Bootstrapping the empirical distribution of a stationary process with change-point

© 2019, Institute of Mathematical Statistics. All rights reserved. When detecting a change-point in the marginal distribution of a stationary time series, bootstrap techniques are required to determine critical values for the tests when the pre-change distribution is unknown. In this paper, we propose a sequential moving block bootstrap and demonstrate its validity under a converging alternative. Furthermore, we demonstrate that power is still achieved by the bootstrap under a non-converging alternative. We follow the approach taken by Peligrad in [14], and avoid assumptions of mixing, association or near epoch dependence. These results are applied to a linear process and are shown to be valid under very mild conditions on the existence of any moment of the innovations and a corresponding condition of summability of the coefficients

Change-point detection in the marginal distribution of a linear process

© 2016, Institute of Mathematical Statistics. All rights reserved. The subject of this paper is the detection of a change in the marginal distribution of a stationary linear process. By considering the marginal distribution, the change-point model can simultaneously incorporate any change in the coefficients and/or the innovations of the linear process. Furthermore, the change point can be random and data dependent. The key is an analysis of the asymptotic behaviour of the sequential empirical process, both with and without a change point. Our results hold under very mild conditions on the existence of any moment of the innovations and a corresponding condition of summability of the coefficients

A new family of bivariate exponential distributions with negative dependence based on counter-monotonic shock method

We introduce a new family of bivariate exponential distributions based on the counter-monotonic shock model. This family of distribution is easy to simulate and includes the Fréchet lower bound, which allows to span all degrees of negative dependence. The construction and distributional properties of the proposed bivariate distribution are presented along with an estimation of the parameters involved in our model based on the method of moments. A simulation study is carried out to evaluate the performance of the suggested estimators. An extension to the general model describing both negative and positive dependence is sketched in the last section of the paper

Breastfeeding Practices in the United Arab Emirates: Prenatal Intentions and Postnatal Outcomes

Breastfeeding provides the ideal nutrition in infancy, and its benefits extend to the health of mothers. Psychosocial factors such as the intention to breastfeed, self-efficacy, or maternal confidence to breastfeed have been shown to impact breastfeeding outcomes in other communities. The aim of this study was to assess the potential associations between mothers’ prenatal intention to breastfeed and post-delivery breastfeeding practices. A cross-sectional study was conducted from March to September 2017. Emirati and non-Emirati mothers with children below the age of 2 were recruited from maternal and child health centers in various geographical areas in Abu Dhabi Capital district, United Arab Emirates. The variables (mothers’ intention to breastfeed, breastfeeding knowledge, support from family and health care professionals, and initiation and duration of breastfeeding) were collected by research assistants during an in-person interview, using a structured questionnaire. A total of 1799 mothers participated in this study. Mothers’ prenatal intention to breastfeed was significantly associated with breastfeeding initiation (p \u3c 0.001) and length of exclusive breastfeeding (p = 0.006). Furthermore, intention to breastfeed during early pregnancy showed a strong association (p \u3c 0.001) with mothers who had exclusively breast fed for more than three months. In addition, knowledge on the benefits of breastfeeding and getting support from relatives and non-relatives demonstrated significant relationship with a longer period of exclusive breastfeeding (p \u3c 0.01) In total, mothers in the study reported receiving almost four thousand advice about breastfeeding, of which 3869 (97%) were encouraging to our others in the study. Our findings on prenatal intentions, knowledge and network support on exclusive breastfeeding indicates the importance of including breastfeeding knowledge and support as critical topics during prenatal education, not only to the mothers but also to close network members who seek a healthy pregnancy outcome

Bivariate Copulas Based on Counter-Monotonic Shock Method

This paper explores the properties of a family of bivariate copulas based on a new approach using the counter-monotonic shock method. The resulting copula covers the full range of negative dependence induced by one parameter. Expressions for the copula and density are derived and many theoretical properties are examined thoroughly, including explicit expressions for prominent measures of dependence, namely Spearman’s rho, Kendall’s tau and Blomqvist’s beta. The convexity properties of this copula are presented, together with explicit expressions of the mixed moments. Estimation of the dependence parameter using the method of moments is considered, then a simulation study is carried out to evaluate the performance of the suggested estimator. Finally, an application of the proposed copula is illustrated by means of a real data set on air quality in New York City

The impact of COVID-19 quarantine on lifestyle indicators in the United Arab Emirates

Introduction: COVID-19 is a virus that has spread rapidly and brought economic and social crises all around the world. The current study aimed to investigate the impact of COVID-19 quarantine on dietary habits, physical activity, food purchasing, smoking, and sleeping patterns in the United Arab Emirates. Methods: A cross-sectional study was conducted using an online questionnaire between November 1st, 2020 and the end of January 2021. Citizens and residents of the UAE aged ≥ 18 years old were asked to complete an anonymous electronic questionnaire created via Google Forms and distributed on various platforms, such as WhatsApp, Twitter, and email. A total of 1682 subjects participated in the study. Results: The results included that during the COVID-19 lockdown, more participants (44.4%) reported an increase in weight. This gain seems to be linked to increased food consumption [(Adjusted Odd Ratio) AOR = 1.68, 95% (Confidence Interval) CI = 1.12, 2.54, p = 0.022], decreased physical activity (AOR = 2.25, 95% CI = 1.58, 3.21, p \u3c 0.001), and increased smoking (AOR = 1.90, 95% CI = 1.04, 3.50, p = 0.038). The groups that were most likely to gain weight included those who consumed more cereals (AOR = 1.67, 95% CI = 1.08, 2.57, p = 0.011), had an increased desire for sweets (AOR = 2.19, 95% CI = 1.50, 3.19, p \u3c 0.001), and an increased desire for food (hunger) (AOR = 2.19, 95% CI = 1.53, 3.14, p \u3c 0.001). In contrast, those who exercised more were more likely to lose weight (AOR = 0.61, 95% CI = 0.44, 0.86, p \u3c 0.001) as well as those who slept over 9 h a day (AOR = 1.90, 95% CI = 0.45, 0.88, p = 0.006). Discussion: Overall, it is essential to promote healthy habits and methods of healthy diet maintenance during stressful and unusual times when people might find it difficult to put effort into their health

Prevalence and Sociodemographic Profiles of Grand Multipara in Abu Dhabi, United Arab Emirates

The literature shows that grand multipara mothers are major contributors to poor maternal and perinatal health compared to multipara mothers. Data regarding parity profiles are essential, especially in rapidly transforming countries such as the United Arab Emirates (UAE). This study aimed to investigate the prevalence and factors associated with multipara mothers compared to multipara mothers in Abu Dhabi, UAE. The data were collected from seven health care centers located in Abu Dhabi.From1818 enrolled mothers, the prevalence of grand multipara was 135(7.4%, 95% Confidence Interval (CI) = 7.2, 7.6). In logistic regression analysis, factors associated positively with grand multipara were a higher maternal age (Adjusted Odd Ratio (AOR) = 1.28, 95% CI = 1.21, 1.34), Arab mothers (AOR = 5.66, 95% CI 2.81, 11.40), overweight pre-pregnancy (AOR = 2.01, 95% CI = 1.26, 3.21), and limited family support for breastfeeding (AOR = 2.05, 95% CI = 1.21, 3.50). The prevalence of grand multipara was low compared to previous researching the UAE. Sociodemographic factors were more prominent and associated with grand multipara mothers compared to obstetrical ones. Therefore, more programs (nutritional, physical activities, and psychosocial) are needed to improve maternal and perinatal health to support grand multipara mothers. Further, research is required to explore the difference in parity based on nationalities, especially from a sociocultural point of view

Complete Study of an Original Power-Exponential Transformation Approach for Generalizing Probability Distributions

In this paper, we propose a flexible and general family of distributions based on an original power-exponential transformation approach. We call it the modified generalized-G (MGG) family. The elegance and significance of this family lie in the ability to modify the standard distributions by changing their functional forms without adding new parameters, by compounding two distributions, or by adding one or two shape parameters. The aim of this modification is to provide flexible shapes for the corresponding probability functions. In particular, the distributions of the MGG family can possess increasing, constant, decreasing, “unimodal”, or “bathtub-shaped“ hazard rate functions, which are ideal for fitting several real data sets encountered in applied fields. Some members of the MGG family are proposed for special distributions. Following that, the uniform distribution is chosen as a baseline distribution to yield the modified uniform (MU) distribution with the goal of efficiently modeling measures with bounded values. Some useful key properties of the MU distribution are determined. The estimation of the unknown parameters of the MU model is discussed using seven methods, and then, a simulation study is carried out to explore the performance of the estimates. The flexibility of this model is illustrated by the analysis of two real-life data sets. When compared to fair and well-known competitor models in contemporary literature, better-fitting results are obtained for the new model

Study of atmospheric pollution and health risk assessment: A case study for the sharjah and ajman emirates (uae)

Dust is a significant pollution source in the United Arab Emirates (UAE) that impacts population health. Therefore, the present study aims to determine the concentration of heavy metals (Cd, Pb, Cr, Cu, Ni, and Zn) in the air in the Sharjah and Ajman emirates’ urban areas and assesses the health risk. Three indicators were used for this purpose: the average daily dose (ADD), the hazard quotient (HQ), and the health index (HI). Data were collected during the period April–August 2020. Moreover, the observation sites were clustered based on the pollutants’ concentration, given that the greater the heavy metal concentration is, the greater is the risk for the population health. The most abundant heavy metal found in the atmosphere was Zn, with a mean concentration of 160.30 mg/kg, the concentrations of other metals being in the following order: Ni \u3e Cr \u3e Cu \u3e Pb \u3e Cd. The mean concentrations of Cd, Pb, and Cr were within the range of background values, while those of Cu, Ni, and Zn were higher than the background values, indicating anthropogenic pollution. For adults, the mean ADD values of heavy metals decreased from Zn to Cd (Zn \u3e Ni \u3e Cr \u3e Cu \u3e Pb \u3e Cd). The HQ (HI) suggested an acceptable (negligible) level of non-carcinogenic harmful health risk to residents’ health. The sites were grouped in three clusters, one of them containing a single location, where the highest concentrations of heavy metals were found

Asymptotics for the Sequential Empirical Process and Testing for Distributional Change for Stationary Linear Models

Detecting a change in the structure of a time series is a classical statistical problem. Here we consider a short memory causal linear process $X_i=\sum_{j=0}^\infty a_j\xi_{i-j}$, $i=1,\cdots,n$, where the innovations $\xi_i$ are independent and identically distributed and the coefficients $a_j$ are summable. The goal is to detect the existence of an unobserved time at which there is a change in the marginal distribution of the $X_i$'s. Our model allows us to simultaneously detect changes in the coefficients and changes in location and/or scale of the innovations. Under very simple moment and summability conditions, we investigate the asymptotic behaviour of the sequential empirical process based on the $X_i$'s both with and without a change-point, and show that two proposed test statistics are consistent. In order to find appropriate critical values for the test statistics, we then prove the validity of the moving block bootstrap for the sequential empirical process under both the hypothesis and the alternative, again under simple conditions. Finally, the performance of the proposed test statistics is demonstrated through Monte Carlo simulations