This book brings together a variety of non-Gaussian autoregressive-type models to analyze time-series data. This book collects and collates most of the available models in the field and provide their probabilistic and inferential properties. This book classifies the stationary t…
Researchers and students who use empirical investigation in their work must go through the process of selecting statistical methods for analyses, and they are often challenged to justify these selections. This book is designed for readers with limited background in statistical m…
Integrated data analyses are becoming increasingly popular in studies of wild animal populations where two or more separate sources of data contain information about common parameters. Here we develop an integrated population model using abundance and demographic data from a stu…
We study how to perform effective Bayesian inference in high-dimensional sparse Factor Analysis models with a zero-norm, sparsity-inducing prior on the model parameters. Such priors represent a methodological ideal, but Bayesian inference in such models is usually regarded as im…
The process of blending observational data in numerical models can be formulated using the Bayesian estimation method. The Bayesian statistical framework strives to find the best state and/or parameter estimates using (a) the stochastic computational model and (b) the noisy obse…
The purpose of this paper is to investigate the effect of fatigue, in the presence of neighboring cracks, and to integrate that into a probabilistic physics of failure based model that could be used to predict crack growth. A total of 20 fatigue experiments were performed at dif…
Phylogenetic analyses that incorporate extinct taxa and assess models for absolute fit allow a more complete picture of evolutionary history to be captured. The Fossilized Birth-Death (FBD) model is a robust yet flexible model of diversification and sampling that considers all a…
Landscapes and sedimentary records host important information about the evolutionary history of the Earth and other planetary bodies. The successful extraction of such information from the preserved record requires a comprehensive understanding of the encoding, propagation, and …
Over the past several decades, reinforcement learning has emerged as a unifying framework for reward-based learning and decision making in brains, minds and machines. With a long history crisscrossing the fields of psychology, neuroscience, and artificial intelligence, reinforce…
Phylogenetic trees are key objects for understanding evolutionary history, first used to describe relationships between groups of species. Phylogenies help us to fill out the tree of life and to describe the dynamics that have given rise to the diversity of life on Earth. As we …
Inference of the evolutionary histories of species, commonly represented by a species tree, is complicated by the divergent evolutionary history of different parts of the genome. Different loci on the genome can have different histories from the underlying species tree (and each…
Complex patient are becoming more and more of a challenge to the health care system given the amount of care they require and the amount of documentation needed to keep track of their state of health and treatment. Record keeping using the EHR makes this easier but mounting amou…
This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the p…
This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the p…
This open access book provides a comprehensive treatment of recent developments in kernel-based identification that are of interest to anyone engaged in learning dynamic systems from data. The reader is led step by step into understanding of a novel paradigm that leverages the p…
