The compound Poisson INAR(1) model for time series of overdispersed counts is considered. For such CPINAR(1) processes, explicit results are derived for joint moments, for the k-step-ahead distribution as well as for the stationary distribution. It is shown that a CPINAR(1) process is strongly...

Traffic flow data are primarily used to monitor road use and to compute road accident rates in Great Britain. The main traffic flow data used for these purposes measure annual traffic flow in vehicle kilometres, however this dataset is limited in its disaggregation. In particular, it is not...

An expectation–maximization (EM) algorithm for factor analysis parameter estimation when observations are missing is developed. In contrast to existing EM algorithms for this problem, the algorithm here is developed assuming the missing observations are not part of the complete data in the EM...

The information content of several interest rate spreads for future output growth is analyzed using wavelet analysis. The “scale-by-scale” regression analysis shows that standard indicators of the stance of monetary policy, such as the shape of the yield curve, the real federal funds rate,...

The problem of finding a template function that represents the common pattern of a sample of curves is considered. To address this issue, a novel algorithm based on a robust version of the isometric featuring mapping (Isomap) algorithm is developed. When the functional data lie on an unknown...

There are many areas of science and engineering where research and decision making are performed using computer models. These computer models are usually deterministic and may take minutes, hours or days to produce an output for a single value of the model inputs. Fitting mixtures of experts of...

A new likelihood-based panel cointegration test which allows a linear time trend in the data generating process is proposed. The test is an extension of the likelihood ratio type test with trend adjustment prior to testing to the panel data framework. Under the null hypothesis, the standardized...

A new regression model for recurrent events from repairable systems is proposed. The effectiveness of each repair in Kijima models I and II is regressed on repair-specific covariates. By modeling effective age in a flexible way, the model allows a spectrum of heterogeneous repairs besides...

The latent class model provides an important platform for jointly modeling mixed-mode data—i.e., discrete and continuous data with various parametric distributions. Multiple mixed-mode variables are used to cluster subjects into latent classes. While the mixed-mode latent class analysis is a...

We address the issue of performing testing inference in generalized linear models when the sample size is small. This class of models provides a straightforward way of modeling normal and non-normal data and has been widely used in several practical situations. The likelihood ratio, Wald and...