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At least 613 records · Page 34Linked to original sources

arXiv2020

A New ECDF Two-Sample Test Statistic

Empirical cumulative distribution functions (ECDFs) have been used to test the hypothesis that two samples come from the same distribution since the seminal contribution by Kolmogorov and Smirnov. This paper describes a statistic which is usable under the same conditions as Kolmogorov-Smirnov, but provides more power than other extant tests in that vein. I demonstrate a valid (conservative) procedure for producing finite-sample p-values. I outline the close relationship between this statistic and its two main predecessors. I also provide a public R package (CRAN: twosamples [2018]) implementing the testing procedure in $O(N\log(N))$ time with $O(N)$ memory. Using the package's functions, I perform several simulation studies showing the power improvements.

stat.ME↗

arXiv2020

A method to find an efficient and robust sampling strategy under model uncertainty

We consider the problem of deciding on sampling strategy, in particular sampling design. We propose a risk measure, whose minimizing value guides the choice. The method makes use of a superpopulation model and takes into account uncertainty about its parameters. The method is illustrated with a real dataset, yielding satisfactory results. As a baseline, we use the strategy that couples probability proportional-to-size sampling with the difference estimator, as it is known to be optimal when the superpopulation model is fully known. We show that, even under moderate misspecifications of the model, this strategy is not robust and can be outperformed by some alternatives

stat.ME↗

arXiv2020

P-Values in a Post-Truth World

The role of statisticians in society is to provide tools, techniques, and guidance with regards to how much to trust data. This role is increasingly more important with more data and more misinformation than ever before. The American Statistical Association recently released two statements on p-values, and provided four guiding principles. We evaluate their claims using these principles and find that they failed to adhere to them. In this age of distrust, we have an opportunity to be role models of trustworthiness, and responsibility to take it.

physics.soc-ph↗

arXiv2020

A Bayesian Redesign of the First Probability/Statistics Course

The traditional calculus-based introduction to statistical inference consists of a semester of probability followed by a semester of frequentist inference. Cobb (2015) challenges the statistical education community to rethink the undergraduate statistics curriculum. In particular, he suggests that we should focus on two goals: making fundamental concepts accessible and minimizing prerequisites to research. Using five underlying principles of Cobb, we describe a new calculus-based introduction to statistics based on simulation-based Bayesian computation.

stat.OT↗

arXiv2020

A Bivariate Compound Dynamic Contagion Process for Cyber Insurance

As corporates and governments become more digital, they become vulnerable to various forms of cyber attack. Cyber insurance products have been used as risk management tools, yet their pricing does not reflect actual risk, including that of multiple, catastrophic and contagious losses. For the modelling of aggregate losses from cyber events, in this paper we introduce a bivariate compound dynamic contagion process, where the bivariate dynamic contagion process is a point process that includes both externally excited joint jumps, which are distributed according to a shot noise Cox process and two separate self-excited jumps, which are distributed according to the branching structure of a Hawkes process with an exponential fertility rate, respectively. We analyse the theoretical distributional properties for these processes systematically, based on the piecewise deterministic Markov process developed by Davis (1984) and the univariate dynamic contagion process theory developed by Dassios and Zhao (2011). The analytic expression of the Laplace transform of the compound process and its moments are presented, which have the potential to be applicable to a variety of problems in credit, insurance, market and other operational risks. As an application of this process, we provide insurance premium calculations based on its moments. Numerical examples show that this compound process can be used for the modelling of aggregate losses from cyber events. We also provide the simulation algorithm for statistical analysis, further business applications and research.

q-fin.RM↗

arXiv2026

Measurement error and reliability from a different perspective: Reliability of decision functions and the sum score

We propose an alternative framework for measurement error that allows us to determine reliability at the level of the decision, such as the decision to pass or fail. This framework makes it possible to answer the question which properties of a decision function are relevant to make decisions. The mechanism is relatively simple for dichotomous items: The response to any item has probability $\tfrac{1}{2}(1-ρ)$, with $ρ\in [-1,1]$, to be different from the original response. We show that this framework satisfies the classical axioms (those of Lord and Novick) and can therefore be considered as being aligned with classical test theory. We also show some relations to modern test theory and its connections to graphs. We then connect the idea of reliability at the level of the decision to the idea of how many of the (two-response) items are required to be flipped to change the decision; this is referred to as stability. Finally, we argue that from this perspective the best decision function (with respect to a set of properties including stability) is a weighted sum score with threshold value.

stat.ME↗

arXiv2021

The Effects of Vacant Lot Greening and the Impact of Land Use and Business Presence on Crime

We examine the effect of the Philadelphia LandCare (PLC) vacant lot greening initiative on crime and the extent to which surrounding land uses and business types moderate this intervention. We rely on a propensity score matching analysis to account for substantial differences in demographic, economic, land use, and business characteristics between greened and ungreened vacant lots. We estimate larger and more significant crime reductions around vacant lots that are greened in our matched pairs analysis compared to unmatched analyses. The effects of vacant lot greening on crime are larger in areas with high residential and low commercial land use and are moderated by the presence of different types of nearby businesses.

stat.OT↗

arXiv2020

Dynamics of ternary statistical experiments with equilibrium state

We study the scenarios of the dynamics of ternary statistical experiments, modeled employing difference equations. The important features are a balance condition and the existence of a steady-state (equilibrium). We give a classification of scenarios of the model evolution which are significantly different between them, depending on the domain of the values of the model basic parameters.

stat.OT↗

arXiv2020

Incertitudes et mesures

Educational guide focused on the statistical treatment of measurement uncertainties. The conditions of application of current practices are detailed and precised: mean values, central limit theorem, linear regression. The last two chapters are devoted to an introduction to the Bayesian inference and a series of application cases: machine failure date, elimination of a background noise, linear adjustment with elimination of outliers.

stat.OT↗

arXiv2020

The rule of conditional probability is valid in quantum theory [Comment on Gelman & Yao's "Holes in Bayesian Statistics"]

In a recent manuscript, Gelman & Yao (2020) claim that "the usual rules of conditional probability fail in the quantum realm" and that "probability theory isn't true (quantum physics)" and purport to support these statements with the example of a quantum double-slit experiment. The present comment recalls some relevant literature in quantum theory and shows that (i) Gelman & Yao's statements are false; in fact, the quantum example confirms the rules of probability theory; (ii) the particular inequality found in the quantum example can be shown to appear also in very non-quantum examples, such as drawing from an urn; thus there is nothing peculiar to quantum theory in this matter. A couple of wrong or imprecise statements about quantum theory in the cited manuscript are also corrected.

stat.OT↗

arXiv2022

Social Learning in Non-Stationary Environments

Potential buyers of a product or service, before making their decisions, tend to read reviews written by previous consumers. We consider Bayesian consumers with heterogeneous preferences, who sequentially decide whether to buy an item of unknown quality, based on previous buyers' reviews. The quality is multi-dimensional and may occasionally vary over time; the reviews are also multi-dimensional. In the simple uni-dimensional and static setting, beliefs about the quality are known to converge to its true value. Our paper extends this result in several ways. First, a multi-dimensional quality is considered, second, rates of convergence are provided, third, a dynamical Markovian model with varying quality is studied. In this dynamical setting the cost of learning is shown to be small.

math.OC↗

arXiv2020

Strategic Evaluation in Optimizing the Internal Supply Chain Using TOPSIS: Evidence In A Coil Winding Machine Manufacturer

Most of the manufacturing firm aims to optimize their Supply Chain in terms of improved profitability of its products through value Addition. This study takes a critical look into the factors that affect the Performance of internal supply chain with respect to specific criteria. Accordingly, ranking these factors to get the critical dimensions of supply chain performance in the manufacturing industry. A semi-structured interview with the pre-defined set of questions used to collect the responses from decision makers of the firm. Multi criteria decision-making tool called TOPSIS is used to evaluate the responses and rank the factors. The results of this indicate that supplier relationship and inventory planning were most principal factors positively influencing on-time delivery of the product, production flexibility, cost savings, additional costs. This study helps to identify and optimize the process parameters using objective and subjective evaluation approach. The combined influence of the thought process of the manager to optimize the internal supply chain is extracted in this work.

cs.AI↗

arXiv2020

Reproducible Research: A Retrospective

Rapid advances in computing technology over the past few decades have spurred two extraordinary phenomena in science: large-scale and high-throughput data collection coupled with the creation and implementation of complex statistical algorithms for data analysis. Together, these two phenomena have brought about tremendous advances in scientific discovery but have also raised two serious concerns, one relatively new and one quite familiar. The complexity of modern data analyses raises questions about the reproducibility of the analyses, meaning the ability of independent analysts to re-create the results claimed by the original authors using the original data and analysis techniques. While seemingly a straightforward concept, reproducibility of analyses is typically thwarted by the lack of availability of the data and computer code that were used in the analyses. A much more general concern is the replicability of scientific findings, which concerns the frequency with which scientific claims are confirmed by completely independent investigations. While the concepts of reproduciblity and replicability are related, it is worth noting that they are focused on quite different goals and address different aspects of scientific progress. In this review, we will discuss the origins of reproducible research, characterize the current status of reproduciblity in public health research, and connect reproduciblity to current concerns about replicability of scientific findings. Finally, we describe a path forward for improving both the reproducibility and replicability of public health research in the future.

stat.OT↗

arXiv2020

On the Programmatic Generation of Reproducible Documents

Reproducible document standards, like R Markdown, facilitate the programmatic creation of documents whose content is itself programmatically generated. While these documents are generally not complete in the sense that they will not include prose content, generated by an author to provide context, a narrative, etc., programmatic generation can provide substantial efficiencies for structuring and constructing documents. This paper explores the programmatic generation of reproducible by distinguishing components than can be created by computational means from those requiring human-generated prose, providing guidelines for the generation of these documents, and identifying a use case in clinical trial reporting. These concepts and use case are illustrated through the listdown package for the R programming environment, which is is currently available on the Comprehensive R Archive Network (CRAN).

cs.DL↗

arXiv2020

Asymmetry approach to study for chemotherapy treatment and devices failure times data using modified Power function distribution with some modified estimators

In order to improve the already existing models that are used extensively in bio sciences and applied sciences research, a new class of Weighted Power function distribution (WPFD) has been proposed with its various properties and different modifications to be more applicable in real life. We have provided the mathematical derivations for the new distribution including moments, incomplete moments, conditional moments, inverse moments, mean residual function, vitality function, order statistics, mills ratio, information function, Shannon entropy, Bonferroni and Lorenz curves and quantile function. We have also characterized the WPFD, based on doubly truncated mean. The aim of the study is to increase the application of the Power function distribution. The main feature of the proposed distribution is that there is no induction of parameters as compare to the other generalization of the distributions, which are complexed having many parameters. We have used R programming to estimate the parameters of the new class of WPFD using Maximum Likelihood Method (MLM), Percentile Estimators (P.E) and their modified estimators. After analyzing the data, we conclude that the proposed model WPFD performs better in the data sets while compared to different competitor models.

stat.OT↗

arXiv2020

On the sum of ordered spacings

We provide the analytic forms of the distributions for the sum of ordered spacings. We do this both for the case where the boundaries are included in the calculation of the spacings and the case where they are excluded. Both the probability densities as well as their cumulatives are provided. These results will have useful applications in the physical sciences and possibly elsewhere.

math.ST↗

arXiv2020

Sulla decifratura di Enigma -- Come un reverendo del XVIII secolo contribuì alla sconfitta degli U-boot tedeschi durante la Seconda Guerra Mondiale

This article, written in Italian language, explores the contribution given by Bayes' rule and by subjective probability in the work at Bletchley Park towards cracking Enigma cyphered messages during WWII. -- In questo articolo, scritto in Italiano, esploriamo il contributo dato dal teorema di Bayes e dalle idee della probabilità soggettiva nel lavoro compiuto a Bletchley Park che ha portato a decifrare i messaggi cifrati con macchine Enigma durante la Seconda Guerra Mondiale.

cs.GL↗

arXiv2020

Opening practice: supporting Reproducibility and Critical spatial data science

This paper reflects on a number of trends towards a more open and reproducible approach to geographic and spatial data science over recent years. In particular it considers trends towards Big Data, and the impacts this is having on spatial data analysis and modelling. It identifies a turn in academia towards coding as a core analytic tool, and away from proprietary software tools offering 'black boxes' where the internal workings of the analysis are not revealed. It is argued that this closed form software is problematic, and considers a number of ways in which issues identified in spatial data analysis (such as the MAUP) could be overlooked when working with closed tools, leading to problems of interpretation and possibly inappropriate actions and policies based on these. In addition, this paper and considers the role that reproducible and open spatial science may play in such an approach, taking into account the issues raised. It highlights the dangers of failing to account for the geographical properties of data, now that all data are spatial (they are collected somewhere), the problems of a desire for n=all observations in data science and it identifies the need for a critical approach. This is one in which openness, transparency, sharing and reproducibility provide a mantra for defensible and robust spatial data science.

stat.OT↗