Skip to main navigation
Skip to search
Skip to main content
Experts@Minnesota Home
Home
Profiles
Research units
University Assets
Projects and Grants
Research output
Datasets
Press/Media
Activities
Fellowships, Honors, and Prizes
Impacts
Search by expertise, name or affiliation
GLM-based statistical control r-charts for dispersed count data with multicollinearity between input variables
Kayoung Park
,
Jong Min Kim
, Dongmin Jung
Statistics (Morris)
Research output
:
Contribution to journal
›
Article
›
peer-review
27
Scopus citations
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'GLM-based statistical control r-charts for dispersed count data with multicollinearity between input variables'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Control Chart
100%
Count Data
100%
Multicollinearity
100%
Statistical Control
100%
Principal Coordinate Analysis (PCoA)
66%
Generalized Linear Model
66%
Model Fitting
33%
Poisson Distribution
33%
Overdispersion
33%
Principal Component Score
33%
Underdispersion
33%
Deviance Residual
33%
Flexible Distributions
33%
Classical Control
33%
Mathematics
Multicollinearity
100%
Statistical Control
100%
Count Data
100%
Principal Component Analysis
66%
Generalized Linear Model
66%
Residuals
33%
Poisson Distribution
33%
Fitted Model
33%
Deviance
33%
Overdispersion
33%
Simulated Data
33%
Real Data
33%
Principal Components
33%