RinRuby: Accessing the R Interpreter from Pure Ruby

RinRuby is a Ruby library that integrates the R interpreter in Ruby, making R's statistical routines and graphics available within Ruby. The library consists of a single Ruby script that is simple to install and does not require any special compilation or installation of R. Since the library is 100% pure Ruby, it works on a variety of operating systems, Ruby implementations, and versions of R. RinRuby's methods are simple, making for readable code. This paper describes RinRuby usage, provides comprehensive documentation, gives several examples, and discusses RinRuby's implementation. The latest version of RinRuby can be found at the project website: http://rinruby.ddahl.org/.

Family Violence and Football: The Effect of Unexpected Emotional Cues on Violent Behavior

We study the link between family violence and the emotional cues associated with wins and losses by local professional football teams. We hypothesize that the risk of violence is affected by the 'gain-loss' utility of game outcomes around a rationally expected reference point. Our empirical analysis uses police reports of violent incidents on Sundays during the professional football season. Controlling for the pre-game point spread and the size of the local viewing audience, we find that upset losses (defeats when the home team was predicted to win by 4 or more points) lead to a 10 percent increase in the rate of at-home violence by men against their wives and girlfriends. In contrast, losses when the game was expected to be close have small and insignificant effects. Upset wins (when the home team was predicted to lose) also have little impact on violence, consistent with asymmetry in the gain-loss utility function. The rise in violence after an upset loss is concentrated in a narrow time window near the end of the game, and is larger for more important games. We find no evidence for reference point updating based on the halftime score.reference dependence, gain-loss utility, intimate partner violence

Integration of R and Scala Using rscala

The rscala software is a simple, two-way bridge between R and Scala that allows users to leverage the unique strengths of both languages in a single project. Scala classes can be instantiated from R and Scala methods can be called. Arbitrary Scala code can be executed on-the-fly from within R and callbacks to R are supported. R packages can be developed based on Scala. Conversely, rscala also enables R code to be embedded within a Scala application. The rscala package is available from the Comprehensive R Archive Network (CRAN) and has no dependencies beyond base R and the Scala standard library

RinRuby: Accessing the R Interpreter from Pure Ruby

RinRuby is a Ruby library that integrates the R interpreter in Ruby, making R's statistical routines and graphics available within Ruby. The library consists of a single Ruby script that is simple to install and does not require any special compilation or installation of R. Since the library is 100% pure Ruby, it works on a variety of operating systems, Ruby implementations, and versions of R. RinRuby's methods are simple, making for readable code. This paper describes RinRuby usage, provides comprehensive documentation, gives several examples, and discusses RinRuby's implementation. The latest version of RinRuby can be found at the project website: http://rinruby.ddahl.org/

Presenting signs and patient co-variables in Gaucher disease : outcome of the Gaucher Earlier Diagnosis Consensus (GED-C) Delphi initiative

© 2018 The Authors. Internal Medicine Journal by Wiley Publishing Asia Pty Ltd on behalf of Royal Australasian College of Physicians.Background: Gaucher disease (GD) presents with a range of signs and symptoms. Physicians can fail to recognise the early stages of GD owing to a lack of disease awareness, which can lead to significant diagnostic delays and sometimes irreversible but avoidable morbidities. Aim: The Gaucher Earlier Diagnosis Consensus (GED-C) initiative aimed to identify signs and co-variables considered most indicative of early type 1 and type 3 GD, to help non-specialists identify ‘at-risk’ patients who may benefit from diagnostic testing. Methods: An anonymous, three-round Delphi consensus process was deployed among a global panel of 22 specialists in GD (median experience 17.5 years, collectively managing almost 3000 patients). The rounds entailed data gathering, then importance ranking and establishment of consensus, using 5-point Likert scales and scoring thresholds defined a priori. Results: For type 1 disease, seven major signs (splenomegaly, thrombocytopenia, bone-related manifestations, anaemia, hyperferritinaemia, hepatomegaly and gammopathy) and two major co-variables (family history of GD and Ashkenazi-Jewish ancestry) were identified. For type 3 disease, nine major signs (splenomegaly, oculomotor disturbances, thrombocytopenia, epilepsy, anaemia, hepatomegaly, bone pain, motor disturbances and kyphosis) and one major co-variable (family history of GD) were identified. Lack of disease awareness, overlooking mild early signs and failure to consider GD as a diagnostic differential were considered major barriers to early diagnosis. Conclusion: The signs and co-variables identified in the GED-C initiative as potentially indicative of early GD will help to guide non-specialists and raise their index of suspicion in identifying patients potentially suitable for diagnostic testing for GD.Peer reviewedFinal Published versio

A DIRICHLET PROCESS MIXTURE OF HIDDEN MARKOV MODELS FOR PROTEIN STRUCTURE PREDICTION

By providing new insights into the distribution of a protein's torsion angles, recent statistical models for this data have pointed the way to more efficient methods for protein structure prediction. Most current approaches have concentrated on bivariate models at a single sequence position. There is, however, considerable value in simultaneously modeling angle pairs at multiple sequence positions in a protein. One area of application for such models is in structure prediction for the highly variable loop and turn regions. Such modeling is difficult due to the fact that the number of known protein structures available to estimate these torsion angle distributions is typically small. Furthermore, the data is "sparse" in that not all proteins have angle pairs at each sequence position. We propose a new semiparametric model for the joint distributions of angle pairs at multiple sequence positions. Our model accommodates sparse data by leveraging known information about the behavior of protein secondary structure. We demonstrate our technique by predicting the torsion angles in a loop from the globin fold family. Our results show that a template-based approach can now be successfully extended to modeling the notoriously difficult loop and turn regions.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS296 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Rigid Chiral Membranes

Statistical ensembles of flexible two-dimensional fluid membranes arise naturally in the description of many physical systems. Typically one encounters such systems in a regime of low tension but high stiffness against bending, which is just the opposite of the regime described by the Polyakov string. We study a class of couplings between membrane shape and in-plane order which break 3-space parity invariance. Remarkably there is only {\it one} such allowed coupling (up to boundary terms); this term will be present for any lipid bilayer composed of tilted chiral molecules. We calculate the renormalization-group behavior of this relevant coupling in a simplified model and show how thermal fluctuations effectively reduce it in the infrared.Comment: 11 pages, UPR-518T (This replaced version has fonts not used removed.