3 citations · 7 across the 6 of their papers we have counts for
6 papers
Statistical Inference for Generalized Integer Autoregressive Processes
Pashmeen Kaur, Peter F. Craigmile
A popular and flexible time series model for counts is the generalized integer autoregressive process of order , GINAR(). These Markov processes are defined using thinning op…
Modeling Nonstationary Time Series using Locally Stationary Basis Processes
Shreyan Ganguly, Peter F. Craigmile
Methods of estimation and forecasting for stationary models are well known in classical time series analysis. However, stationarity is an idealization which, in practice, can at be…
Optimal Design Emulators: A Point Process Approach
Matthew T. Pratola, C. Devon Lin, Peter F. Craigmile
Design of experiments is a fundamental topic in applied statistics with a long history. Yet its application is often limited by the complexity and costliness of constructing experi…
Marginally Interpretable Generalized Linear Mixed Models
Jeffrey J. Gory, Peter F. Craigmile, Steven N. MacEachern
Two popular approaches for relating correlated measurements of a non-Gaussian response variable to a set of predictors are to fit a marginal model using generalized estimating equa…
Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization
Grant Schneider, Peter F. Craigmile, Radu Herbei
Stochastic Differential Equations (SDEs) are used as statistical models in many disciplines. However, intractable likelihood functions for SDEs make inference challenging, and we n…
Discussion of: A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?
Peter Craigmile, Bala Rajaratnam
Discussion of "A statistical analysis of multiple temperature proxies: Are reconstructions of surface temperatures over the last 1000 years reliable?" by B.B. McShane and A.J. Wyne…