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Using Tweedie distributions for fitting spike count data
Dina Moshitch
*
,
Israel Nelken
*
Corresponding author for this work
Edmond & Lily Safra Center for Brain Sciences
Department of Neurobiology (Natural Sciences)
Research output
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Article
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peer-review
13
Scopus citations
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Keyphrases
Count Data
100%
Spike Count
100%
Tweedie Distribution
100%
Interaural Time Difference
50%
Additive Effect
33%
Neuronal Responses
33%
Generalized Linear Model
33%
Count Distribution
33%
Significance Testing
16%
Strong Dependence
16%
Neural Data
16%
Primary Auditory Cortex
16%
Gaussian Distribution
16%
Poisson Distribution
16%
Test Reliability
16%
Long Tail
16%
Family of Distributions
16%
Generalized Model
16%
Tweedie Family
16%
Overdispersion
16%
Variance Effects
16%
Over-dispersed
16%
Poisson Assumption
16%
Mathematics
Spike Count
100%
Count Data
100%
Variance
83%
Time Difference
50%
Generalized Linear Model
33%
Gaussian Distribution
16%
Analysis of Variance
16%
Multiplicative
16%
Covariate
16%
Poisson Distribution
16%
Overdispersion
16%