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Topic Review
Accurate and Invertible Sketch for Super Spread Detection
Super spread detection has been widely applied in network management, recommender systems, and cyberspace security. It is more complicated than heavy hitter owing to the requirement of duplicate removal. Accurately detecting a super spread in real-time with small memory demands remains a nontrivial yet challenging issue. 
  • 90
  • 11 Jan 2024
Topic Review
Aesthetical Evaluation with Stochastic Analysis
Stochastic calculus is used for the objective evaluation of the variability present in aesthetic attributes of paintings and landscapes.
  • 734
  • 24 Nov 2020
Topic Review
Analysis of Time Use Surveys Using CO-STATIS
The aim of this article was to study 23 time use activities measured in the two latest Colombian National Time Use Surveys, taken in 2013 (with 119,899 participants over the age of 10) and in 2017 (with a sample of 122,620 participants), to identify similarities and differences between the years of the survey by gender, age group, and socioeconomic level. The study’s results were obtained using the CO-STATIS multiway multivariate data analysis technique, which is comprised of two X-STATIS analyses and co-inertia analysis. The results confirm the existence of gender issues related to time use in Colombia, which are associated with gender stereotypes that link women to unpaid work and home care, especially in low socioeconomic levels, where women face limitations in terms of the time available to earn their own income. Additionally, differences were found by socioeconomic level, where Colombians of high socioeconomic status in all age groups are able to devote more time to leisure and recreational activities.
  • 459
  • 01 Dec 2021
Topic Review
Application of Biological Domain Knowledge
Integrative approaches that utilize the biological knowledge while performing feature selection are necessary for this kind of data. The main idea behind the integrative gene selection process is to generate a ranked list of genes considering both the statistical metrics that are applied to the gene expression data, and the biological background information which is provided as external datasets. 
  • 1.0K
  • 19 Feb 2021
Topic Review Peer Reviewed
Application of Mobile Operators’ Data in Modern Geographical Research
Mobile operators’ data are one type of Big Data. These are any data about events related to the use of a mobile phone. These data include subscriber identifiers and associated time and location attributes. Big Data in general usually includes datasets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. Big Data can be described by the following key characteristics: volume, variety, velocity, veracity, value, variability etc. Mobile operators’ data are supplied by the Mobile Network Operators. The main distinguishing features of the operator are, firstly, the possession of a state license to use the radio frequency spectrum, and, secondly, the possession or control over the elements of the network infrastructure necessary to provide services to subscribers in the authorized radio frequency spectrum. The smallest structural territorial element for cellular communication systems is a cell; its dimensions can be different (250 by 250 m, 500 by 500 m, etc.).
  • 303
  • 01 Dec 2022
Topic Review
Bayesian Analysis in Social Sciences
Given the reproducibility crisis (or replication crisis), more psychologists and social-cultural scientists are getting involved with Bayesian inference. Therefore, the current article provides a brief overview of programs (or software) and steps to conduct Bayesian data analysis in social sciences. 
  • 1.1K
  • 23 Jul 2021
Topic Review
Bayesian Nonlinear Mixed Effects Models
Nonlinear mixed effects models have become a standard platform for analysis when data is in the form of continuous and repeated measurements of subjects from a population of interest, while temporal profiles of subjects commonly follow a nonlinear tendency. While frequentist analysis of nonlinear mixed effects models has a long history, Bayesian analysis of the models has received comparatively little attention until the late 1980s, primarily due to the time-consuming nature of Bayesian computation. Since the early 1990s, Bayesian approaches for the models began to emerge to leverage rapid developments in computing power, and have recently received significant attention due to (1) superiority to quantify the uncertainty of parameter estimation; (2) utility to incorporate prior knowledge into the models; and (3) flexibility to match exactly the increasing complexity of scientific research arising from diverse industrial and academic fields. 
  • 891
  • 23 Mar 2022
Topic Review
Categorical Exploratory Data Analysis
Categorical exploratory data analysis (CEDA) is demonstrated to provide new resolutions for two topics: multiclass classification (MCC) with one single categorical response variable and response manifold analytics (RMA) with multiple response variables. 
  • 432
  • 08 Jul 2021
Topic Review
Chi square statistic
The Chi-Square test is based on a series of assumptions frequently used in the statistical analysis of experimental data. The main weakness of the chi-square test is that is very accurate only in convergence (in large size samples), and for small sample sizes is exposed to errors of both types (type I and type II). On two scenarios of use - goodness of fit and contingencies assessment (2x2 tables of contingency) - here are discussed different aspects involving it. Further knowledge on the regard of the type of the error in contingencies assessment push further the analysis of the data, while in the same time opens the opportunity to devise a method for filling the gaps in contingencies (e.g. censored data), both scenarios being discussed here in detail. A program designed to fill the gaps in the assumption of the association is provided.
  • 3.5K
  • 24 Dec 2020
Topic Review
Consensus Big Data Clustering for Bayesian Mixture Models
In the context of big-data analysis, the clustering technique holds significant importance for the effective categorization and organization of extensive datasets. However, pinpointing the ideal number of clusters and handling high-dimensional data can be challenging. To tackle these issues, several strategies have been suggested, such as a consensus clustering ensemble that yields more significant outcomes compared to individual models. Another valuable technique for cluster analysis is Bayesian mixture modelling, which is known for its adaptability in determining cluster numbers. 
  • 165
  • 18 Aug 2023
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