Hasil untuk "Probabilities. Mathematical statistics"

SALMA RCHILY

Investments are likely to enhance economic growth; and, in many ways, they strengthen local savings and local investment while being a source of job creation. The Moroccan government views foreign investment as an important vehicle for development. In recent years, morocco has gained the upper hand in its conflict in western Sahara and has been increasing its politically and economically footprints on the African continent, a district of interest, since independence. In this context, this paper seeks to determine the weight of Moroccan FDI in Sub Saharan African countries by examining all factors that have influenced Moroccan policy towards this area and then analyze the effects of its FDI in this region, which they may positively affect human and social development.     Key words: Foreign Direct Investment (FDI), Morocco, Sub-Saharan Africa countries, …  

Anh Tu Tran, Sou Nobukawa, Sou Nobukawa et al.

IntroductionChaotic resonance is similar to stochastic resonance, which emerges from chaos as an internal dynamical fluctuation. In chaotic resonance, chaos-chaos intermittency (CCI), in which the chaotic orbits shift between the separated attractor regions, synchronizes with a weak input signal. Chaotic resonance exhibits higher sensitivity than stochastic resonance. However, engineering applications are difficult because adjusting the internal system parameters, especially of biological systems, to induce chaotic resonance from the outside environment is challenging. Moreover, several studies reported abnormal neural activity caused by CCI. Recently, our study proposed that the double-Gaussian-filtered reduced region of orbit (RRO) method (abbreviated as DG-RRO), using external feedback signals to generate chaotic resonance, could control CCI with a lower perturbation strength than the conventional RRO method.MethodThis study applied the DG-RRO method to a model which includes excitatory and inhibitory neuron populations in the frontal cortex as typical neural systems with CCI behavior.Results and discussionOur results reveal that DG-RRO can be applied to neural systems with extremely low perturbation but still maintain robust effectiveness compared to conventional RRO, even in noisy environments.

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Clinical reasoning is central to the professional practice of speech-language pathologists. It is, however, a very complex and multi-faceted construct. In health sciences in general, and speech-language pathology in particular, the construct of clinical reasoning is quite tricky to assess. Accordingly, one of the strategy's goals is to develop a conceptual model that reflects prevailing research directions for optimum assessment within speech-language pathology. A good literature review, thematically organized using Zotero and Nvivo software, allows the development of an assessment model for clinical reasoning competency in speech-language pathology. This model uses case-based clinical reasoning approaches within the classroom setting. In simulated settings, it uses structured OSCE procedures. During placements, written case notes are used alongside oral case presentations. Although limited, this study provides the foundation for further studies with empirical exploration and validation of this assessment model within the speech-language pathology area and other related health fields.

Ilya Zulaikha Zulkifli, Nor Faezah Mohamad Razi, Nor Hazlina Mohammad et al.

Over recent semesters, the increasing failure rates in STA108 have raised concerns about this course's teaching and learning environment. This issue has prompted an investigation into potential contributing factors, focusing on three main objectives: examining the students’ association between gender and MAT133, exploring the relationship between students’ achievements in MAT133 and their Mathematics grades in the Sijil Pelajaran Malaysia (SPM), and assessing the association between STA108 results and their Mathematics grades in the Sijil Pelajaran Malaysia (SPM). The respondents completed 329 online surveys using the purposive sampling approach. The questionnaire with two distinct parts which included the socio-demographic and other pertinent information required for analysing the respondents' profiles. The second component was the primary focus of the study. Chi-Square test was conducted to analyse the data.   The test revealed no significant association between gender and MAT133. It also indicates a significant correlation between students' achievements in MAT133 and their SPM Mathematics grades. There is a significant association between STA108 and their SPM Mathematics grades. Our research significantly contributes to the ongoing discussion regarding the relationship between secondary and tertiary mathematics education. It also sets the stage for further research into specific pedagogical approaches that could enhance the effectiveness of mathematics education at the tertiary level.

Gilson D. Honvoh, Roger S. Zoh, Anand Gupta et al.

BackgroundObesity has become an important threat to children’s health, with physical and psychological impacts that extend into adulthood. Limited physical activity and sedentary behavior are associated with increased obesity risk. Because children spend approximately 6 h each day in school, researchers increasingly study how obesity is influenced by school-day physical activity and energy expenditure (EE) patterns among school-aged children by using wearable devices that collect data at frequent intervals and generate complex, high-dimensional data. Although clinicians typically define obesity in children as having an age-and sex-adjusted body mass index (BMI) value in the high percentiles, the relationships between school-based physical activity interventions and BMI are analyzed using traditional linear regression models, which are designed to assess the effects of interventions among children with average BMI, limiting insight regarding the effects of interventions among children categorized as overweight or obese.MethodsWe investigate the association between wearable device–based EE measures and age-and sex-adjusted BMI values in data from a cluster-randomized, school-based study. We express and analyze EE levels as both a scalar-valued variable and as a continuous, high-dimensional, functional predictor variable. We investigate the relationship between school-day EE (SDEE) and BMI using four models: a linear mixed-effects model (LMEM), a quantile mixed-effects model (QMEM), a functional mixed-effects model (FMEM), and a functional quantile mixed-effects model (FQMEM). The LMEM and QMEM include SDEE as a summary measure, whereas the FMEM and FQMEM allow for the modeling of SDEE as a high-dimensional covariate. The FMEM and FQMEM allow the influence of the time of day at which physical activity is performed to be assessed, which is not possible using the LMEM or the QMEM. The FMEM assesses how frequently collected SDEE data influences mean BMI, whereas the FQMEM assesses the effects on quantile levels of BMI.ResultsThe LMEM and QMEM detected a statistically significant effect of overall mean SDEE on log (BMI) (the natural logarithm of BMI) after adjusting for intervention, age, race, and sex. The FMEM and FQMEM provided evidence for statistically significant associations between SDEE and log (BMI) for only a short time interval. Being a boy or being assigned a stand-biased desk is associated with a lower log (BMI) than being a girl or being assigned a traditional desk. Across our models, age was not a statistically significant covariate, and white students had significantly lower log (BMI) than non-white students in quantile models, but this significant effect was observed for only the 10th and 50th quantile levels of BMI. The functional regression models allow for additional interpretations of the influence of EE patterns on age-and sex-adjusted BMI, whereas the quantile regression models enable the influence of EE patterns to be assessed across the entire BMI distribution.ConclusionThe FQMEM is recommended when interest lies in assessing how device-monitored SDEE patterns affect children of all body types, as this model is robust and able to assess intervention effects across the full BMI distribution. However, the sample size must be sufficiently large to adequately power determinations of covariate effects across the entire BMI distribution, including the tails.

Cedric De Boom, Michael Reusens

Data science has become increasingly essential for the production of official statistics, as it enables the automated collection, processing, and analysis of large amounts of data. With such data science practices in place, it enables more timely, more insightful and more flexible reporting. However, the quality and integrity of data-science-driven statistics rely on the accuracy and reliability of the data sources and the machine learning techniques that support them. In particular, changes in data sources are inevitable to occur and pose significant risks that are crucial to address in the context of machine learning for official statistics. This paper gives an overview of the main risks, liabilities, and uncertainties associated with changing data sources in the context of machine learning for official statistics. We provide a checklist of the most prevalent origins and causes of changing data sources; not only on a technical level but also regarding ownership, ethics, regulation, and public perception. Next, we highlight the repercussions of changing data sources on statistical reporting. These include technical effects such as concept drift, bias, availability, validity, accuracy and completeness, but also the neutrality and potential discontinuation of the statistical offering. We offer a few important precautionary measures, such as enhancing robustness in both data sourcing and statistical techniques, and thorough monitoring. In doing so, machine learning-based official statistics can maintain integrity, reliability, consistency, and relevance in policy-making, decision-making, and public discourse.

V. Ananiev, A. L. Read

In this paper we consider the probability density function (pdf) of the non-central χ2 distribution with arbitrary number of degrees of freedom and non-centrality. For this function we find the approximate location of the maximum and discuss related edge cases of 1 and 2 degrees of freedom. We also use this expression to demonstrate the improved performance of the C++ Boost’s implementation of the non-central χ2 and extend the domain of its applicability.

A. Ashyralyev, B. Haso

Time-dependent and space-dependent source identification problems for partial differential and difference equations take an important place in applied sciences and engineering, and have been studied by several authors. Moreover, the delay appears in complicated systems with logical and computing devices, where certain time for information processing is needed. In the present paper, the time-dependent identification problem for delay hyperbolic equation is investigated. The theorems on the stability estimates for the solution of the time-dependent identification problem for the one dimensional delay hyperbolic differential equation are established. The proofs of these theorems are based on the Dalambert’s formula for the hyperbolic differential equation and integral inequality.

Siham Bouklata, Bouchra Bouklata

In an ever more demanding competitive bubble with changes as frequent as unpredictable, the ability to adapt becomes a survival imperative for any organization with human capital as its weapon of choice and human resources management as its tool of managerial excellence. A crucial challenge for success, performance reveals to be a major goal any organization continues to scrutinize despite the absence of a single and standard definition of this concept. The performance of HRM is conditioned by a set of determinants as varied as they create value, outlining the missions of this task. The correlation between the performance of HRM and its determinants leads to their optimization and the search for the appropriate combination, as well as the strategic arrangements and the mode of operation capable of maximizing performance and promoting efficiency. A hierarchy of these determinants can be established according to their importance knowing that they are interdependent. Their concerted management allows synergy and hence an economy of scale and better efficiency. Their concerted management allows synergy and therefore an economy of scale and greater efficiency. Once faced with budgetary constraints, the most important determinants must be prioritized, while ensuring the minimum service for the other determinants, especially, the less budgeted ones. The empirical part relating to the Ibn Tofaïl University of Kenitra is but a corroboration of these findings while revealing its specificities in this area.

Xiaoli Yu, Shaoting Li, Jiahua Chen

Dose–response experiments and data analyses are often carried out according to an optimal design under a model assumption. A two-parameter logistic model is often used because of its nice mathematical properties and plausible stochastic response mechanisms. There is an extensive literature on its optimal designs and data analysis strategies. However, a model is at best a good approximation in a real-world application, and researchers must be aware of the risk of model mis-specification. In this paper, we investigate the effectiveness of the sequential ED-design, the D-optimal design, and the up-and-down design under the three-parameter logistic regression model, and we develop a numerical method for the parameter estimation. Simulations show that the combination of the proposed model and the data analysis strategy performs well. When the logistic model is correct, this more complex model has hardly any efficiency loss. The three-parameter logistic model works better than the two-parameter logistic model in the presence of model mis-specification.

Johnson A. Adewara, Kayode S. Adekeye, Olubisi L. Aako

In this paper, two methods of control chart were proposed to monitor the process based on the two-parameter Gompertz distribution. The proposed methods are the Gompertz Shewhart approach and Gompertz skewness correction method. A simulation study was conducted to compare the performance of the proposed chart with that of the skewness correction approach for various sample sizes. Furthermore, real-life data on thickness of paint on refrigerators which are nonnormal data that have attributes of a Gompertz distribution were used to illustrate the proposed control chart. The coverage probability (CP), control limit interval (CLI), and average run length (ARL) were used to measure the performance of the two methods. It was found that the Gompertz exact method where the control limits are calculated through the percentiles of the underline distribution has the highest coverage probability, while the Gompertz Shewhart approach and Gompertz skewness correction method have the least CLI and ARL. Hence, the two-parameter Gompertz-based methods would detect out-of-control faster for Gompertz-based X¯ charts.

C. P. Caetano , P. de Zea Bermudez

It has been well stated that high values of blood pressure constitute a risk factor for cardiovascular diseases [20], with the latter being the number one death cause in Portugal. The main interest of the present study is to model the high values of systolic blood pressure in the individuals of the population who are most at risk, i.e., the elderly. This group frequently suffers from a specific type of hypertension pathology, known as isolated systolic hypertension. With that purpose the Peaks Over Threshold methodology was applied, which consists in fitting a generalized Pareto distribution to the excesses above a sufficiently high threshold. The model will be able to estimate extreme quantiles and tail probabilities.

Mohammad Darvishi, Mohammad Aminianfar, Bahar Heidarinia et al.

Background & Aim: The term hepatitis applies to a wide group of clinical and pathological condition that is often caused by damage to the liver by various factors including viral infections. The present study aimed to assess the awareness of non-medical students about the viral hepatitis disease. Methods & Materials: In this cross-sectional descriptive study, 298 students of the two universities in Tehran were selected. The data collecting tool was a two-part questionnaire. The first part examined the student demographic information, and the second part consisted of 10 questions about of viral hepatitis. Questionnaires were distributed among the students and then the data were analyzed by SPSS software. Results: Among the 298 respondents, there were 224 women with a mean age of 26 years. 155 people (52%) were students of medicine and biosciences and 143 (48%) were students of the humanities. There was a significant difference between the awareness of the correct answer and the fields of study. Therefore, the awareness level of paramedical and biological sciences students was higher than other disciplines. Conclusion: The mean level of awareness of respondents was 32.95%. The average level of awareness in students of paramedical and biological sciences (31.99%) was higher than the average level of awareness in students of humanities (16.06%). Albeit the entire study population was composed of the young and educated people, their awareness of viral hepatitis was low. It strongly reflects poor knowledge of society and especially our young people as a group at risk.

Andrea Saltelli

Statistics experiences a storm around the perceived misuse and possible abuse of its methods in the context of the so-called reproducibility crisis. The methods and styles of quantification practiced in mathematical modelling rarely make it to the headlines, though modelling practitioners writing in disciplinary journals flag a host of problems in the field. Technical, cultural and ethical dimensions are simultaneously at play in the current predicaments of both statistics and mathematical modelling. Since mathematical modelling is not a discipline like statistics, its shortcomings risk remaining untreated longer. We suggest that the tools of statistics and its disciplinary organisation might offer a remedial contribution to mathematical modelling, standardising methodologies and disseminating good practices. Statistics could provide scientists and engineers from all disciplines with a point of anchorage for sound modelling work. This is a vast and long-term undertaking. A step in the proposed direction is offered here by focusing on the use of statistical tools for quality assurance of mathematical models. By way of illustration, techniques for uncertainty quantification, sensitivity analysis and sensitivity auditing are suggested for incorporation in statistical syllabuses and practices.

Melanie Knobelspies, Ralf Münnich

Zur Verbesserung der Schätzqualität werden in Stichprobenerhebungen häufig vorhandene Zusatzinformationen in die Hochrechnung eingebunden, insbesondere bei der Verwendung von verallgemeinerten Regressionsschätzern. In einigen Erhebungen, wie in der Einkommens- und Verbrauchsstichprobe oder im deutschen Survey on Income and Living Conditions (Leben in Europa; D-SILC) stehen hierfür sehr viele Variablen zur Verfügung. In der Praxis muss man sich jedoch aus methodisch-technischen Gründen auf eine geeignete Auswahl von Hilfsvariablen beschränken. In diesem Aufsatz wird der Frage nachgegangen, inwieweit statistisch-ökonometrische Variablenselektionsverfahren bei der Auswahl geeigneter Hilfsvariablen herangezogen werden können. Es wird insbesondere untersucht, ob die Effizienz eines Regressionsmodells, die das Ziel solcher Selektionsverfahren ist, auch gleichzeitig die Genauigkeit der eigentlich interessierenden Stichprobenschätzung optimiert. Darüber hinaus wird untersucht, inwiefern spezielle geschichtete Stichprobenziehungen die Ergebnisse beeinflussen.

Sharad Saxena, Housila P. Singh

The dispersion parameter of a chi-distributed radial error is of interest in numerous target analysis problems as a measure of weapon-system accuracy, and it is often of practical importance to estimate it. This paper presents a few classical estimators including the maximum likelihood estimator, an unbiased estimator and a minimum mean squared error estimator of this dispersion for both when the origin or “center of impact” is known or can be assumed as known and when it is unknown. Some families of shrinkage estimators have also been suggested when a prior point estimate of the dispersion parameter is available in addition to sample information. The estimators of circular error probable and spherical error probable have been obtained as well. A simulation study has been carried out to demonstrate the performance of the proposed estimators.

John H. J. Einmahl, Jun Li, Regina Y. Liu

Statistical depth measures the centrality of a point with respect to a given distribution or data cloud. It provides a natural center-outward ordering of multivariate data points and yields a systematic nonparametric multivariate analysis scheme. In particular, the half-space depth is shown to have many desirable properties and broad applicability. However, the empirical half-space depth is zero outside the convex hull of the data. This property has rendered the empirical half-space depth useless outside the data cloud, and limited its utility in applications where the extreme outlying probability mass is the focal point, such as in classification problems and control charts with very small false alarm rates. To address this issue, we apply extreme value statistics to refine the empirical half-space depth in "the tail." This provides an important linkage between data depth, which is useful for inference on centrality, and extreme value statistics, which is useful for inference on extremity. The refined empirical half-space depth can thus extend all its utilities beyond the data cloud, and hence broaden greatly its applicability. The refined estimator is shown to have substantially improved upon the empirical estimator in theory and simulations. The benefit of this improvement is also demonstrated through the applications in classification and statistical process control.

Satish Shukla, Stojan Radenovic

The purpose of this paper is to prove some Presic-Boyd-Wong type fixed point theorems in ordered metric spaces. The results of this paper generalize the famous results of Presic and Boyd-Wong in ordered metric spaces. We also initiate the homotopy result in product spaces. Some examples are provided which illustrate the results proved herein.

Lígia Henriques-Rodrigues , M. Ivette Gomes , M. Isabel Fraga Alves et al.

In this paper we study, under a semi-parametric framework and for heavy right tails, a class of location invariant estimators of a shape second-order parameter, ruling the rate of convergence of the normalised sequence of maximum values to a non-degenerate limit. This class is based on the PORT methodology, with PORT standing for peaks over random thresholds. Asymptotic normality of such estimators is achieved under a third-order condition on the right-tail of the underlying model F and for suitable large intermediate ranks. An illustration of the finite sample behaviour of the estimators is provided through a small-scale Monte-Carlo simulation study.

Wei Luo, Bing Li, Xiangrong Yin

We introduce a new sufficient dimension reduction framework that targets a statistical functional of interest, and propose an efficient estimator for the semiparametric estimation problems of this type. The statistical functional covers a wide range of applications, such as conditional mean, conditional variance and conditional quantile. We derive the general forms of the efficient score and efficient information as well as their specific forms for three important statistical functionals: the linear functional, the composite linear functional and the implicit functional. In conjunction with our theoretical analysis, we also propose a class of one-step Newton-Raphson estimators and show by simulations that they substantially outperform existing methods. Finally, we apply the new method to construct the central mean and central variance subspaces for a data set involving the physical measurements and age of abalones, which exhibits a strong pattern of heteroscedasticity.