Proportional Hazards models have been widely used to analyze survival data. In many cases survival data do not verify the assumption of proportional hazards. An alternative to the PH models with more relaxed conditions are Accelerated Failure Time models. These models are fairly commonly used in the field of manufacturing, but they are more and more frequent for modeling clinical trial data. Th...

The main objective of the present study is to investigate the feasibility of using Carboxymethyl chitosan magnetic nanoparticles (CCMN) for the adsorption of Cd2+. The study also reports important parameters, which affect the adsorption process, i.e., pH, adsorbent dose, contact time and concentration of Cd2+, using Box-Behnken designs. Firstly, functional carboxymethyl chitosan magnetic nanopa...

In this pedagogical note, we treat prior elicitation and experimental design within a common decision making framework. This is contrary to the standard practice of assuming that priors are already available when performing Bayesian experimental design. We argue instead that these processes are intertwined. We demonstrate our decision-theoretic stance in the setting of learning a causal Bayesia...

This paper discusses General Random Utility Models (GRUMs). These are a class of parametric models that generate partial ranks over alternatives given attributes of agents and alternatives. We propose two preference elicitation scheme for GRUMs developed from principles in Bayesian experimental design, one for social choice and the other for personalized choice. We couple this with a general Mo...

In this extended abstract1, we consider the “small n, large p” prediction problem, where the number of available samples n is much smaller compared to the number of covariates p. This challenging setting is common for multiple applications, such as precision medicine, where obtaining additional samples can be extremely costly or even impossible. Extensive research effort has recently been dedic...

There has been an explosion of interest during the past two decades in a class of nonmarket stated-preference valuation methods known as choice experiments. The overall objective of a choice experiment is to estimate economic values for characteristics (or attributes) of an environmental good that is the subject of policy analysis, where the environmental good or service comprises several chara...

Utility functions in Bayesian experimental design are usually based on the posterior distribution. When the posterior is found by simulation, it must be sampled from for each future dataset drawn from the prior predictive distribution. Many thousands of posterior distributions are often required. A popular technique in the Bayesian experimental design literature, which rapidly obtains samples f...

In previous chapters we analyzed data from so-called one-way experimental designs, in which subjects were randomly assigned to groups that di↵ered on a single treatment or grouping variable. In this chapter we will analyze data from factorial experiments. Factorial experiments contain two or more experimental variables. In a completely crossed factorial experiment, each level of every variable ...

In this contribution different methods to excite dynamic systems are presented. Model-based/model-free and offline/online design plans are discussed and methods to optimize design plans with respect to the intended use are introduced. The presented design plans are appropriate to identify the dynamics of combustion engines and are evaluated by simulation and practical examples.