Bayesian inference and model choice in a hidden stochastic two-compartment model of hematopoietic stem cell fate decisions

Despite rapid advances in experimental cell biology, the in vivo behavior of hematopoietic stem cells (HSC) cannot be directly observed and measured. Previously we modeled feline hematopoiesis using a two-compartment hidden Markov process that had birth and emigration events in the first compartment. Here we perform Bayesian statistical inference on models which contain two additional events in the first compartment in order to determine if HSC fate decisions are linked to cell division or occur independently. Pareto Optimal Model Assessment approach is used to cross check the estimates from Bayesian inference. Our results show that HSC must divide symmetrically (i.e., produce two HSC daughter cells) in order to maintain hematopoiesis. We then demonstrate that the augmented model that adds asymmetric division events provides a better fit to the competitive transplantation data, and we thus provide evidence that HSC fate determination in vivo occurs both in association with cell division and at a separate point in time. Last we show that assuming each cat has a unique set of parameters leads to either a significant decrease or a nonsignificant increase in model fit, suggesting that the kinetic parameters for HSC are not unique attributes of individual animals, but shared within a species.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS269 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Why distinguish between statistics and mathematical statistics - the case of Swedish academia

A separation between the academic subjects statistics and mathematical statistics has existed in Sweden almost as long as there have been statistics professors. The same distinction has not been maintained in other countries. Why is it kept in Sweden?In May 2015 it has been 100 years since Mathematical Statistics was formally established as an academic discipline at a Swedish university where Statistics had existed since the turn of the century. We give an account of the debate in Lund and elsewhere about this division during the first decades after 1900 and present two of its leading personalities. The Lund University astronomer (and mathematical statistician) C.V.L. Charlier was a leading proponent for a position in mathematical statistics at the university. Charlier's adversary in the debate was Pontus Fahlbeck, professor in political science and statistics, who reserved the word statistics for ``statistics as a social science''. Charlier not only secured the first academic position in Sweden in mathematical statistics for his former Ph.D. student Sven Wicksell, but he also demonstrated that a mathematical statistician can be influential in matters of state, finance, as well as in different natural sciences. Fahlbeck saw mathematical statistics as a set of tools that sometimes could be useful in his brand of statistics. After a summary of the organisational growth of the statistical sciences in Sweden that has taken place during the last 50 years, we discuss what effects the Charlier-Fahlbeck divergence might have had on this development

Estimation of the offspring mean in a branching process with non stationary immigration

© 2016, © Taylor & Francis Group, LLC. In the paper, we consider a natural estimator of the offspring mean of a branching process with non stationary immigration based on observation of population sizes and number of immigrating individuals to each generation. We demonstrate that using a central limit theorem for multiple sums of dependent random variables it is possible to derive asymptotic distributions for the estimator without prior knowledge about the behavior (criticality) of the reproduction process. Before the three cases of criticality have been considered separately. Assuming that the immigration mean and variance vary regularly, conditions guaranteeing the strong consistency of the proposed estimator is also derived

Regional climate model assessment using statistical upscaling and downscaling techniques

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/92355/1/env_2145_sm.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/92355/2/env2145.pd

What we look at in paintings: A comparison between experienced and inexperienced art viewers

How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought of as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, and compare the eye movements of experienced and inexperienced art viewers. In addition, we develop a stochastic model, which is rather simple but fits quite well to the eye movement data, to further investigate the differences between the two groups through functional summary statistics