@article {9384,
	title = {Methods for preferential sampling in geostatistics},
	journal = {Journal of the Royal Statistical Society Series C},
	year = {2018},
	abstract = {<p>Preferential sampling in geostatistics occurs when the locations at which observations are made may depend on the spatial process that underlines the correlation structure of the measurements.We show that previously proposed Monte Carlo estimates for the likelihood function may not be approximating the desired function. Furthermore, we argue that, for preferential sampling of moderate complexity, alternative and widely available numerical methods to approximate the likelihood function produce better results than Monte Carlo methods. We illustrate our findings on the Galicia data set analysed previously in the literature.</p>
},
	keywords = {Geostatistics, Laplace approximation, Point processes, Preferential sampling, Template model builder},
	doi = {https://doi.org/10.1111/rssc.12286},
	author = {Dinsdale, Daniel R. and Salibian-Barrera, Mat{\'\i}as}
}
@article {wu_joint_2010,
	title = {Joint Inference on HIV Viral Dynamics and Immune Suppression in Presence of Measurement Errors},
	journal = {Biometrics},
	volume = {66},
	number = {2},
	year = {2010},
	month = {jun},
	pages = {327{\textendash}335},
	abstract = {Summary:  In an attempt to provide a tool to assess antiretroviral therapy and to monitor disease progression, this article studies association of human immunodeficiency virus (HIV) viral suppression and immune restoration. The data from a recent acquired immune deficiency syndrome (AIDS) study are used for illustration. We jointly model HIV viral dynamics and time to decrease in CD4/CD8 ratio in the presence of CD4 process with measurement errors, and estimate the model parameters simultaneously via a method based on a Laplace approximation and the commonly used Monte Carlo EM algorithm. The approaches and many of the points presented apply generally.},
	keywords = {Laplace approximation, Longitudinal data, Mixed-effects, Nonlinear models, Time-to-event},
	issn = {1541-0420},
	doi = {10.1111/j.1541-0420.2009.01308.x},
	url = {http://onlinelibrary.wiley.com/doi/10.1111/j.1541-0420.2009.01308.x/abstract},
	author = {Wu, L. and Liu, W. and Hu, X. J.}
}
