TY - JOUR
T1 - Heterogeneous Weibull count distribution
AU - Karina, Tania M.
AU - Nurrohmah, Siti
AU - Fithriani, Ida
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2019/5/31
Y1 - 2019/5/31
N2 - In this paper, we present a generalized model for count data based upon an assumed Weibull interarrival times. Weibull interarrival times could handle overdispersed data with shape parameter 0 < c < 1, and underdispersed data with c > 1, and is reduced as exponential when c = 1. Weibull count model will be obtained by Taylor expansion and convolution method. By mixing, we obtain heterogeneous Weibull count model. Finally, we fit this model and several other models to non-equidispersed data and show that this model fit the data better than Poisson.
AB - In this paper, we present a generalized model for count data based upon an assumed Weibull interarrival times. Weibull interarrival times could handle overdispersed data with shape parameter 0 < c < 1, and underdispersed data with c > 1, and is reduced as exponential when c = 1. Weibull count model will be obtained by Taylor expansion and convolution method. By mixing, we obtain heterogeneous Weibull count model. Finally, we fit this model and several other models to non-equidispersed data and show that this model fit the data better than Poisson.
UR - http://www.scopus.com/inward/record.url?scp=85067801413&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/1218/1/012020
DO - 10.1088/1742-6596/1218/1/012020
M3 - Conference article
AN - SCOPUS:85067801413
SN - 1742-6588
VL - 1218
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012020
T2 - 3rd International Conference on Mathematics; Pure, Applied and Computation, ICoMPAC 2018
Y2 - 20 October 2018
ER -