TY - JOUR

T1 - On count time series prediction

AU - Christou, V.

AU - Fokianos, K.

PY - 2015

Y1 - 2015

N2 - We consider the problem of assessing prediction for count time series based on either the Poisson distribution or the negative binomial distribution. By a suitable parametrization we employ both distributions with the same mean. We regress the mean on its past values and the values of the response and after obtaining consistent estimators of the regression parameters, regardless of the response distribution, we employ different criteria to study the prediction problem. We show by simulation and data examples that scoring rules and diagnostic graphs that have been proposed for independent but not identically distributed data can be adapted in the setting of count dependent data.

AB - We consider the problem of assessing prediction for count time series based on either the Poisson distribution or the negative binomial distribution. By a suitable parametrization we employ both distributions with the same mean. We regress the mean on its past values and the values of the response and after obtaining consistent estimators of the regression parameters, regardless of the response distribution, we employ different criteria to study the prediction problem. We show by simulation and data examples that scoring rules and diagnostic graphs that have been proposed for independent but not identically distributed data can be adapted in the setting of count dependent data.

KW - calibration

KW - prediction

KW - probability integral transformation plot

KW - quasi-likelihood

KW - scoring rules

KW - sharpness

U2 - 10.1080/00949655.2013.823612

DO - 10.1080/00949655.2013.823612

M3 - Journal article

VL - 85

SP - 357

EP - 373

JO - Journal of Statistical Computation and Simulation

JF - Journal of Statistical Computation and Simulation

SN - 0094-9655

IS - 2

ER -