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An INAR(1) negative multinomial regression model for longitudinal count data
Ulf Böckenholt
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Keyphrases
Multinomial Logistic Regression Model
100%
INAR(1)
100%
Longitudinal Count Data
100%
Negative Binomial
100%
Random Effects
33%
Regression Model
33%
Personality Factors
33%
Poisson Process
33%
Time-dependent Correlation
33%
Bivariate Negative Binomial Distribution
33%
Emotion Experience
33%
Daily Emotions
33%
First-order Autoregressive Model
33%
Negative multinomial Distribution
33%
Integer Values
33%
Mathematics
Regression Model
100%
Count Data
100%
Integer
50%
Bivariate
50%
Multinomial Distribution
50%
Negative Binomial Distribution
50%
Random Effect
50%