AU - Meshkani, Reza
TI - Regression Analysis under Inverse Gaussian Model: Repeated Observation Case
PT - JOURNAL ARTICLE
TA - srtc-jsri
JN - srtc-jsri
VO - 1
VI - 1
IP - 1
4099 - http://jsri.srtc.ac.ir/article-1-138-en.html
4100 - http://jsri.srtc.ac.ir/article-1-138-en.pdf
SO - srtc-jsri 1
ABĀ - Traditional regression analyses assume normality of observations and independence of mean and variance. However, there are many examples in science and Technology where the observations come from a skewed distribution and moreover there is a functional dependence between variance and mean. In this article, we propose a method for regression analysis under Inverse Gaussian model when there are repeated observations for a fixed value of explanatory variable. The problem is treated by likelihood, Bayes, and empirical Bayes procedures, using conjugate priors. Inferences are provided for regression analysis.
CP - IRAN
IN -
LG - eng
PB - srtc-jsri
PG - 31
PT - Research
YR - 2004