Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Soma Sekhar Dhavala

Showing results (1-10 of 4) with videos related to

Pageof 1
Sort By:
Accident; Analysis and Prevention|January 25, 2012
The negative binomial-Lindley generalized linear model: characteristics and application using crash dataSrinivas Reddy Geedipally, Dominique Lord, Soma Sekhar Dhavala
Accident; Analysis and Prevention|March 7, 2016
A semiparametric negative binomial generalized linear model for modeling over-dispersed count data with a heavy tail: Characteristics and applications to crash dataMohammadali Shirazi, Dominique Lord, Soma Sekhar Dhavala, et al.
Accident; Analysis and Prevention|September 9, 2017
A methodology to design heuristics for model selection based on the characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB)Mohammadali Shirazi, Soma Sekhar Dhavala, Dominique Lord, et al.
Risk Analysis : an Official Publication of the Society for Risk Analysis|August 2, 2011
Characterizing the performance of the Conway-Maxwell Poisson generalized linear modelRoyce A Francis, Srinivas Reddy Geedipally, Seth D Guikema, et al.
Pageof 1

Showing results (1-10 of 4) with videos related to

Sort By:
Pageof 1
Accident; Analysis and Prevention|January 25, 2012
The negative binomial-Lindley generalized linear model: characteristics and application using crash dataSrinivas Reddy Geedipally, Dominique Lord, Soma Sekhar Dhavala
Accident; Analysis and Prevention|March 7, 2016
A semiparametric negative binomial generalized linear model for modeling over-dispersed count data with a heavy tail: Characteristics and applications to crash dataMohammadali Shirazi, Dominique Lord, Soma Sekhar Dhavala, et al.
Accident; Analysis and Prevention|September 9, 2017
A methodology to design heuristics for model selection based on the characteristics of data: Application to investigate when the Negative Binomial Lindley (NB-L) is preferred over the Negative Binomial (NB)Mohammadali Shirazi, Soma Sekhar Dhavala, Dominique Lord, et al.
Risk Analysis : an Official Publication of the Society for Risk Analysis|August 2, 2011
Characterizing the performance of the Conway-Maxwell Poisson generalized linear modelRoyce A Francis, Srinivas Reddy Geedipally, Seth D Guikema, et al.
Pageof 1