Development of methods for determining the coordinates of firing positions of roving mortars by a network of counter-battery radars

The mathematical formulation of the problem of determining the coordinates of targets in the network of counter-battery radars is formulated. It has been established that the problem of estimating the coordinates of targets in the network of counter-battery radars for an excessive number of estimates of primary coordinates should be considered as a statistical problem. The method for determining the coordinates of the firing positions of roving mortars has been improved, in which, in contrast to the known ones, the coordinates of targets on the flight trajectory are coordinated with space and time and the information is processed by a network of counter-battery radars. The developed simulation mathematical model for determining the coordinates of the firing positions of roving mortars by a network of counter-battery radars. Simulation modeling of the method for determining the coordinates of the firing positions of roving mortars by a network of counter-battery radars has been carried out. It has been established that the use of a network of radars makes it possible to increase the accuracy of determining the coordinates of the firing means on average from 23 % to 71 %, depending on the number of counter-battery radars in the network. It has also been found that the appropriate number of counter-battery warfare radars in the network is three or four. A further increase in the number of counter-battery warfare radars in the network does not lead to a significant increase in the accuracy of determining the coordinates of artillery and mortar firing positions. In carrying out further research, it is necessary to develop a method for the spatial separation of elements of a group of targets and interfering objects by a network of counter-battery warfare radars

Dominance is necessary to explain human status hierarchies [exposition of three concerns]

Durkee et al. (2020) conducted a cross-cultural investigation of people’s beliefs about how traits, behaviors, and practices that enhance an individual’s perceived ability to generate benefits (prestige) or inflict costs (dominance) promote perceived social status in humans. In this document, we (a) identify multicollinearity in the authors’ statistical analyses and explain how this statistical problem renders their results inconclusive as to how benefit-delivery and cost-infliction contribute to status allocation; (b) outline flaws in the authors’ operationalization and measures of social status, and discuss how they bias results toward benefit-delivery and underestimate any effect of cost-infliction; and (c) discuss a broader problem with the critical assumption underlying Durkee et al.’s approach: people’s subjective beliefs about what determines status do not serve as sufficient evidence for determining how status asymmetries are actually established in real life. Together, these three major issues severely undermine the authors’ conclusion that there is little evidence for dominance. In closing, we briefly survey the broader empirical record on actual status relations among real people (rather than people’s beliefs about what leads to status), conducted both in the lab and in naturalistic settings; these studies consistently yield opposite conclusions to Durkee et al. and demonstrate that both prestige and dominance govern human status hierarchies.

Dominance is necessary to explain human status hierarchies - Extended online version and supplemental

Durkee et al. (2020) conducted a cross-cultural investigation of people’s beliefs about how traits, behaviors, and practices that enhance an individual’s perceived ability to generate benefits (prestige) or inflict costs (dominance) promote perceived social status in humans. In this online extended version of our letter, we identify multicollinearity in the authors’ statistical analyses and explain how this statistical problem renders their results inconclusive as to how benefit-delivery and cost-infliction contribute to status allocation. Moreover, we briefly survey the broader empirical record on actual status relations among real people (rather than people’s beliefs about what leads to status), conducted both in the lab and in naturalistic settings; these studies consistently yield opposite conclusions to Durkee et al. and demonstrate that both prestige and dominance govern human status hierarchies.

If Mathematical Psychology Did Not Exist We Might Need to Invent It: A Comment on Theory Building in Psychology

It is commonplace, when discussing the subject of psychological theory, to write articles from the assumption that psychology differs from the physical sciences in that we have no theories that would support cumulative, incremental science. In this brief article I discuss one counterexample: Shepard’s law of generalization and the various Bayesian extensions that it inspired over the past 3 decades. Using Shepard’s law as a running example, I argue that psychological theory building is not a statistical problem, mathematical formalism is beneficial to theory, measurement and theory have a complex relationship, rewriting old theory can yield new insights, and theory growth can drive empirical work. Although I generally suggest that the tools of mathematical psychology are valuable to psychological theorists, I also comment on some limitations to this approach.

To Count the Absent (or the Problem of the Total Number of Genoese Merchants in Byzantium)

The author develops a mathematical-statistical approach to the problem of estimating the size of Genoese medieval population in Byzantium. The data source is notarial acts covering commercial partnerships, freightage, wills, purchase and sale of houses, goods and people drawn up in the Genoese colony of Constantinople at the end of the 13th century. The will form has a fairly uniform structure. In addition to the mandatory record of names of the contracting parties and witnesses of the transaction, it may also register names of the third parties. Thus, these data on the clientele of Genoese notaries represent a dataset which may indirectly indicate the size of the entire trading Genoese community of Byzantium. This approach is based on a constructed formalized model that describes the behavior of merchants when visiting and concluding a transaction attested by a notary. This makes it possible to pass in a natural way from the initial to the statistical problem of estimating the size of a finite aggregate and use this mathematical theory for its calculation. In this case, the author applies the approach associated with the use of the maximum likelihood function that is a novelty. The resulting formula allows (with a certain degree of probability) one to estimate the required size of the Genoese population. It is interesting that this estimate, on the whole, coincides with the result of A.L. Ponomarev obtained earlier for the same problem using Zipf's empirical law.

Revised findings for "Procedural justice training reduces police use of force and complaints against officers"

Wood et al. (2020) studied the rollout of a procedural justice training program in the Chicago Police Department and found large and statistically significant impacts on complaints and sustained complaints against police officers and police use of force. This document describes a subtle statistical problem that led the magnitude of those estimates to be inflated. We then re-analyze the data using a methodology that corrects for this problem. The re-analysis provides less strong conclusions about the effectiveness of the training than the original study: although the point estimates for most outcomes and specifications are negative and of a meaningful magnitude, the confidence intervals typically include zero or very small effects. On the whole, we interpret the data as providing suggestive evidence that procedural justice training reduced the use of force, but no statistically significant evidence for a reduction in complaints or sustained complaints.

Prediction of wine sensorial quality: a classification problem

When dealing with a wine, it is of interest to be able to predict its quality based on chemical and/or sensory variables. There is no agreement on what wine quality means, or how it should be assessed and it is often viewed in intrinsic (physicochemical, sensory) or extrinsic (price, prestige, context) terms (Jackson, 2017). In this paper, the wine quality was evaluated by experienced judges who scored the wine on the base of a 0-10 scale, with 0 meaning very bad and 10 excellent, so, the resulting variable was categorical. The models applied to predict this variable provide the prediction of the occurrence probabilities of each of its categories. Nevertheless, jointly with this probabilities’ record, the practitioners need the predicted value (category) of the variable, so the statistical problem to be covered refers to the way in which this probabilities’ record is transformed into a single value. In this paper we compare the predictive performances of the default method (Bayes Classifier - BC), which assigns a unit to the most likely category, and other two methods (Maximum Difference Classifier and Maximum Ratio Classifier). The BC is the optimal criterion if one is interested in the accuracy of the classification, but, given that it favors the prevalent category most, when there is not a category of interest, it cannot be the best choice. The data under study concern the quality of the red variant of the Portuguese "Vinho Verde" wine (Cortez et al., 2009), measured on a 0-10 scale. Nevertheless, only 6 scores were used, with 2 scores with a very few number of observations, so this is the right context for predictive performance comparisons. In the study, we investigated different merging of categories and we used 11 explanatory variables to estimate the probabilities’ record of the wine quality variable.

Intelligent Constructing Exact Tolerance Limits for Prediction of Future Outcomes Under Parametric Uncertainty

The problem of constructing one-sided exact statistical tolerance limits on the kth order statistic in a future sample of m observations from a distribution of log-location-scale family on the basis of an observed sample from the same distribution is considered. The new technique proposed here emphasizes pivotal quantities relevant for obtaining tolerance factors and is applicable whenever the statistical problem is invariant under a group of transformations that acts transitively on the parameter space. The exact tolerance limits on order statistics associated with sampling from underlying distributions can be found easily and quickly making tables, simulation, Monte Carlo estimated percentiles, special computer programs, and approximation unnecessary. Finally, numerical examples are given, where the tolerance limits obtained by using the known methods are compared with the results obtained through the proposed novel technique, which is illustrated in terms of the extreme-value and two-parameter Weibull distributions.