The Zombie Apocalypse

The concept of the living dead has been a subject of human fascination for thousands of years, dating back to 8th century Africa. The idea was originally associated with voodoo folklore, but since its origination, has been modernized and popularized with TV shows, movies, and other popular culture facets. With this popular fascination, however, comes concern

Statistical Analysis of fMRI Time-Series: A Critical Review of the GLM Approach.

Functional magnetic resonance imaging (fMRI) is one of the most widely used tools to study the neural underpinnings of human cognition. Standard analysis of fMRI data relies on a general linear model (GLM) approach to separate stimulus induced signals from noise. Crucially, this approach relies on a number of assumptions about the data which, for inferences to be valid, must be met. The current paper reviews the GLM approach to analysis of fMRI time-series, focusing in particular on the degree to which such data abides by the assumptions of the GLM framework, and on the methods that have been developed to correct for any violation of those assumptions. Rather than biasing estimates of effect size, the major consequence of non-conformity to the assumptions is to introduce bias into estimates of the variance, thus affecting test statistics, power, and false positive rates. Furthermore, this bias can have pervasive effects on both individual subject and group-level statistics, potentially yielding qualitatively different results across replications, especially after the thresholding procedures commonly used for inference-making

Forecast with judgment and models

This paper proposes a simple and model-consistent method for combining forecasts generated by structural micro-founded models and judgmental forecasts. The method also enables the judgmental forecasts to be interpreted through the lens of the model. We illustrate the proposed methodology with a real-time forecasting exercise, using a simple neo-Keynesian dynamic stochastic general equilibrium model and prediction from the Survey of Professional Forecastersforecasting, judgment, structural models, Kalman Filter, real time

Obstacle problem for Arithmetic Asian options

We prove existence, regularity and a Feynman-Ka\v{c} representation formula of the strong solution to the free boundary problem arising in the financial problem of the pricing of the American Asian option with arithmetic average

Families of locally separated Hamilton paths

We improve by an exponential factor the lower bound of K¨orner and Muzi for the cardinality of the largest family of Hamilton paths in a complete graph of n vertices in which the union of any two paths has maximum degree 4. The improvement is through an explicit construction while the previous bound was obtained by a greedy algorithm. We solve a similar problem for permutations up to an exponential factor