Some New Robust Estimators for Circular Logistic Regression Model with Applications on Meteorological and Ecological Data

Maximum likelihood estimation (MLE) is often used to estimate the parameters of the circular logistic regression model due to its efficiency under a parametric model. However, evidence has shown that the classical MLE extremely affects the parameter estimation in the presence of outliers. This article discusses the effect of outliers on circular logistic regression and extends four robust estimators, namely, Mallows, Schweppe, Bianco and Yohai estimator BY, and weighted BY estimators, to the circular logistic regression model. These estimators have been successfully used in linear logistic regression models for the same purpose. The four proposed robust estimators are compared with the classical MLE through simulation studies. They demonstrate satisfactory finite sample performance in the presence of misclassified errors and leverage points. Meteorological and ecological datasets are analyzed for illustration

Inverse power Ramos–Louzada distribution with various classical estimation methods and modeling to engineering data

This work uses the inverse-power transformation to create the inverse power Ramos–Louzada distribution (IPRLD), a novel two-parameter version of the Ramos–Louzada distribution. The failure rate of the new distribution can be represented by a reverse bathtub shape, a rising shape, or a decreasing shape, making it appropriate for a range of real data. Asymmetrical and unimodal densities can be produced via the IPRLD. Its mathematical characteristics are computed in some cases. The novel proposed model’s structural characteristics are derived. To estimate the model parameters, several estimating strategies are explored, including ten classical methods. Simulation results with their partial and total ranks are used to evaluate the ranking and behavior of various approaches. Finally, two real-world datasets are used to experimentally show the suggested distribution’s adaptability. The analysis of the data reveals that the introduced distribution offers a better fit than some significant rival distributions, including the inverse Ramos–Louzada, inverse power Burr Hatke, inverse Nakagami-M, inverse log-logistic, inverse weighted Lindley, inverse Lindley, and Ramos–Louzada

Estimation of Constant Stress Partially Accelerated Life Test for Fréchet Distribution with Type-I Censoring

Modern reliability engineering accelerated life tests (ALT) and partially accelerated life tests (PALT) are widely used to obtain the timely information on the reliability of objects, products, elements, and materials as well as to save time and cost. The ALTs or PALTs are useful in determining the failed manners of the items at routine conditions by using the information of the data generated from the experiment. PALT is the most sensible method to be used for estimating both ordinary and ALTs. In this research, constant stress PALT design for the Fréchet distribution with type-I censoring has been investigated due to a wide applicability of the Fréchet distribution in engineering problems especially in hydrology. The distribution parameters and acceleration factor are obtained by using the maximum likelihood method. Fisher's information matrix is used to develop the asymptotic confidence interval estimates of the model parameters. A simulation study is conducted to illustrate the statistical properties of the parameters and the confidence intervals by using the R software. The results indicated that the constant stress PALT plan works well. Moreover, a numerical example is given to exemplify the performance of the proposed methods

The prevalence of sedentary behavior among university students in Saudi Arabia

Abstract Background A considerable body of research has demonstrated that reducing sitting time benefits health. Therefore, the current study aimed to explore the prevalence of sedentary behavior (SB) and its patterns. Methods A total of 6975 university students (49.1% female) were chosen randomly to participate in a face-to-face interview. The original English version of the sedentary behavior questionnaire (SBQ) was previously translated into Arabic. Then, the validated Arabic version of the SBQ was used to assess SB. The Arabic SBQ included 9 types of SB (watching television, playing computer/video games, sitting while listening to music, sitting and talking on the phone, doing paperwork or office work, sitting and reading, playing a musical instrument, doing arts and crafts, and sitting and driving/riding in a car, bus or train) on weekdays and weekends. Results SBQ indicated that the total time of SB was considerably high (478.75 ± 256.60 and 535.86 ± 316.53 (min/day) during weekdays and weekends, respectively). On average, participants spent the most time during the day doing office/paperwork (item number 4) during weekdays (112.47 ± 111.11 min/day) and weekends (122.05 ± 113.49 min/day), followed by sitting time in transportation (item number 9) during weekdays (78.95 ± 83.25 min/day) and weekends (92.84 ± 100.19 min/day). The average total sitting time of the SBQ was 495.09 ± 247.38 (min/day) and 58.4% of the participants reported a high amount of sitting time (≥ 7 hours/day). Independent t-test showed significant differences (P ≤ 0.05) between males and females in all types of SB except with doing office/paperwork (item number 4). The results also showed that male students have a longer daily sitting time (521.73 ± 236.53 min/day) than females (467.38 ± 255.28 min/day). Finally, 64.1% of the males reported a high amount of sitting time (≥ 7 hours/day) compared to females (52.3%). Conclusion In conclusion, the total mean length of SB in minutes per day for male and female university students was considerably high. About 58% of the population appeared to spend ≥7 h/day sedentary. Male university students are likelier to sit longer than female students. Our findings also indicated that SB and physical activity interventions are needed to raise awareness of the importance of adopting an active lifestyle and reducing sitting time