The Study of Confidence Interval Coverage for Small Samples of Overdispersed Count Data
碩士 === 國立臺灣大學 === 農藝學研究所 === 91 === The inference of GLM (generalized linear models) is based on the properties of maximum likelihood estimate, such as asymptotic normality and asymptotic variance covariance matrix. However, the sample size of real life data seldom are large. Therefore th...
Main Authors: | Chen, Wei-Ting, 陳威廷 |
---|---|
Other Authors: | Pong, Yun-Ming |
Format: | Others |
Language: | zh-TW |
Published: |
2003
|
Online Access: | http://ndltd.ncl.edu.tw/handle/40240222604227989189 |
Similar Items
-
Inference for overdispersion in count data without making distributional assumptions
by: Ya-ting Tsao, et al.
Published: (2011) -
Mean and Variance Modeling of Under- and Overdispersed Count Data
by: David M. Smith, et al.
Published: (2016-03-01) -
Comparison of the test power of some test procedures for overdispersed count data
by: shu-chun chen, et al.
Published: (2002) -
Leaf count overdispersion in coffee seedlings
by: Edilson Marcelino Silva, et al.
Published: (2019-04-01) -
Analysis of overdispersed count data: A multilevel modeling approach
by: Fazle Elahi, et al.
Published: (2020-06-01)