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Demand for reliable statistics at a local area (small area) level has greatly increased in recent years. Traditional area-specific estimators based on probability samples are not adequate because of small sample size or even zero sample size in a local area. As a result, methods based on models linking the areas are widely used. World Bank focused on estimating poverty measures, in particular poverty incidence and poverty gap called FGT measures, using a simulated census method, called ELL, based on a one-fold nested error model for a suitable transformation of the welfare variable. Modified ELL methods leading to significant gain in efficiency over ELL also have been proposed under the one-fold model. An advantage of ELL and modified ELL methods is that distributional assumptions on the random effects in the model are not needed. In this paper, we extend ELL and modified ELL to two-fold nested error models to estimate poverty indicators for areas (say a state) and subareas (say counties within a state). Our simulation results indicate that the modified ELL estimators lead to large efficiency gains over ELL at the area level and subarea level. Further, modified ELL method retaining both area and subarea estimated effects in the model (called MELL2) performs significantly better in terms of mean squared error (MSE) for sampled subareas than the modified ELL retaining only estimated area effect in the model (called MELL1).

Recent observations of the light component of the cosmic-ray spectrum have revealed unexpected features that motivate further and more precise measurements up to the highest energies. The Dark Matter Particle Explorer is a satellite-based cosmic-ray experiment that has been operational since December 2015, continuously collecting data on high-energy cosmic particles with very good statistics, energy resolution, and particle identification capabilities. In this work, the latest measurements of the energy spectrum of proton+helium in the energy range from 46 GeV to 464 TeV are presented. Among the most distinctive features of the spectrum, a spectral hardening at 600 GeV has been observed, along with a softening at 29 TeV measured with a 6.6{\sigma} significance. Moreover, the detector features and the analysis approach allowed for the extension of the spectral measurement up to the sub-PeV region. Even if with small statistical significance due to the low number of events, data suggest a new spectral hardening at about 150 TeV., Comment: Published on PRD

More than a century after the performance of the oil drop experiment, the possible existence of fractionally charged particles FCP still remains unsettled. The search for FCPs is crucial for some extensions of the Standard Model in particle physics. Most of the previously conducted searches for FCPs in cosmic rays were based on experiments underground or at high altitudes. However, there have been few searches for FCPs in cosmic rays carried out in orbit other than AMS-01 flown by a space shuttle and BESS by a balloon at the top of the atmosphere. In this study, we conduct an FCP search in space based on on-orbit data obtained using the DArk Matter Particle Explorer (DAMPE) satellite over a period of five years. Unlike underground experiments, which require an FCP energy of the order of hundreds of GeV, our FCP search starts at only a few GeV. An upper limit of $6.2\times 10^{-10}~~\mathrm{cm^{-2}sr^{-1} s^{-1}}$ is obtained for the flux. Our results demonstrate that DAMPE exhibits higher sensitivity than experiments of similar types by three orders of magnitude that more stringently restricts the conditions for the existence of FCP in primary cosmic rays., Comment: 19 pages, 6 figures, accepted by PRD

The measurement of the energy spectrum of cosmic ray helium nuclei from 70 GeV to 80 TeV using 4.5 years of data recorded by the DArk Matter Particle Explorer (DAMPE) is reported in this work. A hardening of the spectrum is observed at an energy of about 1.3 TeV, similar to previous observations. In addition, a spectral softening at about 34 TeV is revealed for the first time with large statistics and well controlled systematic uncertainties, with an overall significance of $4.3\sigma$. The DAMPE spectral measurements of both cosmic protons and helium nuclei suggest a particle charge dependent softening energy, although with current uncertainties a dependence on the number of nucleons cannot be ruled out., Comment: 11 pages, 13 figures, published in Phys. Rev. Lett. Add one more digit for first three columns in Table S2

In this article we propose a new variable selection method for analyzing data collected from longitudinal sample surveys. The procedure is based on the survey-weighted quadratic inference function, which was recently introduced as an alternative to the survey-weighted generalized estimating function. Under the joint model-design framework, we introduce the penalized survey-weighted quadratic inference estimator and obtain sufficient conditions for the existence, weak consistency, sparsity and asymptotic normality. To illustrate the finite sample performance of the model selection procedure, we include a limited simulation study.

Public-use survey data are an important source of information for researchers in social science and health studies to build statistical models and make inferences on the target finite population. This paper presents two general inferential tools through the pseudo empirical likelihood and the sample empirical likelihood methods. Theoretical results on point estimation and linear or nonlinear hypothesis tests involving parameters defined through estimating equations are established, and practical issues with the implementation of the proposed methods are discussed. Results from simulation studies and an application to the 2016 General Social Survey dataset of Statistics Canada show that the proposed methods work well under different scenarios. The inferential procedures and theoretical results presented in the paper make the empirical likelihood a practically useful tool for users of complex survey data., Comment: 50 pages, including 11 pages of tables

The precise measurement of the spectrum of protons, the most abundant component of the cosmic radiation, is necessary to understand the source and acceleration of cosmic rays in the Milky Way. This work reports the measurement of the cosmic ray proton fluxes with kinetic energies from 40 GeV to 100 TeV, with two and a half years of data recorded by the DArk Matter Particle Explorer (DAMPE). This is the first time an experiment directly measures the cosmic ray protons up to ~100 TeV with a high statistics. The measured spectrum confirms the spectral hardening found by previous experiments and reveals a softening at ~13.6 TeV, with the spectral index changing from ~2.60 to ~2.85. Our result suggests the existence of a new spectral feature of cosmic rays at energies lower than the so-called knee, and sheds new light on the origin of Galactic cosmic rays., Comment: 37 pages, 5 figures, published in Science Advances

The DArk Matter Particle Explorer (DAMPE), a satellite-based cosmic ray and gamma-ray detector, was launched on December 17, 2015, and began its on-orbit operation on December 24, 2015. In this work we document the on-orbit calibration procedures used by DAMPE and report the calibration results of the Plastic Scintillator strip Detector (PSD), the Silicon-Tungsten tracKer-converter (STK), the BGO imaging calorimeter (BGO), and the Neutron Detector (NUD). The results are obtained using Galactic cosmic rays, bright known GeV gamma-ray sources, and charge injection into the front-end electronics of each sub-detector. The determination of the boundary of the South Atlantic Anomaly (SAA), the measurement of the live time, and the alignments of the detectors are also introduced. The calibration results demonstrate the stability of the detectors in almost two years of the on-orbit operation.

Standard statistical methods that do not take proper account of the complexity of survey design can lead to erroneous inferences when applied to survey data due to unequal selection probabilities, clustering, and other design features. In particular, the actual type I error rates of tests of hypotheses using standard methods can be much bigger than the nominal significance level. Methods that take account of survey design features in testing hypotheses have been proposed, including Wald tests and quasi-score tests that involve the estimated covariance matrices of parameter estimates. In this paper, we present a unified approach to hypothesis testing that does not require computing the covariance matrices by constructing bootstrap approximations to weighted likelihood ratio statistics and weighted quasi-score statistics and establish the asymptotic validity of the proposed bootstrap tests. In addition, we also consider hypothesis testing from categorical data and present a bootstrap procedure for testing simple goodness of fit and independence in a two-way table. In the simulation studies, the type I error rates of the proposed approach are much closer to their nominal significance level compared with the naive likelihood-ratio test and quasi-score test. An application to data from an educational survey under a logistic regression model is also presented.

High energy cosmic ray electrons plus positrons (CREs), which lose energy quickly during their propagation, provide an ideal probe of Galactic high-energy processes and may enable the observation of phenomena such as dark-matter particle annihilation or decay. The CRE spectrum has been directly measured up to $\sim 2$ TeV in previous balloon- or space-borne experiments, and indirectly up to $\sim 5$ TeV by ground-based Cherenkov $\gamma$-ray telescope arrays. Evidence for a spectral break in the TeV energy range has been provided by indirect measurements of H.E.S.S., although the results were qualified by sizeable systematic uncertainties. Here we report a direct measurement of CREs in the energy range $25~{\rm GeV}-4.6~{\rm TeV}$ by the DArk Matter Particle Explorer (DAMPE) with unprecedentedly high energy resolution and low background. The majority of the spectrum can be properly fitted by a smoothly broken power-law model rather than a single power-law model. The direct detection of a spectral break at $E \sim0.9$ TeV confirms the evidence found by H.E.S.S., clarifies the behavior of the CRE spectrum at energies above 1 TeV and sheds light on the physical origin of the sub-TeV CREs., Comment: 18 pages, 6 figures, Nature in press, doi:10.1038/nature24475

The DArk Matter Particle Explorer (DAMPE), one of the four scientific space science missions within the framework of the Strategic Pioneer Program on Space Science of the Chinese Academy of Sciences, is a general purpose high energy cosmic-ray and gamma-ray observatory, which was successfully launched on December 17th, 2015 from the Jiuquan Satellite Launch Center. The DAMPE scientific objectives include the study of galactic cosmic rays up to $\sim 10$ TeV and hundreds of TeV for electrons/gammas and nuclei respectively, and the search for dark matter signatures in their spectra. In this paper we illustrate the layout of the DAMPE instrument, and discuss the results of beam tests and calibrations performed on ground. Finally we present the expected performance in space and give an overview of the mission key scientific goals., Comment: 45 pages, including 29 figures and 6 tables. Published in Astropart. Phys

Poverty maps are used to aid important political decisions such as allocation of development funds by governments and international organizations. Those decisions should be based on the most accurate poverty figures. However, often reliable poverty figures are not available at fine geographical levels or for particular risk population subgroups due to the sample size limitation of current national surveys. These surveys cannot cover adequately all the desired areas or population subgroups and, therefore, models relating the different areas are needed to 'borrow strength" from area to area. In particular, the Spanish Survey on Income and Living Conditions (SILC) produces national poverty estimates but cannot provide poverty estimates by Spanish provinces due to the poor precision of direct estimates, which use only the province specific data. It also raises the ethical question of whether poverty is more severe for women than for men in a given province. We develop a hierarchical Bayes (HB) approach for poverty mapping in Spanish provinces by gender that overcomes the small province sample size problem of the SILC. The proposed approach has a wide scope of application because it can be used to estimate general nonlinear parameters. We use a Bayesian version of the nested error regression model in which Markov chain Monte Carlo procedures and the convergence monitoring therein are avoided. A simulation study reveals good frequentist properties of the HB approach. The resulting poverty maps indicate that poverty, both in frequency and intensity, is localized mostly in the southern and western provinces and it is more acute for women than for men in most of the provinces., Comment: Published in at http://dx.doi.org/10.1214/13-AOAS702 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Rejoinder of "Impact of Frequentist and Bayesian Methods on Survey Sampling Practice: A Selective Appraisal" by J. N. K. Rao [arXiv:1108.2356], Comment: Published in at http://dx.doi.org/10.1214/11-STS346REJ the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)

According to Hansen, Madow and Tepping [J. Amer. Statist. Assoc. 78 (1983) 776--793], "Probability sampling designs and randomization inference are widely accepted as the standard approach in sample surveys." In this article, reasons are advanced for the wide use of this design-based approach, particularly by federal agencies and other survey organizations conducting complex large scale surveys on topics related to public policy. Impact of Bayesian methods in survey sampling is also discussed in two different directions: nonparametric calibrated Bayesian inferences from large samples and hierarchical Bayes methods for small area estimation based on parametric models., Comment: Published in at http://dx.doi.org/10.1214/10-STS346 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)

The term ``empirical predictor'' refers to a two-stage predictor of a linear combination of fixed and random effects. In the first stage, a predictor is obtained but it involves unknown parameters; thus, in the second stage, the unknown parameters are replaced by their estimators. In this paper, we consider mean squared errors (MSE) of empirical predictors under a general setup, where ML or REML estimators are used for the second stage. We obtain second-order approximation to the MSE as well as an estimator of the MSE correct to the same order. The general results are applied to mixed linear models to obtain a second-order approximation to the MSE of the empirical best linear unbiased predictor (EBLUP) of a linear mixed effect and an estimator of the MSE of EBLUP whose bias is correct to second order. The general mixed linear model includes the mixed ANOVA model and the longitudinal model as special cases.