Upcoming Seminar:
Title: Attitudes Towards Firm and Competition: How do they Matter for CRM Activities?
Speaker: Nalini Ravishanker
Department of Statistics, University of Connecticut
Abstract:
Easy availability of information on a customer's transactions with the firm and the pressure to establish financial returns from marketing investments has led to a dominance of models that directly connect marketing investments to sales at the customer level. Customer's attitudes, on the other hand, have always been assumed to influence customer's reactions to a firm's marketing communications, but rarely included in models that determine customer value. We empirically assess (a) the role of customer's attitudes in determining their value to the firm, and (b) how knowledge of customer attitudes can influence a firm's customer management strategy. Specifically, we evaluate which aspects of attitudes, i.e., attitudes towards firm or competition, have a bigger effect on customer behavior, and whether customer attitudes are more important for managing some customers than others. We use monthly sales call, sales, and survey based attitude information collected over three years from the same customers of a multinational pharmaceutical firm for this study. We develop a hierarchical generalized dynamic linear model (HGDLM) framework that combines the sales call and sales data that are available at regular time intervals, with customer attitudes that are not available at regular intervals, and carry out inference in the Bayesian framework.
Time: Monday, October 19th 4:00-5:00 pm
Location: Funger Hall 520 (2201 G Street, NW)
Title: Combining Simulations and Physical Observations to Estimate Cosmological Parameters
Speaker: David Higdon
Statistical Sciences, Los Alamos National Laboratory
Abstract:
The Lambda-Cold Dark Matter (LCDM) model of cosmology is perhaps the simplest model that best describes the makeup and evolution of the universe in accordance with physical observations. This model contains up to 20 different cosmological parameters from space and ground based surveys.
These cosmological measurements have reached a remarkable level of accuracy over the last decade. Future sky surveys promise to give even more numerous and more accurate data. However, such data does not inform directly about the cosmological parameters of interest. Detailed physical simulation models are typically required to relate information from these surveys to cosmological parameters of interest. A Bayesian formulation adapted from Kennedy and O'Hagan (2001) and Higdon et al. (2008) is used to give parameter constraints from physical observations and a limited number of simulations. The framework is based on the idea of replacing the simulator by an emulator which can then be used to facilitate computations required for the analysis. In this talk I'll describe an application that uses large scale structure and Cosmic Microwave Background (CMB) data to inform about a subset of the
parameters controlling the LCDM model.
Time: Friday, October 9th 4:30-5:30 pm (Followed by wine & cheese reception)
Location: Duques Hall 652 (2201 G Street, NW)