors:	Tsou,TS
Contributors:	統計研究所
Keywords:	STATISTICAL EVIDENCE;LIKELIHOOD FUNCTIONS;MODELS
Date:	2009
Issue Date:	2010-06-29 19:33:28 (UTC+8)
Publisher:	中央大學
Abstract:	Real data are rarely normally distributed. Nonetheless, regression analysis is routinely done under the assumption of normality. Such a practice generally results in invalid statistical inferences once normality is false. This article shows how one could carry out corrected normal regression and gamma regression analysis, which provides asymptotically valid inferences without the knowledge of the true underlying distributions. No additional programming is necessary in order to implement the proposed novel regression method. Outputs provided by existing statistical software suffice.
Relation:	COMMUNICATIONS IN STATISTICS-THEORY AND METHODS
Appears in Collections:	[Graduate Institute of Statistics] journal & Dissertation

Files in This Item:

File	Description	Size	Format
index.html		0Kb	HTML	460	View/Open

社群 sharing