Latest in stat.ot
total 607took 0.28s
Statistical witchhunts: Science, justice & the p-value crisisApr 11 2019We provide accessible insight into the current 'replication crisis' in 'statistical science', by revisiting the old metaphor of 'court trial as hypothesis test'. Inter alia, we define and diagnose harmful statistical witch-hunting both in justice and ... More Statistical testing in a Linear Probability SpaceApr 02 2019Imagine that you could calculate of posttest probabilities, i.e. Bayes theorem with simple addition. This is possible if we stop thinking of probabilities as ranging from 0 to 1.0. There is a naturally occurring linear probability space when data are ... More Data-driven discovery of coordinates and governing equationsMar 29 2019The discovery of governing equations from scientific data has the potential to transform data-rich fields that lack well-characterized quantitative descriptions. Advances in sparse regression are currently enabling the tractable identification of both ... More Data-driven discovery of coordinates and governing equationsMar 29 2019Apr 04 2019The discovery of governing equations from scientific data has the potential to transform data-rich fields that lack well-characterized quantitative descriptions. Advances in sparse regression are currently enabling the tractable identification of both ... More GraSPy: Graph Statistics in PythonMar 29 2019We introduce GraSPy, a Python library devoted to statistical inference, machine learning, and visualization of random graphs and graph populations. This package provides flexible and easy-to-use algorithms for analyzing and understanding graphs with a ... More Deterministic bootstrapping for a class of bootstrap methodsMar 26 2019Apr 09 2019An algorithm is described that enables efficient deterministic approximate computation of the bootstrap distribution for any linear bootstrap method $T_n^*$, alleviating the need for repeated resampling from observations (resp. input-derived data). In ... More Deterministic bootstrapping for a class of bootstrap methodsMar 26 2019An algorithm is described that enables efficient deterministic approximate computation of the bootstrap distribution for any linear bootstrap method $T_n^*$, alleviating the need for repeated resampling from observations (resp. input-derived data). In ... More Revising the Wilks Scoring System for pro RAW PowerliftingMar 22 2019Purpose: In powerlifting the total result is highly dependent on the athletes bodyweight. Powerlifting is divided to equipped and RAW types. Pro RAW powerlifting competitions use the Wilks scoring system to compare and rank powerlifting results across ... More Tutorial: Deriving The Efficient Influence Curve for Large ModelsMar 05 2019Mar 09 2019This paper aims to provide a tutorial for upper level undergraduate and graduate students in statistics, biostatistics and epidemiology on deriving influence functions for non-parametric and semi-parametric models. The author will build on previously ... More Comparison of plotting system outputs in beginner analystsMar 03 2019The R programming language is built on an ecosystem of packages, some that allow analysts to accomplish the same tasks. For example, there are at least two clear workflows for creating data visualizations in R: using the base graphics package (referred ... More Bounds on Bayes Factors for Binomial A/B TestingFeb 28 2019Bayes factors, in many cases, have been proven to bridge the classic -value based significance testing and bayesian analysis of posterior odds. This paper discusses this phenomena within the binomial A/B testing setup (applicable for example to conversion ... More A note on Fibonacci Sequences of Random VariablesFeb 26 2019The focus of this paper is the random sequences in the form $\{X_{0},X_{1},$ $X_{n}=X_{n-2}+X_{n-1},n=2,3,..\dot{\}},$ referred to as Fibonacci Random Sequence (FRS). The initial random variables $X_{0}$ and $X_{1}$ are assumed to be absolutely continuous ... More A Combinatorial Approach to Causal InferenceFeb 18 2019The objective of causal inference is to learn the network of causal relationships holding between a system of variables from the correlations that these variables exhibit; a sub-problem of which is to certify whether or not a given causal hypothesis is ... More Synthesis of High-Resolution Load Profiles with Minimal DataFeb 15 2019For the estimation of a new energy supply system it is an important to have high-resolution energy load profile. Such a profile is in general either not present or very costly to obtain. We will therefore present a method which synthesizes load profiles ... More Optimal BIBD-extended designsFeb 12 2019Balanced incomplete block designs (BIBDs) are a class of designs with v treatments and b blocks of size k that are optimal with regards to a wide range of optimality criteria, but it is not clear which designs to choose for combinations of v, b and k ... More Characterization of Sine- Skewed von Mises DistributionFeb 07 2019The von Mises distribution is one of the most important distribution in statistics to deal with circular data. In this paper we will consider some basic properties and characterizations of the sine skewed von Mises distribution. Organic Fiducial InferenceJan 23 2019A substantial generalization is put forward of the theory of subjective fiducial inference as it was outlined in earlier papers. In particular, this theory is extended to deal with cases where the data are discrete or categorical rather than continuous, ... More Fitting A Mixture Distribution to Data: TutorialJan 20 2019This paper is a step-by-step tutorial for fitting a mixture distribution to data. It merely assumes the reader has the background of calculus and linear algebra. Other required background is briefly reviewed before explaining the main algorithm. In explaining ... More Custodes: Auditable Hypothesis TestingJan 19 2019We present Custodes: a new approach to solving the complex issue of preventing "p-hacking" in scientific studies. The novel protocol provides a concrete and publicly auditable method for controlling false-discoveries and eliminates any potential for data ... More Systemic Risk: Conditional Distortion Risk MeasuresJan 15 2019Jan 28 2019In this paper, we introduce the rich classes of conditional distortion (CoD) risk measures and distortion risk contribution ($\Delta$CoD) measures as measures of systemic risk and analyze their properties and representations. The classes include the well-known ... More Approaching Ethical Guidelines for Data ScientistsJan 14 2019The goal of this article is to inspire data scientists to participate in the debate on the impact that their professional work has on society, and to become active in public debates on the digital world as data science professionals. How do ethical principles ... More Projective Decomposition and Matrix Equivalence up to ScaleJan 04 2019A data matrix may be seen simply as a means of organizing observations into rows ( e.g., by measured object) and into columns ( e.g., by measured variable) so that the observations can be analyzed with mathematical tools. As a mathematical object, a matrix ... More Generalized Score Matching for Non-Negative DataDec 26 2018A common challenge in estimating parameters of probability density functions is the intractability of the normalizing constant. While in such cases maximum likelihood estimation may be implemented using numerical integration, the approach becomes computationally ... More Pragmatic hypotheses in the evolution of scienceDec 25 2018This paper introduces pragmatic hypotheses and relates this concept to the spiral of scientific evolution. Previous works determined a characterization of logically consistent statistical hypothesis tests and showed that the modal operators obtained from ... More Application of Robust Estimators in Shewhart S-ChartsDec 24 2018Maintaining the quality of manufactured products at a desired level is known to increase customer satisfaction and profitability. Shewhart control chart is the most widely used in statistical process control (SPC) technique to monitor the quality of products ... More On a flexible construction of a negative binomial modelDec 18 2018This work presents a construction of stationary Markov models with negative binomial marginal distributions. The proposal is novel in that a simple form of the corresponding transition probabilities is available, thus revealing uninvolved simulation and ... More Multiple testing with persistent homologyDec 16 2018We propose a general null model for persistent homology barcodes from a point cloud, to test for example acyclicity in simplicial complexes generated from point clouds. One advantage of the null model we propose is efficiency in generating a null model ... More Key Factor Not to Drop Out is to Attend the LectureDec 12 2018In addition to the learning check testing results performed at each lectures, we have extended the factors to find the key dropping out factors. Among them are, the number of successes in the learning check testing, the number of attendances to the follow-up ... More On some properties of the new Sine-skewed Cardioid DistributionNov 25 2018The new Sine Skewed Cardioid (ssc) distribution been just introduced and characterized by Ahsanullah (2018). Here, we study the asymptotic properties of its tails by determining its extreme value domain, the characteristic function, the moments and likelihood ... More Essential Collaboration Skills: The ASCCR Frame for CollaborationNov 08 2018Mar 28 2019Statistics and data science are collaborative disciplines that typically require practitioners to interact with many different people or groups. Consequently, collaboration skills are part of the personal and professional skills essential for success ... More Using GitHub Classroom To Teach StatisticsNov 05 2018Git and GitHub are common tools for keeping track of multiple versions of data analytic content, which allow for more than one person to simultaneously work on a project. GitHub Classroom aims to provide a way for students to work on and submit their ... More On a generalized form of subjective probabilityOct 25 2018This paper is motivated by the questions of how to give the concept of probability an adequate real-world meaning, and how to explain a certain type of phenomenon that can be found, for instance, in Ellsberg's paradox. It attempts to answer these questions ... More I can see clearly now: reinterpreting statistical significanceOct 15 2018Null hypothesis significance testing remains popular despite decades of concern about misuse and misinterpretation. We believe that much of the problem is due to language: significance testing has little to do with other meanings of the word "significance". ... More Canadian Crime Rates in the Penalty BoxOct 11 2018Oct 26 2018Over the 1962-2016 period, the Canadian violent crime rate has remained strongly correlated with National Hockey League (NHL) penalties. The Canadian property crime rate was similarly correlated with stolen base attempts in the Major League Baseball (MLB). ... More Benchmarking in cluster analysis: A white paperSep 27 2018Oct 01 2018To achieve scientific progress in terms of building a cumulative body of knowledge, careful attention to benchmarking is of the utmost importance. This means that proposals of new methods of data pre-processing, new data-analytic techniques, and new methods ... More The Turtleback Diagram for Conditional ProbabilityAug 21 2018We elaborate on an alternative representation of conditional probability to the usual tree diagram. We term the representation `turtleback diagram' for its resemblance to the pattern on turtle shells. Adopting the set theoretic view of events and the ... More The Function Transformation Omics - FunomicsAug 17 2018There are no two identical leaves in the world, so how to find effective markers or features to distinguish them is an important issue. Function transformation, such as f(x,y) and f(x,y,z), can transform two, three, or multiple input/observation variables ... More A Conversation with Jon WellnerAug 15 2018Jon August Wellner was born in Portland, Oregon, in August 1945. He received his Bachelor's degree from the University of Idaho in 1968 and his PhD degree from the University of Washington in 1975. From 1975 until 1983 he was an Assistant Professor and ... More A Constructive Algebraic Proof of Student's TheoremJun 21 2018Student's theorem is an important result in statistics which states that for normal population, the sample variance is independent from the sample mean and has a chi-square distribution. The existing proofs of this theorem either overly rely on advanced ... More Kernel Methods for Nonlinear Connectivity DetectionJun 19 2018In this paper, we show that the presence of nonlinear coupling between time series may be detected employing kernel feature space representations alone dispensing with the need to go back to solve the pre-image problem to gauge model adequacy. As a consequence, ... More Data learning from big dataJun 08 2018Technology is generating a huge and growing availability of observa tions of diverse nature. This big data is placing data learning as a central scientific discipline. It includes collection, storage, preprocessing, visualization and, essentially, statistical ... More To Bayes or Not To Bayes? That's no longer the question!May 28 2018This paper seeks to provide a thorough account of the ubiquitous nature of the Bayesian paradigm in modern statistics, data science and artificial intelligence. Once maligned, on the one hand by those who philosophically hated the very idea of subjective ... More Hyperspectral Data Analysis in R: the hsdar PackageMay 14 2018Hyperspectral remote sensing is a promising tool for a variety of applications including ecology, geology, analytical chemistry and medical research. This article presents the new \hsdar package for R statistical software, which performs a variety of ... More Conjectures on Optimal Nested Generalized Group Testing AlgorithmMay 03 2018Sep 12 2018Consider a finite population of $N$ items, where item $i$ has a probability $p_i$ to be defective. The goal is to identify all items by means of group testing. This is the generalized group testing problem (GGTP hereafter). In the case of $\displaystyle ... More Viewing Simpson's ParadoxApr 21 2018Well known Simpson's paradox is puzzling and surprising for many, especially for the empirical researchers and users of statistics. However there is no surprise as far as mathematical details are concerned. A lot more is written about the paradox but ... More Resolving the Lord's ParadoxApr 21 2018An explanation to Lord's paradox using ordinary least square regression models is given. It is not a paradox at all, if the regression parameters are interpreted as predictive or as causal with stricter conditions and be aware of laws of averages. We ... More Multiple factor analysis of distributional dataApr 19 2018In the framework of Symbolic Data Analysis (SDA), distribution-variables are a particular case of multi-valued variables: each unit is represented by a set of distributions (e.g. histograms, density functions or quantile functions), one for each variable. ... More