Search NASA⌕ Search

SEARCH · Search NASA

Results for “randomized sampling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Defect Formation under Nitrogen-Ion Implantation and Subsequent Annealing in GaAs Structures with an Uncovered Surface and a Surface Covered with an AlN Film

The concentration profiles of defects produced in structures upon the implantation of nitrogen ions into GaAs epitaxial layers with an uncovered surface and that covered with an AlN film and subsequent annealing are studied. The ion energies and the implantation doses are chosen so that the nitrogen-atom concentration profiles coincided in structures of both types. Rutherford proton backscattering spectra are measured in the random and channeling modes, and the concentration profiles of point defects formed are calculated for the samples under study. It is found that the implantation of nitrogen ions introduces nearly the same number of point defects into structures of both types, and the formation of an AlN film by ion-plasma sputtering is accompanied by the formation of an additional number of defects. However, the annealing of structures of both types leads to nearly the same concentrations of residual defects.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Reliability, stability during long-term storage, and intra-individual variation of circulating levels of osteopontin, osteoprotegerin, vascular endothelial growth factor-A, and interleukin-17A

Background: Studies in many populations have reported associations between circulating cytokine levels and various physiological or pathological conditions. However, the reliability of cytokine measurements in population studies, which measure cytokines in multiple assays over a prolonged period, has not been adequately examined; nor has stability during sample storage or intra-individual variation been assessed. Methods: We assessed (1) analytical reliability in short- and long-term repeated measurements; (2) stability and analytical reliability during long-term sample storage, and (3) variability within individuals over seasons, of four cytokines—osteopontin (OPN), osteoprotegerin (OPG), vascular endothelial growth factor-A (VEGF-A), and interleukin-17A (IL-17A). Measurements in plasma or serum samples were made with commercial kits according to standard procedures. Estimation was performed by fitting a random or mixed effects linear model on the log scale. Results: In repeated assays over a short period, OPN, OPG, and VEGF-A had acceptable reliability, with intra- and inter-assay coefficients of variation (CV) less than 0.11. Reliability of IL-17A was poor, with inter- and intra-assay CV 0.85 and 0.43, respectively. During long-term storage, OPG significantly decayed (-33% per year; 95% confidence interval [-54, -3.7]), but not OPN or VEGF-A (-0.3% or -6.3% per year, respectively). Intra- and inter-assay CV over a long period were comparable to that in a short period except for a slight increase in inter-assay CV of VEGF-A. Within-individual variation was small for OPN and VEGF-A, with intra-class correlations (ICC) 0.68 and 0.83, respectively, but large for OPG (ICC 0.11). Conclusions: We conclude that OPN and VEGF-A can be reliably measured in a large population, that IL-17A is suitable only for small experiments, and that OPG should be assessed with caution due to degradation during storage and intra-individual variation. The overall results of our study illustrate the need for validation under relevant conditions when measuring circulating cytokines in population studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Detecting outbreaks using a spatial latent field

In this paper, we present a method for estimating the infection-rate of a disease as a spatial-temporal field. Our data comprises time-series case-counts of symptomatic patients in various areal units of a region. We extend an epidemiological model, originally designed for a single areal unit, to accommodate multiple units. The field estimation is framed within a Bayesian context, utilizing a parameterized Gaussian random field as a spatial prior. We apply an adaptive Markov chain Monte Carlo method to sample the posterior distribution of the model parameters condition on COVID-19 case-count data from three adjacent counties in New Mexico, USA. Our results suggest that the correlation between epidemiological dynamics in neighboring regions helps regularize estimations in areas with high variance (i.e., poor quality) data. Using the calibrated epidemic model, we forecast the infection-rate over each areal unit and develop a simple anomaly detector to signal new epidemic waves. Our findings show that anomaly detector based on estimated infection-rates outperforms a conventional algorithm that relies solely on case-counts.

Safta, Cosmin [Sandia National Laboratories (SNL-C↗
DOE OSTI2016

Energy budget of forming clumps in numerical simulations of collapsing clouds

We analyze the physical properties and energy balance of density enhancements in two SPH simulations of the formation, evolution, and collapse of giant molecular clouds. In the simulations, no feedback is included, so all motions are due either to the initial decaying turbulence or to gravitational contraction. We define clumps as connected regions above a series of density thresholds. The resulting full set of clumps follows the generalized energy equipartition relation, σ{sub v}/R{sup 1/2}∝Σ{sup 1/2}, where σ{sub v} is the velocity dispersion, R is the “radius,” and Σ is the column density. We interpret this as a natural consequence of gravitational contraction at all scales rather than virial equilibrium. Nevertheless, clumps with low Σ tend to show a large scatter around equipartition. In more than half of the cases, this scatter is dominated by external turbulent compressions that assemble the clumps rather than by small-scale random motions that would disperse them. The other half does actually disperse. Moreover, clump sub-samples selected by means of different criteria exhibit different scalings. Sub-samples with narrow Σ ranges follow Larson-like relations, although characterized by their respective values of Σ. Finally, we find that (i) clumps lying in filaments tend to appear sub-virial, (ii) high-density cores (n⩾10{sup 5} cm{sup 3}) that exhibit moderate kinetic energy excesses often contain sink (“stellar”) particles and the excess disappears when the stellar mass is taken into account in the energy balance, and (iii) cores with kinetic energy excess but no stellar particles are truly in a state of dispersal.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Applications of Machine Learning to Predicting Core-collapse Supernova Explosion Outcomes

Most existing criteria derived from progenitor properties of core-collapse supernovae are not very accurate in predicting explosion outcomes. We present a novel look at identifying the explosion outcome of core-collapse supernovae using a machine-learning approach. Informed by a sample of 100 2D axisymmetric supernova simulations evolved with F ornax , we train and evaluate a random forest classifier as an explosion predictor. Furthermore, we examine physics-based feature sets including the compactness parameter, the Ertl condition, and a newly developed set that characterizes the silicon/oxygen interface. With over 1500 supernovae progenitors from 9-27 M ⊙ , we additionally train an autoencoder to extract physics-agnostic features directly from the progenitor density profiles. We find that the density profiles alone contain meaningful information regarding their explodability. Both the silicon/oxygen and autoencoder features predict the explosion outcome with ≈90% accuracy. In anticipation of much larger multidimensional simulation sets, we identify future directions in which machine-learning applications will be useful beyond the explosion outcome prediction.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

Detecting high-emitting methane sources in oil/gas fields using satellite observations

Methane emissions from oil/gas fields originate from a large number of relatively small and densely clustered point sources. A small fraction of high-mode emitters can make a large contribution to the total methane emission. Here we conduct observation system simulation experiments (OSSEs) to examine the potential of recently launched or planned satellites to detect and locate these high-mode emitters through measurements of atmospheric methane columns. We simulate atmospheric methane over a generic oil/gas field (20–500 production sites of different size categories in a 50 × 50 km 2 domain) for a 1-week period using the WRF-STILT meteorological model with 1.3 × 1.3 km 2 horizontal resolution. The simulations consider many random realizations for the occurrence and distribution of high-mode emitters in the field by sampling bimodal probability density functions (PDFs) of emissions from individual sites.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Long history of Cl-36 Assessment of Graphite Waste by EDF Engineering and the Latest Suggested Developments - 17043

Prior to 2005, the EDF initial version for the radiological inventory of graphite was based on the maximum values of the measures, namely a very pessimistic way. In 2008, a scientific method was developed by EDF to evaluate the inventory by reverse activation calculation, in order to limit the overestimation. The radiological inventory computation principles can be compared to those of all engineering studies. First, the calculation is simplified by taking margins, and if the results are not satisfactory enough, some simplifications are suppressed to reduce these margins even if computation becomes more complicated. On EDF piles, the gain obtained in 2008 represented a factor 50 relative to the initial version of Cl-36, even with a very penalizing multiplicative factor for uncertainty. Today, the accurate calculation of the uncertainty no longer justifies such a factor. A gain of about 150 now occurs compared to the initial version of Cl-36. It is more than 2 orders of magnitude, which is already enough to assess again the necessary type of disposal because Cl-36 is one of the key radionuclides. After global presentation of graphite waste management in France, the paper focuses on the inventory scientific process of EDF nuclear graphite, the purity of graphite and its consequences, its particular sampling, the lessons learned, the initial method description, the link with the demonstration of the completely random point process of chlorine in nuclear graphite and the last suggested precise uncertainty computation of inventory of Cl-36. The method confirmation for concentration assessment, the history of the EDF method development and its benefits are also emphasized. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Radioactive Source Localization via Bayesian Particle Filter

In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Simulated Contrast of Two Dislocations

A three-dimensional Monte Carlo simulation algorithm is used to study the contrast of two dislocations perpendicular to the irradiated surface of an n-doped silicon sample in the electron beam induced current mode. The dislocations are positioned in the irradiation trajectory, and each of both is considered as a cylinder where the minority carrier diffusion length varies abruptly from a low inside dislocations up to a high value outside dislocations. The EBIC contrast was obtained by simulating the random diffusion of carriers generated at point-like sources randomly distributed within the generation volume. Results are analyzed on the basis of change in the generation volume in the bulk of the sample and of carrier trapping process inside dislocations. The EBIC contrast increases with the increase of the electron beam energy. It also increases when the minority diffusion length inside dislocations, or their separating distance decreases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

macroMS: Image-Guided Analysis of Random Objects by Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry

Mass spectrometry imaging is well-suited to characterizing sample surfaces for their chemical content in a spatially resolved manner. However, when the surface contains small objects with significant empty spaces between them, more efficient approaches to sample acquisition are possible. Image-guided mass spectrometry (MS) enables high-throughput analysis of a diverse range of sample types, such as microbial colonies, liquid microdroplets, and others, by recognizing and analyzing selected location targets in an image. Here, we describe an imaging protocol and macroMS, an online software suite that can be used to enhance MS measurements of macroscopic samples that are imaged by a camera or a flatbed scanner. Furthermore, the web-based tool enables users to find and filter targets from the optical images, correct optical distortion issues for improved spatial location of selected targets, input the custom geometry files into an MS device to acquire spectra at the selected locations, and finally, perform limited data analysis and use visualization tools to aid locating samples containing compounds of interest. Using the macroMS suite, an enzyme mutant library of Saccharomyces cerevisiae and nL droplet arrays of Escherichia coli and Pseudomonas fluorescens have been assayed at a rate of ~2 s/sample.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Hormonal contraception alters vaginal microbiota and cytokines in South African adolescents in a randomized trial

Young women in sub-Saharan Africa are disproportionally affected by HIV infection and unintended pregnancies. However, hormonal contraceptive (HC) use may influence HIV risk through changes in genital tract microbiota and inflammatory cytokines. To investigate this, 130 HIV negative adolescent females aged 15–19 years were enrolled into a substudy of UChoose, an open-label randomized crossover study (NCT02404038), comparing acceptability and contraceptive product preference as a proxy for HIV prevention delivery methods. Participants were randomized to injectable norethisterone enanthate (Net-En), combined oral contraceptives (COC) or etonorgesterol/ethinyl estradiol combined contraceptive vaginal ring (CCVR) for 16 weeks, then crossed over to another HC for 16 weeks. Cervicovaginal samples were collected at baseline, crossover and exit for characterization of the microbiota and measurement of cytokine levels; primary endpoints were cervical T cell activation, vaginal microbial diversity and cytokine concentrations. Adolescents randomized to COCs had lower vaginal microbial diversity and relative abundance of HIV risk-associated taxa compared to Net-En or CCVR. Cervicovaginal inflammatory cytokine concentrations were significantly higher in adolescents randomized to CCVR compared to COC and Net-En. This suggests that COC use may induce an optimal vaginal ecosystem by decreasing bacterial diversity and inflammatory taxa, while CCVR use is associated with genital inflammation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

High Entropy Protected Sharp Magnetic Transitions in Highly Disordered Spinel Ferrites

How disorder affects magnetic ordering is always an intriguing question, and it becomes even more interesting in the recently rising high entropy oxides due to the extremely high disorder density. However, due to the lack of high-quality single crystal samples, the strong compositional disorder effect on magnetic transition has not been deeply investigated. In this work, we have successfully synthesized high-quality single crystalline high entropy spinel ferrites (Mg 0.2 Mn 0.2 Fe 0.2 Co 0.2 Ni 0.2 ) x Fe 3-x O 4 . Our findings from high-temperature magnetization and neutron diffraction experiments showed ferrimagnetic transitions at 748, 694, and 674 K for x values of 1, 1.5, and 1.8, respectively. Notably, the magnetic transition almost showed no broadening for x values of 1 and 1.5, compared to Fe 3 O 4 . Extended X-ray absorption fine structure measurements provided insights into the elemental distribution among the octahedral and tetrahedral sites. The random distribution of elements across these sites reduced the formation of local clusters and short-range orders, enhancing sample homogeneity and preserving the sharpness of the magnetic transition, despite bond length variation. Here, our study not only marks the first successful synthesis of an HEO bulk single crystal exhibiting long-range magnetic order but also sheds light on the interaction between high configurational entropy and magnetic orderings. This opens new avenues for future research and applications of magnetic high entropy oxides.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Structural Studies of Amorphous Materials by Fluctuation Electron Microscopy

Fluctuation Electron Microscopy (FEM) is a technique that examines the fluctuations in electron scattering across a uniformly thin amorphous sample. The statistics of the intensity fluctuations, mean and variance, reveal any underlying medium-range order present in the structure. The goals of this project were: (1) To determine the fundamentals of the scattering physics that gives rise to the variance signal in fluctuation electron microscopy (FEM); (2) To use these discoveries to find ways to quantify FEM; (3) To apply the FEM method to interesting and technologically important families of amorphous materials, particularly those with important applications in energy-related processes. Excellent progress was made in items (1) and (2). In stage (3) we did not examine the metamict zircons, as proposed. Instead, we examined films of polycrystalline and amorphous semi-conducting diamond. Significant accomplishments are: (1) A Reverse Monte Carlo procedure was successfully implemented to invert FEM data into a structural model. This is computer-intensive, but it demonstrated that diffraction and FEM data from amorphous silicon are most consistent with a paracrystallite model. This means that there is more diamond-like topology present in amorphous silicon than is predicted by the continuous random network model. (2) There is significant displacement decoherence arising in diffraction from amorphous silicon and carbon. The samples are being bombarded by the electron beam and atoms do not stay still while being irradiated – much more than was formerly understood. The atom motions cause the destructive and constructive interferences in the diffraction pattern to fluctuate with time, and it is the time-averaged speckle that is being measured. The variance is reduced by a factor m, 4 ≤ m ≤ 1000, relative to that predicted by kinematical scattering theory. (3) Speckle intensity obeys a gamma distribution, where the mean intensity $ \overline{I}\ $ and m are the two parameters governing the shape of the gamma distribution profile. m is determined by the illumination spatial coherence, which is normally very high, and mostly by the displacement decoherence within the sample. (4) Amorphous materials are more affected by the electron beam than are crystalline materials. Different samples exhibit different disruptibility, as measured by the effective values of m that fit the data. (5) Understanding the origin of the displacement decoherence better should lead to efficient methods for computing the observed variance from amorphous materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Tools for Water Ingress Testing

The Safety Storage and Engineering Team, as part of the Production Support Services division (PSS-2), is tasked with ensuring the safety of containers used for handling and storage of nuclear materials. As part of this work, water ingress tests are conducted to evaluate the water-tightness of containers intended for in-glovebox use. In collaboration, the statistics group of the Computer and Computational Sciences Division (CCS-6) provided support in developing a statistically defensible approach for determining appropriate sample sizes for water ingress testing. Water ingress testing involves multiple measurements on multiple containers. Our approach uses a simple random effects model to analyze a pilot data set, implementing prediction limits to evaluate the efficacy of collecting additional data. Although this study capitalizes on available data, our approach can be used with estimates of the ratio of between and within variability and average values, often available from past testing or expert knowledge. An interactive Shiny tool was developed as a final user-friendly product for future testing. The Shiny interface is an open-source package providing a framework for building web applications. Raw data exploration and prediction interval-based sample size assessments can quickly be conducted by the engineering team without needing to interact with the underlying code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

Organic doping of rotated double layer graphene

Charge transfer techniques have been extensively used as knobs to tune electronic properties of two- dimensional systems, such as, for the modulation of conductivity \ mobility of single layer graphene and for opening the bandgap in bilayer graphene. The charge injected into the graphene layer shifts the Fermi level away from the minimum density of states point (Dirac point). In this work, we study charge transfer in rotated double-layer graphene achieved by the use of organic dopant, Tetracyanoquinodimethane. Naturally occurring bilayer graphene has a well-defined A-B stacking whereas in rotated double-layer the two graphene layers are randomly stacked with different rotational angles. This rotation is expected to significantly alter the interlayer interaction. Double-layer samples are prepared using layer-by-layer assembly of chemical vapor deposited single-layer graphene and they are identified by characteristic resonance in the Raman spectrum. The charge transfer and distribution of charges between the two graphene layers is studied using Raman spectroscopy and the results are compared with that for single-layer and A-B stacked bilayer graphene doped under identical conditions.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Simulated effects of sample size and grain neighborhood on the modeling of extreme value fatigue response

Assessing the size of representative volume elements (RVEs) for fatigue-related applications is challenging. A RVE relevant to random microstructure requires a volume of material that is sufficiently large to capture the grain/phase heterogeneity that captures all statistical moments of the distribution of the driving force for fatigue crack formation at “hot spot” grains. Consequently, the large size of a microstructure RVE required to study fatigue phenomena is largely computationally intractable and difficult to explore. A more realistic objective in this work is to systematically study, as a function of the size of a statistical sample of microstructure, trends towards convergence of the simulated distribution of driving force for fatigue crack formation. Our present work accordingly leverages the recently developed open-source PRISMS-Fatigue framework to examine the trends in convergence of extreme value distributions (EVD) of Fatigue Indicator Parameters (FIPs) in progressively larger polycrystalline microstructure realizations of FCC Al alloy 7075-T6 using crystal plasticity finite element method simulations. The results are compared to the traditional method in which ensembles of statistical volume elements (SVEs) are simulated to build up statistics intended to approximate those associated with a larger volume of material. The convergence of EVDs with increase of size of a SVE of microstructure is closely related to the extent of grain nearest neighbor (NN) interactions. Accordingly, the sensitivity of the local micromechanical response at hot spot grains is quantitatively investigated by systematically varying the orientations of NN grains. Results indicate that SVEs with cubic crystallographic texture tend towards convergence of the EVD of FIPs with tens of thousands of grains while the random and rolled textures require larger volumes. Simple relationships based on microstructure parameters (e.g., Schmid Factor, grain size, NN misorientation) do not completely correlate to fatigue hot spot grains. Finally, the sensitivity of the extreme value fatigue response at hot spot grains extends to the 3rd NN when a single neighborhood grain orientation is altered.

36 MATERIALS SCIENCE↗
DOE OSTI2016

Abiotic proxies for predictive mapping of nearshore benthic assemblages: implications for marine spatial planning

Marine spatial planning (MSP) should assist managers in guiding human activities toward sustainable practices and in minimizing user conflicts in our oceans. A necessary first step is to quantify spatial patterns of marine assemblages in order to understand the ecosystem's structure, function, and services. However, the large spatial scale, high economic value, and density of human activities in nearshore habitats often makes quantifying this component of marine ecosystems especially daunting. To address this challenge, we developed an assessment method that employs abiotic proxies to rapidly characterize marine assemblages in nearshore benthic environments with relatively high resolution. We evaluated this assessment method along 300 km of the State of Maine's coastal shelf (<100 m depth), a zone where high densities of buoyed lobster traps typically preclude extensive surveys by towed sampling gear (i.e., otter trawls). During the summer months of 2010–2013, we implemented a stratified-random survey using a small remotely operated vehicle that allowed us to work around lobster buoys and to quantify all benthic megafauna to species. Stratifying by substrate, depth, and coastal water masses, we found that abiotic variables explained a significant portion of variance (37–59%) in benthic species composition, diversity, biomass, and economic value. Generally, the density, diversity, and biomass of assemblages significantly increased with the substrate complexity (i.e., from sand-mud to ledge). The diversity, biomass, and economic value of assemblages also decreased significantly with increasing depth. Last, demersal fish densities, sessile invertebrate densities, species diversity, and assemblage biomass increased from east to west, while the abundance of mobile invertebrates and economic value decreased, corresponding mainly to the contrasting water mass characteristics of the Maine Coastal Current system (i.e., summertime current direction, speed, and temperature). Integrating modeled predictions with existing GIS layers for abiotic conditions allowed us to scale up important assemblage attributes to define key foundational ecological principles of MSP and to find priority regions where some bottom-disturbing activities would have minimal impact to benthic assemblages. We conclude that abiotic proxies can be strong forcing functions for the assembly of marine communities and therefore useful tools for spatial extrapolations of marine assemblages in congested (heavily used) nearshore habitats.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Two-Step Estimation in a Heteroscedastic Linear Regression Model

We study the problem of estimating a parameter in some heteroscedastic linear regression model in the case where the regressors consist of all order statistics based on the sample of identically distributed not necessarily independent observations with finite second moment. It is assumed that the random errors depend on the parameter and distributions of the corresponding regressors. We propose a two-step procedure for finding explicit asymptotically normal estimators.

97 MATHEMATICS AND COMPUTING↗