CALIBRATION FOR INVERSE GAUSSIAN REGRESSION

被引：4

作者：

WOLDIE, M

FOLKS, JL

机构：

[1] TEXAS SO UNIV,HOUSTON,TX 77004

[2] OKLAHOMA STATE UNIV,STILLWATER,OK 74078

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1995年 / 24卷 / 10期

关键词：

REGRESSION; ZERO INTERCEPT; NONCONSTANT VARIANCE; PREDICTION INTERVAL; CALIBRATION;

D O I：

10.1080/03610929508831636

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

Inverse Gaussian regression models are useful for regression data where both variables are nonnegative and the variance of the dependent variable depends on the independent variable. Zero intercept inverse Gaussian regression models are presented with non-constant variance, constant ratio of variance to the mean and constant coefficient of variation. For purposes of calibration, the prediction band is used to give point and interval estimators for the independent variable. The results illustrated with a real data set.

引用

页码：2609 / 2620

页数：12

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