TY - JOUR
T1 - The likelihood of the parameters of a continuous time vector autoregressive model
AU - McCrorie, James Roderick
PY - 2002/10
Y1 - 2002/10
N2 - This paper provides a method of constructing the likelihood function of the parameters of a continuous time vector autoregressive model on the basis of discrete data without requiring the restrictions extant methods impose on the data that are capable of being rejected by a statistical test. In particular, the method does not rely on a steady-state assumption that can rule out unit root processes; it allows for weak assumptions on the innovations; and it allows for a mixture of skip-sampled and temporally-aggregated data.
AB - This paper provides a method of constructing the likelihood function of the parameters of a continuous time vector autoregressive model on the basis of discrete data without requiring the restrictions extant methods impose on the data that are capable of being rejected by a statistical test. In particular, the method does not rely on a steady-state assumption that can rule out unit root processes; it allows for weak assumptions on the innovations; and it allows for a mixture of skip-sampled and temporally-aggregated data.
U2 - 10.1023/A:1021283821215
DO - 10.1023/A:1021283821215
M3 - Article
SN - 1387-0874
VL - 5
SP - 273
EP - 286
JO - Statistical Inference for Stochastic Processes
JF - Statistical Inference for Stochastic Processes
IS - 3
ER -