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Topic Review
Statistical Methods for Food Composition Database Analysis
A food composition database (FCDB) or nutrient database is a compilation of the chemical composition of food and beverage items, obtained from chemical analyses, estimations from published literature, or unpublished laboratory reports. A summary of the statistical methods that have been directly applied to food composition databases and datasets is described here.
  • 1.0K
  • 08 Jun 2022
Topic Review
Diffusion of Solar PV Energy
Solar photovoltaic energy (solar PV) is considered a very attractive solution among renewable energy sources (RES), especially for households. According to the most recent IEA report on renewables, the growth of renewable power capacity at the world level has reached another record in 2021, driven by solar photovoltaic energy; solar PV alone has accounted for more than half of all renewable power expansion in 2021, followed by wind and hydropower.
  • 1.0K
  • 28 Apr 2022
Topic Review
Modelling Energy Transition in Germany
The expression energy transition indicates a long-term structural change in energy systems. It is not a new phenomenon: man has made several energy transitions in his short history on Earth. One of the most significant was shifting to an energy system based on fossil fuels (coal, oil, and natural gas) from one essentially based on wood; however, since the 1980s, it has been realized that fossil fuels are at the root of climate change due to carbon emissions into the atmosphere.
  • 479
  • 20 Apr 2022
Topic Review Peer Reviewed
Spatial Hurst–Kolmogorov Clustering
The stochastic analysis in the scale domain (instead of the traditional lag or frequency domains) is introduced as a robust means to identify, model and simulate the Hurst–Kolmogorov (HK) dynamics, ranging from small (fractal) to large scales exhibiting the clustering behavior (else known as the Hurst phenomenon or long-range dependence). The HK clustering is an attribute of a multidimensional (1D, 2D, etc.) spatio-temporal stationary stochastic process with an arbitrary marginal distribution function, and a fractal behavior on small spatio-temporal scales of the dependence structure and a power-type on large scales, yielding a high probability of low- or high-magnitude events to group together in space and time. This behavior is preferably analyzed through the second-order statistics, and in the scale domain, by the stochastic metric of the climacogram, i.e., the variance of the averaged spatio-temporal process vs. spatio-temporal scale.
  • 1.1K
  • 14 Apr 2022
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. 
  • 905
  • 23 Mar 2022
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.
  • 474
  • 01 Dec 2021
Topic Review
Healthcare Electronic Records
Healthcare electronic records can provide both physicians and healthcare agencies to discover knowledge.  This work proposes an overview of the data mining techniques used for knowledge discovery in medical records. Furthermore, based on real healthcare data, this paper also demonstrates a case study of discovering knowledge with the help of three data mining techniques: (1) association analysis; (2) sequential pattern mining; (3) clustering. Particularly, association analysis is used to extract frequent correlations among examinations done by patients with a specific disease, sequential pattern mining allows extracting frequent patterns of medical events and clustering is used to find groups of similar patients. The discovered knowledge may enrich healthcare guidelines, improve their processes and detect anomalous patients’ behavior with respect to the medical guidelines. 
  • 432
  • 23 Sep 2021
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
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. 
  • 441
  • 08 Jul 2021
Topic Review
Gompertz Function with R
The Gompertz function is a sigmoid curve being a special case of a logistic curve. Although it was originally designed to describe mortality, it is now used in biology. For example, it is useful to describe many  phenomena such as the growth of a cancerous tumor confined to an organ without metastasis, the growth of the number of individuals in a population, e.g. prey in a Volterra-Lotka model, the germination of seeds, etc. It also models as the logistic function the growth of a colony of bacteria or in an epidemic the spread of the number of infected people. However, despite its many applications, in many cases the fitting of experimental data to the Gompertz function is not always straightforward. In this article we present a protocol that will be useful when performing the data regression to this curve using the statistical package R.
  • 20.1K
  • 07 Apr 2021
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