Add to ORKGInteger-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-valued phenomena that evolve over time. The distribution of an INAR(p) process is essentially described by two parameters: a vector of autoregression coefficients and a probability distribution on the nonnegative integers, called an immigration or innovation distribution. Traditionally, parametric models are considered where the innovation distribution is assumed to belong to a parametric family. This paper instead considers a more realistic semiparametric INAR(p) model where there are essentially no restrictions on the innovation distribution. We provide an (semiparametrically) efficient estimator of both the autoregression parameters and the i...
This paper considers the periodic self-exciting threshold integer-valued autoregressive processes un...
We consider integer-valued autoregressive models of order one contaminated with in-novational outlie...
Suppose we observe a time series that alternates between different nonlinear autore-gressive process...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
Integer-valued auto-regressive (INAR) processes have been introduced to model non-negative integer-v...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integervalu...
Integer-valued autoregressive (INAR) processes have been introduced to model non-negative integer-va...
Integer-valued autoregressive (INAR) time series form a very useful class of processes suitable to m...
The INteger-valued AutoRegressive (INAR) processes were introduced in the literature by Al-Osh and A...
We illustrate several recent results on efficient estimation for semiparametric time series models w...
The INteger-valued AutoRegressive (INAR) processes were introduced in the lite-rature by Al-Osh and ...
In this paper, an integer-valued autoregressive model of order one (INAR(1)) with time-varying param...
In recent years, many attempts have been made to find accurate models for integer-valued times serie...
The purpose of this paper is to introduce and develop a family of Z+-valued autoregressive processes...
This paper considers the periodic self-exciting threshold integer-valued autoregressive processes un...
We consider integer-valued autoregressive models of order one contaminated with in-novational outlie...
Suppose we observe a time series that alternates between different nonlinear autore-gressive process...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
Integer-valued auto-regressive (INAR) processes have been introduced to model non-negative integer-v...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integer-val...
Integer-valued autoregressive (INAR) processes have been introduced to model nonnegative integervalu...
Integer-valued autoregressive (INAR) processes have been introduced to model non-negative integer-va...
Integer-valued autoregressive (INAR) time series form a very useful class of processes suitable to m...
The INteger-valued AutoRegressive (INAR) processes were introduced in the literature by Al-Osh and A...
We illustrate several recent results on efficient estimation for semiparametric time series models w...
The INteger-valued AutoRegressive (INAR) processes were introduced in the lite-rature by Al-Osh and ...
In this paper, an integer-valued autoregressive model of order one (INAR(1)) with time-varying param...
In recent years, many attempts have been made to find accurate models for integer-valued times serie...
The purpose of this paper is to introduce and develop a family of Z+-valued autoregressive processes...
This paper considers the periodic self-exciting threshold integer-valued autoregressive processes un...
We consider integer-valued autoregressive models of order one contaminated with in-novational outlie...
Suppose we observe a time series that alternates between different nonlinear autore-gressive process...