Sex Offender Treatment Program: Preliminary Description

This report provides a summary of the history of sex offender treatment in Alaska, including the current status of treatment programs offered by the Alaska Department of Corrections, a review of literature on sex offender treatment and recidivism issues, and a summary of the descriptive characteristics of individuals who came in contact with the Hiland Mountain Correctional Center from January 1987 to March 1993.Alaska Department of CorrectionsIntroduction / Sex Offender Treatment in Alaska / Literature Review / Methodology / Results / Conclusion and Recommendations / Bibliograph

Statistical Semantic Classification of Crisis Information

The rise of social media as an information channel during crisis has become key to community response. However, existing crisis awareness applications, often struggle to identify relevant information among the high volume of data that is generated over social platforms. A wide range of statistical features and machine learning methods have been researched in recent years to automatically classify this information. In this paper we aim to complement previous studies by exploring the use of semantics as additional features to identify relevant crisis in- formation. Our assumption is that entities and concepts tend to have a more consistent correlation with relevant and irrelevant information, and therefore can enhance the discrimination power of classifiers. Our results, so far, show that some classification improvements can be obtained when using semantic features, reaching +2.51% when the classifier is applied to a new crisis event (i.e., not in training set)

Abandon Statistical Significance

We discuss problems the null hypothesis significance testing (NHST) paradigm poses for replication and more broadly in the biomedical and social sciences as well as how these problems remain unresolved by proposals involving modified p-value thresholds, confidence intervals, and Bayes factors. We then discuss our own proposal, which is to abandon statistical significance. We recommend dropping the NHST paradigm--and the p-value thresholds intrinsic to it--as the default statistical paradigm for research, publication, and discovery in the biomedical and social sciences. Specifically, we propose that the p-value be demoted from its threshold screening role and instead, treated continuously, be considered along with currently subordinate factors (e.g., related prior evidence, plausibility of mechanism, study design and data quality, real world costs and benefits, novelty of finding, and other factors that vary by research domain) as just one among many pieces of evidence. We have no desire to "ban" p-values or other purely statistical measures. Rather, we believe that such measures should not be thresholded and that, thresholded or not, they should not take priority over the currently subordinate factors. We also argue that it seldom makes sense to calibrate evidence as a function of p-values or other purely statistical measures. We offer recommendations for how our proposal can be implemented in the scientific publication process as well as in statistical decision making more broadly

Bayesian Statistical Pragmatism

Discussion of "Statistical Inference: The Big Picture" by R. E. Kass [arXiv:1106.2895]Comment: Published in at http://dx.doi.org/10.1214/11-STS337C the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Statistical quantum operation

A generic unital positive operator-valued measure (POVM), which transforms a given stationary pure state to an arbitrary statistical state with perfect decoherence, is presented. This allows one to operationally realize thermalization as a special case. The loss of information due to randomness generated by the operation is discussed by evaluating the entropy. Thermalization of the bipartite spin-1/2 system is discussed as an illustrative example.Comment: 10 pages, no figure

Statistical Risk Models

We give complete algorithms and source code for constructing statistical risk models, including methods for fixing the number of risk factors. One such method is based on eRank (effective rank) and yields results similar to (and further validates) the method set forth in an earlier paper by one of us. We also give a complete algorithm and source code for computing eigenvectors and eigenvalues of a sample covariance matrix which requires i) no costly iterations and ii) the number of operations linear in the number of returns. The presentation is intended to be pedagogical and oriented toward practical applications.Comment: 44 pages; a trivial typo corrected, references updated; to appear in The Journal of Investment Strategies. arXiv admin note: text overlap with arXiv:1602.04902, arXiv:1508.04883, arXiv:1604.0874

Equilibrium Statistical Mechanics

An introductory review of Classical Statistical MechanicsComment: 56 page