The FastHCS algorithm for robust PCA

Principal component analysis (PCA) is widely used to analyze high-dimensional data, but it is very sensitive to outliers. Robust PCA methods seek fits that are unaffected by the outliers and can therefore be trusted to reveal them. FastHCS (high-dimensional congruent subsets) is a robust PCA algorithm suitable for high-dimensional applications, including cases where the number of variables exceeds the number of observations. After detailing the FastHCS algorithm, we carry out an extensive simulation study and three real data applications, the results of which show that FastHCS is systematically more robust to outliers than state-of-the-art methods.     

Percentile-t Bootstrap Confidence Intervals for Period Using Periodogram

The magnitude of light intensity of many stars varies over time in a periodic way. Therefore, estimation of period and making inference about this parameter are of great interest in astronomy. The periodogram can be used to estimate period, properly. Bootstrap confidence intervals for period suggested here, are based on using the periodogram and constructed by percentile-t methods. We prove that the equal-tailed percentile-t bootstrap confidence intervals for period have an error of order n ^?1. We also show that the symmetric percentile-t bootstrap confidence intervals reduce the error to order n ^?2, and hence have a better performance. Finally, we assess the theoretical results by conducting a simulation study, compare the results with the coverages of percentile bootstrap confidence intervals for period and then analyze a real data set related to the eclipsing system R Canis Majoris collected by Shiraz Biruni Observatory.     

Cross-Cultural Adaptation of the Female Genital Self-Image Scale (FGSIS) in Iranian Female College Students

The aim of the present study was to investigate the psychometric properties of a translated and culturally adapted Iranian version of the Female Genital Self-Image Scale (FGSIS-I) in a sample of college women. Further, the relationship between women's self-image, body appreciation, sexual functioning, and gynecological exam behavior was explored. A sample of 1,877 female students from five different universities across Qazvin and Tehran completed the Female Sexual Function Index (FSFI), the Body Appreciation Scale (BAS), the Rosenberg Self-Esteem Scale (RSES), the FGSIS-I, and a gynecological exam behavior questionnaire. Good to excellent internal consistency reliability, test-retest reliability, and convergent and construct validity were found. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) both provided a two-factor structure for the FGSIS-I. The validity of the FGSIS-I in predicting gynecological exam behavior of college women was tested using structural equation modeling (SEM). The final model accounted for 33% of the variance in gynecological exam behavior (p < 0.01). In conclusion, the FGSIS-I was found to be a highly valid and reliable instrument to assess female genital self-image in Iranian women.     

Shape bias of robust covariance estimators: an empirical study

Detecting outliers in a multivariate point cloud is not trivial, especially when dealing with a sizable fraction of contamination. Over time, it has increasingly been recognized that the safest and most feasible approach to exposing outliers starts by computing a highly robust estimator of location and scatter that can withstand a large proportion of contamination. Many such estimators have been proposed in recent years. We will compare the worst-case bias of several prominent robust multivariate estimators by means of simulation. We also propose a new tool to compare robust estimators on real data sets, and illustrate it.     

Family Focused Care for Refugees and Displaced Populations: Global Opportunities for Family Therapists

Recent global crises have created a significant increase in the number of people leaving their countries. Distress experienced by these refugees often leads to posttraumatic stress disorder and depression and can also result in psychotic disorders, substance abuse, and interpersonal violence. The World Health Organization leads the organizing of refugee services as part of a larger initiative to provide mental health services to citizens in low‐ and middle‐income countries. The World Health Organization has identified challenges in providing care, including a provider shortage, issues with how refugees access and receive care and a lack of uniformity in mental health services. By applying the values and systemic orientation of the profession, family therapists can address some of the challenges in treating mental health concerns of these at‐risk populations.     

On Properties of Percentile Bootstrap Confidence Intervals for Period Using Periodogram

Periodic functions have many applications in astronomy. They can be used to model the magnitude of light intensity of the period variable stars that their brightness vary with time. Because the data related to the astronomical applications are commonly observed at the time points that are not regularly spaced, the use of the periodogram as a good tool for estimating period is highlighted. Our bootstrap inference about period is based on maximizing the periodogram and consists of percentile two-sided bootstrap confidence intervals construction for the true period. We also obtain their coverage levels theoretically, and discuss the benefit of double-bootstrap confidence intervals for the parameter by which the coverage levels are substantially improved. Precisely, we show that the coverage error of single-bootstrap confidence intervals is of order n ^?1, decreasing to order n ^?2 when applying double-bootstrap methods. The simulation study given here is a numerical assessment of the theoretical work.