Percentile Method Research Articles

Phenomics data processing: A plot-level model for repeated measurements to extract the timing of key stages and quantities at defined time points

• General plot-level model for repeated high-throughput field phenotyping measurements. • Extraction of three main intermediate trait categories for dynamic modelling. • Seamless processing approach that integrates temporal and spatial modelling. • Phenomics data processing cheatsheet. Decision-making in breeding increasingly depends on the ability to capture and predict crop responses to changing environmental factors. Advances in crop modeling as well as high-throughput field phenotyping (HTFP) hold promise to provide such insights. Processing HTFP data is an interdisciplinary task that requires broad knowledge on experimental design, measurement techniques, feature extraction, dynamic trait modeling, and prediction of genotypic values using statistical models. To get an overview of sources of variation in HTFP, we develop a general plot-level model for repeated measurements. Based on this model, we propose a seamless step-wise procedure that allows for carry on of estimated means and variances from stage to stage. The process builds on the extraction of three intermediate trait categories; (1) timing of key stages, (2) quantities at defined time points or periods, and (3) dose-response curves. In a first stage, these intermediate traits are extracted from low-level traits’ time series (e.g., canopy height) using P-splines and the quarter of maximum elongation rate method (QMER), as well as final height percentiles. In a second and third stage, extracted traits are further processed using a stage-wise linear mixed model analysis. Using a wheat canopy growth simulation to generate canopy height time series, we demonstrate the suitability of the stage-wise process for traits of the first two above-mentioned categories. Results indicate that, for the first stage, the P-spline/QMER method was more robust than the percentile method. In the subsequent two-stage linear mixed model processing, weighting the second and third stage with error variance estimates from the previous stages improved the root mean squared error. We conclude that processing phenomics data in stages represents a feasible approach if estimated means and variances are carried forward from one processing stage to the next. P-splines in combination with the QMER method are suitable tools to extract timing of key stages and quantities at defined time points from HTFP data.

Common causes in grassroot development: a case for community-based and community-driven response in the postpandemic era

PurposeThe purpose of this study is to determine the impact of community-based and driven approaches during the lockdowns and early periods of the pandemic. The study examines the impact and perceptions of the state-led intervention. This would help to discover a better approach for postpandemic interventions and policy responses.Design/methodology/approachThis article used the inductive method and gathered its data from surveys. In search of global opinions on COVID-19 responses received in communities, two countries in each continent with high COVID-19 infection per 100,000 during the peak period were chosen for study. In total, 13 community workers, leaders and members per continent were sampled. The simple percentile method was chosen for analysis. The simple interpretation was used to discuss the results.FindingsThe study showed that poor publicity of community-based interventions affected awareness and fame as most were mistaken for government interventions. The study found that most respondents preferred state interventions but preferred many communities or local assessments of projects and interventions while the projects were ongoing to adjust the project and intervention as they progressed. However, many preferred community-based and driven interventions.Research limitations/implicationsState secrecy and perceived opposition oppression limited data sourcing for this study in countries where state interventions are performed in secret and oppression of perceived opposition voices limited data collection in some countries. Thus, last-minute changes were made to gather data from countries on the same continent. An intercontinental study requires data from more countries, which would require more time and resources. This study was affected by access to locals in remote areas where raw data would have benefited the study.Practical implicationsThe absence of data from the two most populous countries due to government censorship limits access to over a third of the global population, as they make up 2.8 out of 7 billion.Social implicationsThe choice of two countries in each continent is representational enough, yet the absence of data from the two most populous countries creates a social identity gap.Originality/valueThe survey collected unique and genuine data and presents novel results. Thus, this study provides an important contribution to the literature on the subject. There is a need for maximum support for community-based interventions and projects as well as global data collection on community-based or driven interventions and projects.

A note on the coverage behaviour of bootstrap percentile confidence intervals for constrained parameters

The asymptotic behaviour of the commonly used bootstrap percentile confidence interval is investigated when the parameters are subject to linear inequality constraints. We concentrate on the important one- and two-sample problems with data generated from general parametric distributions in the natural exponential family. The focus of this paper is on quantifying the coverage probabilities of the parametric bootstrap percentile confidence intervals, in particular their limiting behaviour near boundaries. We propose a local asymptotic framework to study this subtle coverage behaviour. Under this framework, we discover that when the true parameters are on, or close to, the restriction boundary, the asymptotic coverage probabilities can always exceed the nominal level in the one-sample case; however, they can be, remarkably, both under and over the nominal level in the two-sample case. Using illustrative examples, we show that the results provide theoretical justification and guidance on applying the bootstrap percentile method to constrained inference problems.

Analysis of heat stress and heat wave in the four metropolitan cities of India in recent period

Cities are becoming hotter day-by-day because heat is trapped near the earth's surface due to a decrease in green cover, rapid urbanization, energy-intensity activities, and concrete structures. The four major metropolitan cities of India, i.e. Kolkata, Chennai, Delhi and Mumbai, have experienced heat waves and heat stress frequently during the summer season. This study analyses heat wave and heat stress patterns in these cities using 30 years of data from 1990 to 2019 during the summer season. We used daily maximum temperature, relative humidity, wind speed and solar radiation datasets for the above mentioned period in this study. To understand the episode of a heat wave, we have used the 95th percentile method. Furthermore, we have also used Humidity Index (HD) to evaluate the degree of discomfort and the Universal Thermal Climate Index (UTCI) to categorize the level of heat stress. The analysis indicates that the number of heat wave events in the Delhi region is 26.31%, 31.58% and 63.16% higher than Kolkata, Chennai, and Mumbai regions respectively. It is also seen that the risks of extreme heat stress and dangerous-heat stroke events in the Chennai region during heat wave periods are higher than that experienced in other metropolitan cities because of high temperature with higher values of relative humidity. The risk of extreme heat stress is less in Delhi because of lower relative humidity compared to other metropolitan cities although temperature is higher in this region. However, the risk of extreme heat stress is lower in Mumbai region because of relatively lower temperature than Chennai during summer season. The likelihood of experiencing great discomfort during heat wave periods in Kolkata city is higher than that experienced in other metropolitan cities in India, however, during non-heat wave periods the probability of extreme discomfort is higher in Chennai.

Improving the Methods for Processing Hard Rock Aquifers Boreholes’ Databases. Application to the Hydrodynamic Characterization of Metamorphic Aquifers from Western Côte d’Ivoire

Statistical analysis of a borehole database, linear discharges, and water strikes processing enabled an understanding of the structure, geometry and hydrodynamic properties of the metamorphic hard rock aquifers from the Montagnes District, Western Côte d’Ivoire. The database comprises 1654 boreholes among which 445 only were usable for this research work after its pre-processing. Analysis shows that the structure of the aquifer is similar to that observed in several other areas in the world: it developed due to weathering processes, comprises the capacitive saprolite, 10–20 m thick on average, and an underlying transmissive fractured layer, overlying the unweathered impermeable hard rock. The fractured layer is 80 m thick, the first 40 to 45 metres being its most productive zone, with a 11.3 m3/h median productivity. This research shows that metamorphic aquifers exhibit similar aquifer properties (thickness, hydrodynamic parameters) as plutonic ones and that there is interest in using such databases for research and other purposes. However, a rigorous pre-treatment of the data is mandatory, and geological data from published maps must be used instead of the geological data from the database. A previous methodology aiming at processing the boreholes’ linear discharges was improved. It notably appears that the slope method must be preferred to the percentile method.

Reliability estimation of [formula omitted]-out-of-[formula omitted] system in a multicomponent stress–strength dependent model based on copula function

In reliability analysis of the traditional stress–strength models, the stress and strength are often assumed to be independent variables. However the case where this two variables are dependent is more realistic in engineering. To evaluate multicomponent system reliability in such case, the stress and strength are assumed to have dependent Kumaraswamy variable and unit Gompertz variable based on Clayton copula. Then the maximum likelihood (ML), least squares (LS), maximum product of spacings (MPS), Cramér–von-Mises and LS (CL) hybrid estimates of the unknown parameters and system reliability are derived using two-step estimation procedure under order sample. Also the asymptotic distribution of the ML estimation and the parametric bootstrap percentile method are used to construct approximate confidence intervals (CI). Moreover, Monte Carlo simulations are implemented to compare the performance of the proposed methods. Finally, one real data set is analyzed for illustrative purposes.

The Impact of Intense Winter Saharan Dust Events on PM and Optical Properties at Urban Sites in the Southeast of the Iberian Peninsula

The influence of three Saharan dust events (SDE) on particulate matter (PM) concentrations and aerosol optical properties (AOP) during February 2021 was studied. The physical characteristics of the African aerosol were different for each episode. Therefore, the impacts of the three events on PM and AOP were analyzed separately. The monitoring sites were placed in Elche, in the southeast of the Iberian Peninsula. The sites can be classified as urban background locations. The procedure used to obtain the contribution of SDE to PM10 mass concentrations was the 40th percentile method. Nearly half of the days during the study period were under the influence of Saharan air masses. The average contribution of mineral dust (MD) to the PM10 mean concentration was ~50%, which was the highest contribution during the month of February in the last 14 years. The results show that those events characterized by a high input of fine particles (PM1 and PM2.5) caused larger increases in the absorption (σap) and scattering (σsp) coefficients than SDE in which coarse particles predominated. Nevertheless, as expected, SAE (Scattering Angström Exponent) values were lowest during these episodes. AAE (Absorption Angström Exponent) values during SDE were slightly higher than those observed in the absence of African dust, suggesting some contribution from MD to the absorption process.

Arctic air mass triggered the extreme temperature events recorded in the Laohugou ice core from the northeastern Tibetan Plateau

The frequency and the intensity of extreme temperature events have both increased globally because of the effects of climate warming. Such extreme events should be distinct in high-elevation areas owing to the phenomenon of elevation-dependent warming; however, corroborating evidence remains limited because of scarce observations. This study used the percentile method to identify annual extreme temperature events recorded in the δ18O of the Laohugou ice core (1960–2006) retrieved from the high-elevation area of the northeastern Tibetan Plateau (NETP). Comparison of these events with synchronous observations obtained at surrounding meteorological stations indicated that extreme temperature events identified from the ice core corresponded well with most temperature observations from the meteorological stations, suggesting that the δ18O record could be considered a reasonable proxy for regional temperature. However, occasional discord between the ice core and station records might reflect specific climatic shifts. Using circulation synthesis, the influencing circulation mechanism of each event was determined on the basis of differences in atmospheric parameters between each event and the average climatic state during 1970–2000. A double blocking high with warming over the Ural Mountains and east of Kuril–Kamchatka resulted in Eurasian warming, which transported warm air to the NETP and triggered the extreme high-temperature events. Conversely, a polar vortex in the Arctic led to a cold low over Eurasia, which transported cold air to the NETP causing extreme low-temperature events. The finding that variation of the Arctic air mass triggers extreme temperature events at high elevations in the NETP provides crucial insight for improved comprehension and forecasting of regional extreme temperature events.

A New Extended Cosine—G Distributions for Lifetime Studies

In this article, we introduce a new extended cosine family of distributions. Some important mathematical and statistical properties are studied, including asymptotic results, a quantile function, series representation of the cumulative distribution and probability density functions, moments, moments of residual life, reliability parameter, and order statistics. Three special members of the family are proposed and discussed, namely, the extended cosine Weibull, extended cosine power, and extended cosine generalized half-logistic distributions. Maximum likelihood, least-square, percentile, and Bayes methods are considered for parameter estimation. Simulation studies are used to assess these methods and show their satisfactory performance. The stress–strength reliability underlying the extended cosine Weibull distribution is discussed. In particular, the stress–strength reliability parameter is estimated via a Bayes method using gamma prior under the square error loss, absolute error loss, maximum a posteriori, general entropy loss, and linear exponential loss functions. In the end, three real applications of the findings are provided for illustration; one of them concerns stress–strength data analyzed by the extended cosine Weibull distribution.

Summertime Clean-Background Ozone Concentrations Derived from Ozone Precursor Relationships are Lower than Previous Estimates in the Southeast United States.

Background ozone in this study is defined as the amount of ozone that is not affected by the emissions of ozone precursors in the region of study and is transported from the distant troposphere or the stratosphere. It is one of the factors that must be considered in regional ozone control strategies. Different methods have been applied to define the background ozone level. We develop a new method based on the O3-CO-HCHO relationships, which can be applied to both observation and modeling data for regions with high isoprene emission ozone, such as the Southeast United States. We make use of the extensive aircraft and surface observations in the Southeast in the summer of 2013. Compared to the diagnostic results using the relationship of O3-NOz (total reactive nitrogen excluding nitrogen oxides), zero-emission (model-only), and 5th percentile methods, the new method is most consistent using observation or model data and the resulting background ozone concentrations are 4-50% lower than the other methods for field campaigns. Using this method, we find that the summertime background ozone at the surface is in the range of 10-15 ppbv in the inland areas of the Southeast, which is lower than that reported in previous studies. This background ozone tends to increase from urban centers to rural regions and from the surface to higher altitude due to changing ozone lifetime driven by anthropogenic emissions and dry deposition to the surface. The better quantification of background ozone using the new method highlights the importance of the contributions by natural emissions to ozone and the necessity to control anthropogenic emissions in ozone nonattainment areas of the Southeast.

"Diminishing returns" for leaves of five age-groups of Phyllostachys edulis culms.

Leaf mass (M) and lamina surface area (A) are important functional traits reported to obey a scaling relationship called "diminishing returns" (i.e., M ∝ Aα>1 ). Previous studies have focused primarily on eudicots and ignored whether the age of leaves affects the numerical value of the scaling exponent (i.e., α). The effect of age was examined using 1623 Phyllostachys edulis leaves from culms differing in age collected in Nanjing, China. The scaling relationships among leaf A, fresh mass (FM), and dry mass (DM) were evaluated using reduced major axis protocols. The bootstrap percentile method was used to test the significance of differences in α-values. Overall, the numerical values of α exceeded 1.0. The scaling relationship between FM and A was statistically more robust than that between DM and A. The scaling exponents of FM vs. A exhibited a "high-low-high-low-high" numerical trend from the oldest to the youngest age-group. FM increased linearly as culm age decreased; the leaf DM per unit area (LMA) exhibited a parabolic trend across the age-groups. "Diminishing returns" is confirmed for all but one age-group of an important monocot species. The relationship between FM and A was statistically more robust than that between DM and A for each age-group. The FM per unit A decreased with increasing age-groups, whereas the middle age-groups had a greater LMA than the oldest and youngest age-groups. These data are the first to show that the age of shoots affects the scaling relationship between leaf mass and area.

Application of genetic screening processor in screening neonatal glucose-6-phosphate dehydrogenase deficiency.

To evaluate the performance of genetic screening processor (GSP analyzer) in neonatal screening for glucose-6-phosphate dehydrogenase (G6PD)deficiency. The accuracy and precision of GSP analyzer was evaluated with the control materials from National Center for Clinical Laboratories and the low and high quality G6PD control kit (fluorescence analysis). GSP analyzer and semi-automatic fluorescence immunoanalyzer (1420 analyzer) were simultaneously used to detect 2622 neonatal screening samples and 41 confirmed samples to analyze the correlation and consistency of the test results; 78 floating samples and 78 non-floating samples were detected to compare the result. A total of 1 100 384 neonatal screening samples from January 2017 to December 2018 and 855 856 neonatal screening samples from January 2019 to December 2020 were detected with 1420 analyzer and GSP analyzer, respectively. Referring to the percentile method and the expert consensus, the new cut-off value of GSP analyzer for G6PD deficiency in screening was established. The relative bias of GSP analyzer in detecting G6PD was 0.71%-4.23%; the intra assay precision was 4.34%-4.91%, the inter assay precision was 0.85%-2.12%, and the total coefficient of variation was 5.44%-5.72%. There was a significant positive correlation between G6PD activity detected by GSP analyzer and 1420 analyzer (=0.740, <0.01). Forty-one clinical confirmed patients were identified by both 1420 analyzer and GSP analyzer (=0.945). The G6PD activity in floating dry blood spots detected by 1420 analyzer was significantly lower than that in non-floating dry blood spots (<0.05), but there was no significant difference in G6PD activity between floating and non-floating dry blood spots detected by GSP analyzer (>0.05). The sensitivities of GSP analyzer and 1420 analyzer in screening G6PD deficiency were both 100.00%, and the specificities were both more than 99.80%. Compared with 1420 analyzer, the positive predictive value, positive rate and prevalence of G6PD deficiency detected by GSP analyzer were increased, and the false positive rate was decreased (all <0.01). The new cut-off value was 26.1 U/dL for male and 29.1 U/dL for female according to the 99.1% percentile of the population. GSP analyzer has better detection performance with high automation, efficiency and throughput, which can be used in large-scale screening for neonatal G6PD deficiency.

Association between Helicobacter pylori antibody-positive status and extragastric diseases in Japanese junior high school students.

Helicobacter pylori (H.pylori) infection causes various extragastric diseases. Its transmission route has still not been clarified. However, no large-scale studies have examined the extragastric diseases caused by H.pylori in adolescents. This study aimed to examine the association of H.pylori infection with anemia, serum cholesterol levels, physique, and birth delivery method (vaginal or cesarean) in a large number of Japanese adolescents. From 2016 to 2018, we screened 2,399 adolescents (aged 13-15years) in their second and third years of junior high school using an enzyme-linked immunosorbent assay-based antibody test. Red blood cells, hemoglobin, hematocrit, total cholesterol, high-density lipoprotein (HDL) cholesterol, and serum antibody levels were measured. Hemoglobin and hematocrit levels were significantly lower in the H.pylori antibody-positive group than in the H.pylori antibody-negative group in both sexes (boys: P = 0.0004 and 0.0022; girls: P = 0.0019 and 0.0005, respectively). Total cholesterol and non-HDL cholesterol levels were significantly higher in the H. pylori-positive group than in the H.pylori-negative group among boys (P = 0.0370 and 0.0293 respectively). There was no significant difference in body mass index percentile and birth delivery method between the H.pylori-positive and H.pylori-negative groups in both boys and girls. Among Japanese junior high school students, H.pylori antibody-positive status was associated with anemia in both sexes while total cholesterol and non-HDL cholesterol levels were associated among boys. There was no association between H.pylori antibody status, body mass index percentile, and birth-delivery method.

Mixed Topp-Leone-Kumaraswamy distribution

In this article, a new generalization of the Topp-Leone distribution with a unit interval, namely Mixed Topp-Leone-Kumaraswamy distribution is defined and studied. The mathematical properties of this mixing distribution are described. Moments, quantile function, R?nyi entropy, incomplete moments and moments of residual are obtained for the new Mixed Topp-Leone - Kumaraswamy distribution. The maximum likelihood (MLE), Crans (CM) , Percentile (PM) and Particle Swarm Optimization(PSO) estimators of the parameters are derived. The percentile Method is more efficient method as compred to the others. Two real data sets are used to illustrate an application and superiority of the proposed distribution.

Assessing the hydrodynamic properties of the fissured layer of granitoid aquifers in the Tchologo Region (Northern Côte d'Ivoire)

Stratiform fissured layer within basement aquifers has increasingly been tapped because of its good transmissivity and groundwater storage capacity. This study aims to determine the hydrodynamic properties and thickness of the fissured layer of granitoids in the Tchologo region where access to drinking water has deteriorated over the years. Statistical analysis of the vertical distribution of the linear discharge from 148 boreholes measured from the length below the base of the saprolites has made it possible to characterize the geometry of fissured layer. The useful thickness of the fissured layer was determined from the 80% percentile method. Linear discharge range from 0.0087 to 0.678 m3 h−1.m−1. The thickness of the most transmissive part of the fissured layer is between 20 and 40 m. The 40 m depth is the useful thickness of the hard-rock aquifer. The mean linear discharge and mean discharge for this useful thickness are 0.129 m3 h−1.m−1 and 5.21 m3.h-1, respectively. These results will improve the success rate of drilling in the region because it will be possible to define the average useful depth of the boreholes to be drilled.

Comparing three estimators of fuzzy reliability for one scale parameter Rayleigh distribution

This paper deals with comparing three different estimators of fuzzy reliability estimator of one scale parameter Rayleigh distribution were first of all the one scale parameter Rayleigh is defined. Afterwards, the cumulative distribution function is derived, as well as the reliability function is also found. The parameters θ is estimated by three different methods, which are maximum likelihood, and moments, as well as the third method of estimation which is called percentile method or Least Square method, where the estimator $(hat{vartheta}_{pec})$ obtained from Minimizing the total sum of the square between given C DF, and one non-parametric estimator like $hat{F}(ti,theta)=frac{i}{n+1}$ after the estimator of $(theta)$, which $(hat{theta})$ is obtained. We work on comparing different fuzzy reliability estimators and all the results are explained besides different sets of taking four sample sizes $(n= 20, 40, 60, and 80)$.

Psychosocial safety climate as a mediator between high-performance work practices and service recovery performance: an international study in the airline industry

Responding to calls for further investigation of the HRM ‘black box’, our paper examines how psychosocial safety climate (PSC), an important but understudied form of organizational climate, mediates the relationship between ability, motivation and opportunity (AMO)-enhancing HPWPs and service recovery performance (SRP). We conducted a quantitative survey amongst flight attendants in Canada, Germany and France, which yielded 1664 valid answers. Using AMOS software V.24, the structural equation method was used to test our model. The method of Monte Carlo (parametric bootstrap) and more precisely bias corrected percentile method was used to test the mediation mechanism, based on 5,000 bootstrapping and 95% confidence intervals. Our results show that each AMO-enhancing HR bundle directly influences PSC and indirectly influences SRP via PSC. They also reveal a direct relationship between PSC and SRP.

Robot-assisted Versus Open Radical Cystectomy in Bladder Cancer: An Economic Evaluation Alongside a Multicentre Comparative Effectiveness Study

BackgroundOpen radical cystectomy (ORC) is regarded as the standard treatment for muscle-invasive bladder cancer, but robot-assisted radical cystectomy (RARC) is increasingly used in practice. A recent study showed that RARC resulted in slightly fewer minor but slightly more major complications, although the difference was not statistically significant. Some differences were found in secondary outcomes favouring either RARC or ORC. RARC use is expected to increase in coming years, which fuels the debate about whether RARC provides value for money. ObjectiveTo assess the cost-effectiveness of RARC compared to ORC in bladder cancer. Design, setting, and participantsThis economic evaluation was performed alongside a prospective multicentre comparative effectiveness study. We included 348 bladder cancer patients (ORC, n = 168; RARC, n = 180) from 19 Dutch hospitals. Outcome measurements and statistical analysisOver 1 yr, we assessed the incremental cost per quality-adjusted life year (QALY) gained from both healthcare and societal perspectives. We used single imputation nested in the bootstrap percentile method to assess missing data and uncertainty, and inverse probability of treatment weighting to control for potential bias. Deterministic sensitivity analyses were performed to explore the impact of various parameters on the cost difference. Results and limitationsThe mean healthcare cost per patient was €17 141 (95% confidence interval [CI] €15 791–€18 720) for ORC and €21 266 (95% CI €19 163–€23 650) for RARC. The mean societal cost per patient was €18 926 (95% CI €17 431–€22 642) for ORC and €24 896 (95% CI €21 925–€31 888) for RARC. On average, RARC patients gained 0.79 QALYs (95% CI 0.74–0.85) compared to 0.81 QALYs (95% CI 0.77–0.85) for ORC patients, resulting in a mean QALY difference of −0.02 (95% CI −0.05 to 0.02). Using a cost-effectiveness threshold of €80 000, RARC was cost-effective in 0.6% and 0.2% of the replications for the healthcare and societal perspectives, respectively. ConclusionsRARC shows no difference in terms of QALYs, but is more expensive than ORC. Hence, RARC does not seem to provide value for money in comparison to ORC. Patient summaryThis study assessed the relation between costs and effects of robot-assisted surgery compared to open surgery for removal of the bladder in 348 Dutch patients with bladder cancer. We found that after 1 year, the two approaches were similarly effective according to a measure called quality-adjusted life years, but robot-assisted surgery was much more expensive.This trial was prospectively registered in the Netherlands Trial Register as NTR5362 (https://www.trialregister.nl/trial/5214).

First Estimation of Reference Intervals for Thyroid-Stimulating Hormone and Thyroid Hormones in Slovenian Population

For thyroid function estimation and clinical decision making, use of appropriate reference intervals for thyroid-stimulating hormone (TSH), free thyroxine (fT4) and free triiodothyronine (fT3) is crucial. For each laboratory, establishment of own reference intervals is advised. For the first Slovenian estimation of reference intervals for thyroid hormones a large group of 1722 healthy individuals without thyroid disease was established retrospectively. Hormone analyses were performed on automated analyser Advia Centaur XP Immunoassay System (Siemens Healthineers), which reference intervals for TSH, fT4 and fT3 were 0.55-4.78 mIU/L, 11.5-22.7 pmol/L, and 3.5-6.5 pmol/L, respectively. Statistical analysis followed non-parametric percentile method. Our laboratory reference intervals for TSH, fT4 and fT3 are mostly narrower than intervals given by manufacturer. Median value, lower and upper limit for TSH, fT4 and fT3 were 1.98 (0.59-4.23) mIU/L, 14.5 (11.3-18.8) pmol/L and 4.82 (3.79-6.05) pmol/L, respectively. Most likely, an inclusion of a high number of healthy individuals without thyroid disease was a reason for such results.

Generalized Inference on Stress-Strength Reliability in Generalized Pareto Model

The article focuses on the inference of stress-strength reliability in generalized Pareto model using the generalized variable approach and bootstrap percentile method. Simulation studies are conducted to obtain expected lengths and coverage probabilities of confidence intervals constructed using the generalized variable and the bootstrap percentile methods. An example consisting of real stress-strength data is also presented for illustrative purposes.