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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.
07 Apr 2021
Mobile Technology in Tourism
The influence of mobile technology on tourism is very significant. With the support of mobile-related devices (smartphones, glasses, or other wearable devices), technology, data and services, multiple travel concepts, and travel modes including mobile tourism, smart tourism, e-tourism, and sustainable tourism have emerged or developed further. Mobile technology is touted as the next technology wave that can fundamentally change tourism and hotels. Moreover, mobile technology is playing an increasing role in the travel experience, and increasing travel research is concentrated in this field. Research findings show that, first, the research of mobile technology in tourism can be divided into three phases and to a certain extent is synchronized with the development of mobile technology. Second, in the area of social sciences, the research of mobile technology in tourism needs further exploration, which must refer to related research in the areas of Transportation and IT to expand the perspective of research. Top journal analysis, journal co-citation analysis, author co-citation analysis, and collaboration network analysis reveal the most representative journals, authors, institutions, and countries/regions in this research field. This finding provides a valuable reference for scholars in this field. Additionally, this research also grasped the hot and cutting-edge topics in this field through the analysis of keywords in this field. Finally, the clustering of co-citation references presents the knowledge base of mobile technology research in the tourism field: mobile technology, travel mode, mobile instrument, travel behavior research, mobile applications, and geo-based technology.
28 Sep 2020
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.
24 Dec 2020
Markov Chain Applications to Education
The theory of Markov chains is a smart combination of Linear Algebra and Probability theory offering ideal conditions for modelling situations depending on random variables. Markov chains have found important applications to many sectors of the human activity. In this work a finite Markov chain is introduced representing mathematically the teaching process which is based on the ideas of constructivism for learning. Interesting conclusions are derived and a measure is obtained for the teaching effectiveness. An example on teaching the derivative to fresher university students is also presented illustrating our results.
03 Dec 2020
Extreme values statistic
One of the pillars of experimental sciences is sampling. Based on analysis conducted on samples the estimations for the populations are made. The distributions are split in two main groups: continuous and discrete and the present study applies for the continuous ones. One of the challenges of the sampling is the accuracy of it, or, in other words how representative is the sample for the population from which was drawn. Another challenge, connected with this one, is the presence of the outliers - observations wrongly collected, not actually belonging to the population subjected to study. The present study proposes a statistic (and a test) intended to be used for any continuous distribution to detect the outliers, by constructing the confidence interval for the extreme value in the sample, at certain (preselected) risk of being in error, and depending on the sample size. The proposed statistic is operational for known distributions (having known their probability density function) and is dependent too on the statistical parameters of the population.
29 Oct 2020
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.
19 Feb 2021
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.
14 Apr 2022
Six Stages to Choose Sampling Techniques
In order to answer the research questions, it is doubtful that researcher should be able to collect data from all cases. Thus, there is a need to select a sample. The entire set of cases from which researcher sample is drawn in called the population. Since, researchers neither have time nor the resources to analysis the entire population so they apply sampling technique to reduce the number of cases. There are six stages to choose sampling techniques.
18 Feb 2022
Optimal Interpolation for infrared satellite data
Thermal infrared remote sensing measurements are blinded to surface emissions under cloudiness because infrared sensors cannot penetrate thick cloud layers. Therefore, surface and atmospheric parameters can be retrieved only in clear sky conditions giving origin to spatial fields flagged with missing pieces of information. Motivated by this we present a methodology to retrieve missing values of some interesting geophysical variables retrieved from spatially scattered infrared satellite observations in order to yield level 3 (L3), regularly gridded, data. The technique is based on a 2-Dimensional (2D) Optimal Interpolation (OI) scheme. The goodness of the approach has been tested on 15-min temporal resolution Spinning Enhanced Visible and Infrared Imager (SEVIRI) emissivity and surface temperature (ST) products over South Italy (land and sea), on Infrared Atmospheric Sounding Interferometer (IASI) atmospheric ammonia (NH3) concentration over North Italy and carbon monoxide (CO), sulfur dioxide (SO2) and NH3 concentrations over China. Sea surface temperature (SST) retrievals have been compared with gridded data from MODIS (Moderate-resolution Imaging Spectroradiometer) observations. For gases concentration, we have considered data from 3 different emission inventories, that is, Emissions Database for Global Atmospheric Research v3.4.2 (EDGARv3.4.2), the Regional Emission inventory in ASiav3.1 (REASv3.1) and MarcoPolov0.1, plus an independent study.
30 Oct 2020
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.
23 Jul 2021
Featured Entry Collections
Encyclopedia of Social Sciences
Expected Online Date: Dec 2022
Encyclopedia of ZEMCH Research and Development
Expected Online Date: Dec 2022
Encyclopedia of Engineering
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Encyclopedia of Piezoelectrics
Expected Online Date: Dec 2022
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