Data analysis with ordinal and interval dependent variables: examples from a study of real estate salespeople

This paper re-examines the problems of estimating the parameters of an underlying linear model using survey response data in which the dependent variables are in discrete categories of ascending order (ordinal, as distinct from numerical) or, where they are observed to fall into certain groups on a continuous scale (interval), where the actual values remain unobserved. An ordered probit model is discussed as an appropriate framework for statistical analysis for ordinal dependent variables. Next, a maximum likelihood estimator (MLE) derived from grouped data regression for interval dependent variable is discussed. Using LIMDEP, a packaged statistical program, survey data from an earlier manuscript are analyzed and the findings presented.

A Contextual-Bandit Approach to Personalized News Article Recommendation

Personalized web services strive to adapt their services (advertisements, news articles, etc) to individual users by making use of both content and user information. Despite a few recent advances, this problem remains challenging for at least two reasons. First, web service is featured with dynamically changing pools of content, rendering traditional collaborative filtering methods inapplicable. Second, the scale of most web services of practical interest calls for solutions that are both fast in learning and computation. In this work, we model personalized recommendation of news articles as a contextual bandit problem, a principled approach in which a learning algorithm sequentially selects articles to serve users based on contextual information about the users and articles, while simultaneously adapting its article-selection strategy based on user-click feedback to maximize total user clicks. The contributions of this work are three-fold. First, we propose a new, general contextual bandit algorithm that is computationally efficient and well motivated from learning theory. Second, we argue that any bandit algorithm can be reliably evaluated offline using previously recorded random traffic. Finally, using this offline evaluation method, we successfully applied our new algorithm to a Yahoo! Front Page Today Module dataset containing over 33 million events. Results showed a 12.5% click lift compared to a standard context-free bandit algorithm, and the advantage becomes even greater when data gets more scarce.Comment: 10 pages, 5 figure

Modelling the thermal transport of a thawing permafrost plateau

Permafrost covers approximately 24% of the Northern Hemisphere and is in a state of decay which has large implications. To characterize the processes involved in the transitional period of permafrost decay, a three-dimensional finite element numerical model is developed. The model is based on the Scotty Creek Research Basin in the Northwest Territories, Canada (61°18\u27N, 121°18\u27W). FEFLOW groundwater flow and heat transport modelling software is used in conjunction with the piFreeze plug-in, to account for phase changes between ice and water. As transiently simulating actual permafrost evolution would require 100’s of years of climate variations over an evolving landscape, whose geomorphic features are unknown, a steady-state developed permafrost bulb is used as an initial condition for a transient model run. The steady-state developed permafrost was generated by the application of freezing surface temperatures. The transient approach applies daily climatic data over the current plateau; the Simultaneous Heat and Water model (SHAW) is used to calculate ground temperatures and infiltration rates. It was found that a transient model with “unsteady-state” applied temperatures that include an unfrozen layer between the supra-permafrost table and ground surface yields better results than with steady-state permafrost initial conditions. Modelling permafrost will allow for the testing of remedial measures, such as mulching and borehole heat exchangers, to stabilize permafrost in high value infrastructure environments

Photometric Variability in Earthshine Observations

The identification of an extrasolar planet as Earth-like will depend on the detection of atmospheric signatures or surface non-uniformities. In this paper we present spatially unresolved flux light curves of Earth for the purpose of studying a prototype extrasolar terrestrial planet. Our monitoring of the photometric variability of earthshine revealed changes of up to 23 % per hour in the brightness of Earth's scattered light at around 600 nm, due to the removal of specular reflection from the view of the Moon. This variability is accompanied by reddening of the spectrum, and results from a change in surface properties across the continental boundary between the Indian Ocean and Africa's east coast. Our results based on earthshine monitoring indicate that specular reflection should provide a useful tool in determining the presence of liquid water on extrasolar planets via photometric observations.Comment: To appear in Astrobiology 9(3). 17 pages, 3 figures, 1 tabl

Volume-preserving normal forms of Hopf-zero singularity

A practical method is described for computing the unique generator of the algebra of first integrals associated with a large class of Hopf-zero singularity. The set of all volume-preserving classical normal forms of this singularity is introduced via a Lie algebra description. This is a maximal vector space of classical normal forms with first integral; this is whence our approach works. Systems with a non-zero condition on their quadratic parts are considered. The algebra of all first integrals for any such system has a unique (modulo scalar multiplication) generator. The infinite level volume-preserving parametric normal forms of any non-degenerate perturbation within the Lie algebra of any such system is computed, where it can have rich dynamics. The associated unique generator of the algebra of first integrals are derived. The symmetry group of the infinite level normal forms are also discussed. Some necessary formulas are derived and applied to appropriately modified R\"{o}ssler and generalized Kuramoto--Sivashinsky equations to demonstrate the applicability of our theoretical results. An approach (introduced by Iooss and Lombardi) is applied to find an optimal truncation for the first level normal forms of these examples with exponentially small remainders. The numerically suggested radius of convergence (for the first integral) associated with a hypernormalization step is discussed for the truncated first level normal forms of the examples. This is achieved by an efficient implementation of the results using Maple

Structure of MnO nanoparticles embedded into channel-type matrices

X-ray diffraction experiments were performed on MnO confined in mesoporous silica SBA-15 and MCM-41 matrices with different channel diameters. The measured patterns were analyzed by profile analysis and compared to numerical simulations of the diffraction from confined nanoparticles. From the lineshape and the specific shift of the diffraction reflections it was shown that the embedded objects form ribbon-like structures in the SBA-15 matrices with channels diameters of 47-87 {\AA}, and nanowire-like structures in the MCM-41 matrices with channels diameters of 24-35 {\AA}. In the latter case the confined nanoparticles appear to be narrower than the channel diameters. The physical reasons for the two different shapes of the confined nanoparticles are discussed.Comment: 8 pages, including 9 postscript figures, uses revtex4.cl