Application of bayesian scientific approach to constructing the statistical estimations for solving metrological and measurement problems

Nowadays, constructing effective statistical estimates with a limited amount of statistical information constitutes a significant practical problem. The article is devoted to applying the Bayesian scientific approach to the construction of statistical estimates of the parameters of the laws of distribution of random variables. Five distribution laws are considered: The Poisson law, the exponential law, the uniform law, the Pareto law, and the ordinary law. The concept of distribution laws that conjugate with the observed population was introduced and used. It is shown that for considered distribution laws, the parameters of the laws themselves are random variables and obey the typical law, gamma law, gamma - normal law, and Pareto law. Recalculation formulas are obtained to refine the parameters of these laws, taking into account posterior information. If we apply the recalculation formulas several times in a row, we will get some convergent process. Based on a converging process, it is possible to design a process for self-learning a system or self-tuning a system. The developed scientific approach was applied to solve the measuring problems for the testing measuring devices and technical systems. The results of constructing point estimates and constructing interval estimates for these laws' parameters are given. The results of comparison with the corresponding statistical estimates constructed by the classical maximum likelihood method are presented.

A Regime Shift in the Interhemispheric Teleconnection between the Yellow and East China Seas and The Southeastern Tropical Pacific in The Southern Hemisphere during The Boreal Summer

Through statistical estimations on reconstructed datasets for the period 1982−2020 after removing a long-term trend, we observed that there was a drastic regime shift in the early summer’s connection between the YECS and the tropical Pacific in the early 2000s. The summer YECS SSTs had seemed to be modulated by local oceanic and atmospheric processes along with their marginal coupling to the tropical Pacific during the pre-2003 period before the regime shift. In contrast, an interhemispheric YECS−tropical southeastern Pacific (SEP) coupling appeared after the regime shift. This teleconnection was at least partially attributed to a reduced El Niño signature in the tropical Pacific, which favors the emergence of the South Pacific meridional mode (SPMM) independently from ENSO signals. Precipitation anomalies in the western tropical Pacific act as an atmospheric bridge to mediate the air-sea interacted variability associated with the SPMM into the North Pacific. The susceptibility of the YECS to atmospheric forcing may highlight the role of SST over the YECS as a potential indicator of basin-scale climate changes.

Non-Isothermal Models to Determine the Rheological Constants of Different Kuwaiti Crude Oils

The rheological characteristics of four Kuwaiti crude oils samples collected from four different collection points; namely, MG 23T, MG 29T, MG 34T and MG 108T were investigated. The investigation were conducted in the temperature range 298–313 K using the Bingham, Ostwald–de Waele, Herschel–Bulkley, Casson, and modified Casson models. The experimental data of the shear stress were modeled as a function of the shear rate and temperature. Statistical estimations were used to determine the most accurate model and non-isothermal empirical relations. The Ostwald–de Waele and Herschel–Bulkley models yielded the most accurate predictions for MG 23T, MG 29T and MG 108T, and MG 34T, respectively. It is noted that all the crude oils follow shear thinning behavior. Arrhenius-Eyring equation has been used to estimate the activation energy and the pre-exponential factor of these crude oils at a shear rate of 10.3 s-1.

Is there any association between real earnings management and crash risk of stock price during uncertainty? An evidence from family-owned firms in an emerging economy

This research work intends to analyze the association between real earnings manipulation and stock price crash. Further, we also analyze the spillover outcome of the crash as a result of applying real earnings management. It is hypothesized that there is a positive and statistically significant association between real activities manipulation and crash risk. It is also assumed that this spillover outcome is more noticeable during uncertainty. By applying data of family firms for the time period 2005–2018, empirical results provide the proof that real manipulation has a significant impact on stock crash for a developing economy like Pakistan among family-based companies. This research work also gives a statistical insight that spillover outcome is more notable for firms facing uncertainty. Our statistical estimations are in support of the assumed hypotheses of the study. This study has very significant and practical implications for academic researchers, standard setters, and investors.

Seroprevalence of Human Fascioliasis Using ELISA in Sistan and Baluchestan Province, Southeast of Iran

Background: Fascioliasis is a zoonotic disease caused by the liver parasites, Fasciola hepatica, and F. gigantica. Objectives: The aim of this study was to determine the seroprevalence of fascioliasis in Zahedan and the surrounding towns (i.e., Zabol, Chabahar, Iranshahr, etc.) in the Southeast of Iran. Methods: This cross-sectional study was conducted in 2017. Based on statistical estimations, 251 human serum samples were collected randomly in Zahedan and surrounding towns (Zabol, Chabahar, Iranshahr, and others), then the samples were analyzed using indirect enzyme-linked immunosorbent assay (ELISA) test. A questionnaire was obtained from each individual. Statistical analysis was performed using the chi-square test in SPSS, version 20. Results: Of the 251 samples, the anti-fasciola antibody was detected in 6 (2.40%) samples. There was a significant relationship between the use of local freshwater vegetables and seropositivity to fasciolosis. Conclusions: This study showed that the prevalence of human fascioliasis was higher among women (2.70%) compared to men (0.0%), and raising health levels and health education can reduce the prevalence of human fascioliasis disease.

Lineage EM algorithm for inferring latent states from cellular lineage trees

Summary Phenotypic variability in a population of cells can work as the bet-hedging of the cells under an unpredictably changing environment, the typical example of which is the bacterial persistence. To understand the strategy to control such phenomena, it is indispensable to identify the phenotype of each cell and its inheritance. Although recent advancements in microfluidic technology offer us useful lineage data, they are insufficient to directly identify the phenotypes of the cells. An alternative approach is to infer the phenotype from the lineage data by latent-variable estimation. To this end, however, we must resolve the bias problem in the inference from lineage called survivorship bias. In this work, we clarify how the survivorship bias distorts statistical estimations. We then propose a latent-variable estimation algorithm without the survivorship bias from lineage trees based on an expectation–maximization (EM) algorithm, which we call lineage EM algorithm (LEM). LEM provides a statistical method to identify the traits of the cells applicable to various kinds of lineage data. Availability and implementation An implementation of LEM is available at https://github.com/so-nakashima/Lineage-EM-algorithm. Supplementary information Supplementary data are available at Bioinformatics online.

Berry–Esséen bound for the parameter estimation of fractional Ornstein–Uhlenbeck processes

For an Ornstein–Uhlenbeck process driven by fractional Brownian motion with Hurst index [Formula: see text], we show the Berry–Esséen bound of the least squares estimator of the drift parameter based on the continuous-time observation. We use an approach based on Malliavin calculus given by Kim and Park [Optimal Berry–Esséen bound for statistical estimations and its application to SPDE, J. Multivariate Anal. 155 (2017) 284–304].

THE IMPACT OF DEMOCRACY, CORRUPTION AND MILITARY EXPENDITURE ON ENVIRONMENTAL DEGRADATION: EVIDENCE FROM TOP SIX ASEAN COUNTRIES

Purpose of the study: The current study aims to examine the relationship between corruption, democracy, military expenditure and environmental degradation in a panel of six ASEAN countries including Malaysia, Indonesia, Philippines, Thailand, Singapore and Vietnam using a panel data from 1995 to 2017. Methodology: In addition, the current study is unique in applying the sophisticated methods of panel Fully Modified Ordinary Least Square (FMOLS) and Dynamic Ordinary Least Square (DOLS) that have been adopted in several earlier quality research. Main Findings: The results of panel estimations conclude that corruption, military expenditure, and democracy have a noteworthy and significant impact on carbon dioxide emission in ASEAN countries. The results of FMOLS and DOLS confirm that there is a positive and significant impact of military expenditure and corruption on carbon dioxide emission. However, we found a negative and significant impact of democracy on carbon dioxide emission in all selected ASEAN countries. Implications: In general, the consequences of both statistical estimations affirm that corruption, democracy, and military expenditure are the critical and noteworthy determinants of carbon dioxide emission in ASEAN nations.

THE THEORETICAL-EMPIRICAL TECHNIQUE OF HYDROCARBONS PREDICTION IN THE BOREHOLES LOGS WITH THE BASIC PARAMETER – COMPRESSIBILITY

The theoretical-empirical technique of hydrocarbon prediction in the boreholes logs is presented. It is based on the adequate physical-mathematical model of rocks, on the empirical relations between compressibility, porosity and pressure for these rocks, on the core data and also on acoustic logging data (the interval times or body wave’s velocities). For the cases of the acoustic logging data absence, the variants of the prediction technique by using data of gamma-logging, electric logging, and the offset logging method are developed. The presented technique is realized as a system of theoretical and empirical relations and the resulting functional. The adequate set of software tools is developed in the Fortran, C# and Excel environments. The technique is tested on the well’s data of a number of structures of Western oil and gas region of Ukraine: Lishchynska, Buchatska, Ludynska, Zaluzhanska, Zarichnianska, Nyklovytska, Orkhovytska. The statistical estimations of petrophysical characteristics of rock-collectors of those wells are presented. For more reliable prediction by the technique, instead of relations for the general parametric base, the empirical relations for concrete available in the studied boreholes logs types and subtypes of rock-collectors are elaborated.