Distribution-free prediction intervals for the future current record statistics

Prediction of records plays an important role in many applications, such as, meteorology, hydrology, industrial stress testing and athletic events. In this paper, based on the observed current records of an iid sequence sample drawn from an arbitrary unknown distribution, we develop distribution-free prediction intervals as well as prediction upper and lower bounds for current records from another iid sequence. We also present sharp upper bounds for the expected lengths of the so obtained prediction intervals. Numerical computations of the coverage probabilities are presented for choosing the appropriate limits of the prediction intervals.      

Decision Models for Robot Selection: A Comparison of Ordinary Least Squares and Linear Goal Programming Methods

The profusion of robot designs, the cost of testing, and the fact that robot operational parameter maximums are often mutually exclusive are factors that create a complex selection decision for the potential user. While formal robot testing standards are now in place, formal techniques to select robots for the testing process have not been addressed. A linear goal programming model is an effective tool for the decision maker for optimizing the robot selection process in terms of requirement priorities. It is also shown that this model provides a more stable result than the ordinary least squares estimator in the presence of statistical outliers of robot parameters. The methodology is illustrated through the use of current robot specifications.     

Validity of the microsoft kinect system in assessment of compensatory stepping behavior during standing and treadmill walking

Background

Rapid compensatory stepping plays an important role in preventing falls when balance is lost; however, these responses cannot be accurately quantified in the clinic. The Microsoft Kinect? system provides real-time anatomical landmark position data in three dimensions (3D), which may bridge this gap.

Methods

Compensatory stepping reactions were evoked in 8 young adults by a sudden platform horizontal motion on which the subject stood or walked on a treadmill. The movements were recorded with both a 3D-APAS motion capture and Microsoft Kinect? systems. The outcome measures consisted of compensatory step times (milliseconds) and length (centimeters). The average values of two standing and walking trials for Microsoft Kinect? and the 3D-APAS systems were compared using t-test, Pearson’s correlation, Altman-bland plots, and the average difference of root mean square error (RMSE) of joint position.

Results

The Microsoft Kinect? had high correlations for the compensatory step times (r?=?0.75–0.78, p?=?0.04) during standing and moderate correlations for walking (r?=?0.53–0.63, p?=?0.05). The step length, however had a very high correlations for both standing and walking (r?>?0.97, p?=?0.01). The RMSE showed acceptable differences during the perturbation trials with smallest relative error in anterior-posterior direction (2-3%) and the highest in the vertical direction (11–13%). No systematic bias were evident in the Bland and Altman graphs.

Conclusions

The Microsoft Kinect? system provides comparable data to a video-based 3D motion analysis system when assessing step length and less accurate but still clinically acceptable for step times during balance recovery when balance is lost and fall is initiated.

     

Repetitive group sampling plan based on the process capability index for the lot acceptance problem

An acceptance sampling plan is a method used to make a decision about acceptance or rejection of a product, based on adherence to a standard. Meanwhile, process capability indices (PCIs) have been applied in different manufacturing industries as capability measures based on specified criteria which include process departure from a target, process consistency, process yield and process loss. In this paper, a repetitive group sampling (RGS) plan based on PCI is introduced for variables’ inspection. First, the optimal parameters of the developed RGS plan are obtained considering constraints related to the risk of consumers and producers and also a double sampling plan, a multiple dependent state sampling plan and a sampling plan for resubmitted lots have been designed. Finally, after the development of variable sampling plans based on the Bayesian and exact approach, a comparison study has been performed between the developed RGS plan and other types of sampling plans and the results are elaborated.     

Factors Influencing Interorganizational Collaboration within a Disaster Relief Context

Despite the need for interorganizational collaboration within a humanitarian setting in recent years, there are a considerable number of challenges to efficient collaboration among humanitarian organizations (HOs) operating after natural disasters. Up to this point, scholars have explored the inhibitors and drivers of collaboration in a number of papers and reports that have primarily served to provide a list of factors that influence collaboration within a disaster relief context. Since each list is partial or limited, we conducted this meta-study to advance and frame knowledge on collaboration among HOs, to trace the gap of the literature and to initiate further studies on this topic. Our systematic literature review proposes a categorization of the factors influencing collaboration among HOs. It contains three clusters of factors: (1) contextual factors; (2) interorganizational factors; and (3) inner-organizational factors. In the last section, we elaborate on opportunities for future research on collaboration among HOs.     

Best linear unbiased interpolation of order statistics

We derive the best linear unbiased interpolation for the missing order statistics of a random sample using the well-known projection theorem. The proposed interpolation method only needs the first two moments on both sides of a missing order statistic. A simulation study is performed to compare the proposed method with a few interpolation methods for exponential and Lévy distributions.     

Marriage and Family Formation of the Second‐Generation Afghans in Iran: Insights from a Qualitative Study

In 2006, around 1.2 million documented Afghans remained in Iran, of whom half were second generation. This paper is based on the results of a qualitative study conducted in three settings: Tehran, Mashhad and Isfahan, and draws on data collected via 80 in‐depth interviews and six focus group discussions with second generation Afghans in Iran. The aim of the paper is to explore the adaptation of second‐generation Afghans in Iran, particularly in relation to marriage and family formation. The results show that educational achievements and occupational skills of the second‐generation Afghans in Iran facilitated their adaptation to the host society, and inspired different marriage and family behaviors and aspirations in comparison with the first generation.     

A characterization of geometric distribution based on weak records

Let \({\{X_n, n\geq 1\}}\) be a sequence of independent and identically distributed non-degenerated random variables with common cumulative distribution function F. Suppose X ₁ is concentrated on 0, 1, . . . , N ≤ ∞ and P(X ₁ = 1) > 0. Let \({X_{U_w(n)}}\) be the n-th upper weak record value. In this paper we show that for any fixed m ≥ 2, X ₁ has Geometric distribution if and only if \({X_{U_{w}(m)}\mathop=\limits^d X_1+\cdots+X_m ,}\) where \({\underline{\underline{d}}}\) denotes equality in distribution. Our result is a generalization of the case m = 2 obtained by Ahsanullah (J Stat Theory Appl 8(1):5–16, 2009).     

Minimal neighbor designs in circular blocks of unequal sizes

Neighbor designs have their own importance in the experiments to remove the neighbor effects where the performance of a treatment is affected by the treatments applied to its adjacent plots. If each pair of distinct treatments appears exactly once as neighbors, neighbor designs are called minimal. Most of the neighbor designs require a large number of blocks of equal sizes. In this situation minimal neighbor designs in unequal block sizes are preferred to reduce the experimental material. In this article some series are presented to construct minimal neighbor designs in circular blocks of unequal sizes.