This article develops a set of tools for smoothing and prediction with dependent point event patterns. The methodology is motivated by the problem of tracking weekly maps of violent crime events, but is designed to be straightforward to adapt to a wide variety of alternative settings. In particular, a Bayesian semiparametric framework is introduced for modeling correlated time series of marked ...

We introduce a flexible marginal modelling approach for statistical inference for clustered/longitudinal data under minimal assumptions. This estimated estimating equations (EEE) approach is semiparametric and the proposed models are fitted by quasi-likelihood regression, where the unknown marginal means are a function of the fixed-effects linear predictor with unknown smooth link, and variance...

Classical peaks over threshold analysis is widely used for statistical modeling of sample extremes, and can be supplemented by a model for the sizes of clusters of exceedances. Under mild conditions a compound Poisson process model allows the estimation of the marginal distribution of threshold exceedances and of the mean cluster size, but requires the choice of a threshold and of a run paramet...

We model monthly disease counts on an age-time grid using the two-dimensional varying-coefficient Poisson regression. Since the marginal profile of counts shows a very strong and varying annual cycle, sine and cosine regressors model periodicity, but their coefficients are allowed to vary smoothly over the age and time plane. The coefficient surfaces are estimated using a relatively large tenso...

Approximately 100,000 youths are currently incarcerated in the US, yet little is known whether such a penalty deters future crime or interrupts human capital formation in a way that increases the likelihood of later criminal behavior. This paper uses the incarceration tendency of randomly-assigned judges as an instrumental variable to estimate causal effects of juvenile incarceration on adult r...

We characterize all stationary time-reversible Markov processes whose finite-dimensional marginal distributions (of all orders) are infinitely divisible. Aside from two trivial cases (iid and constant), every such process with full support in both discrete and continuous time is a branching process with Poisson or Negative Binomial marginal distributions and a specific bivariate distribution at...

In this paper, dynamic aspects of railway infrastructure operation and maintenance costs in Sweden are explored. Econometric cost functions are estimated to check the robustness of previous marginal cost estimates by introducing lags and leads of both dependent and independent variables. We find support for a forward-looking behaviour within the Swedish National Rail Administration (Banverket) ...

Suppose we have data from a bivariate model with parametric marginals. Efficient estimators of the parameters in the marginal models are generally not efficient in the bivariate model. In this article, we propose a method of improving these marginal estimators and demonstrate that the magnitude of this improvement can be as large as 100 percent in some cases.

Approximately 100,000 youths are currently incarcerated in the US, yet little is known whether such a penalty deters future crime or interrupts human capital formation in a way that increases the likelihood of later criminal behavior. This paper uses the incarceration tendency of randomly-assigned judges as an instrumental variable to estimate causal effects of juvenile incarceration on adult r...