Showing papers by "Douglas M. Bates published in 1992"
TL;DR: The multiphasic logistic function has recently been proposed as a model for lactation curves in dairy cattle and may be useful for examining dosage effects in long-term bST studies in which injections begin in midlactation or later.
10 citations
TL;DR: This paper uses the modified method of Kaufman to exploit both loose coupling and conditional linearity in nonlinear least squares problems where some parameters affect only some of the predicted responses while other parameters affect all the predictedResponses.
8 citations
01 Jan 1992
TL;DR: The nonlinear regression model is considered but these approaches to inference are applicable in more general circumstances and it is felt the comparisons will remain useful.
Abstract: : As greater computing power becomes routinely available to researchers, analyses based on Bayesian or likelihood methods become easier to perform, especially since the increase in computing power has been accompanied by development of inventive statistical algorithms for inference. We consider here the nonlinear regression model but these approaches to inference are applicable in more general circumstances and we feel the comparisons will remain useful. Several methods can be used for inference in nonlinear regression: propagation of errors, likelihood profiles, approximate marginal likelihoods and posteriors, and Monte Carlo methods such as importance sampling, and the Gibbs sampler. These methods vary in computing intensity and in their ability to handle poorly conditioned situations. Furthermore, since some of these methods have only been recently developed, it is not easy for the practitioner to compare them and choose between them because they are not widely implemented. We demonstrate the respective merits of these methods in a small but instructive example. Nonlinear Models; Profile Likelihood; Importance Sampling; Gibbs Sampler, Approximate Marginalization.
1 citations