New methods for fitting multiple sinusoids from irregularly sampled data

A novel framework is proposed for the estimation of multiple sinusoids from irregularly sampled time series. This spectral analysis problem is addressed as an under-determined inverse problem, where the spectrum is discretized on an arbitrarily thin frequency grid. As we focus on line spectra estimation, the solution must be sparse, i.e. the amplitude of the spectrum must be zero almost everywhere. Such prior information is taken into account within the Bayesian framework. Two models are used to account for the prior sparseness of the solution, namely a Laplace prior and a Bernoulli–Gaussian prior, associated to optimization and stochastic sampling algorithms, respectively. Such approaches are efficient alternatives to usual sequential prewhitening methods, especially in case of strong sampling aliases perturbating the Fourier spectrum. Both methods should be intensively tested on real data sets by physicists.     

Multilevel maximum likelihood estimation with application to covariance matrices

The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of covariance models to the sample, which is important in data assimilation. The hierarchical maximum likelihood approach is applied to the spectral diagonal covariance model with different parameterizations of eigenvalue decay, and to the sparse inverse covariance model with specified parameter values on different sets of nonzero entries. It is shown computationally that using smaller sets of parameters can decrease the sampling noise in high dimension substantially.     

A surplus process involving a compound Poisson counting process and applications

Abstract

In this paper, we introduce a surplus process involving a compound Poisson counting process, which is a generalization of the classical ruin model where the claim-counting process is a homogeneous Poisson process. The incentive is to model batch arrival of claims using a counting process that is based on a compound distribution. This reduces the difficulty of modeling claim amounts and is consistent with industrial data. Recursive formula, some properties and relevant main ruin theory results are provided. Further, we consider applications involving zero-truncated negative binomial and zero-truncated binomial batch arrivals when the claim amounts follow exponential or Erlang distribution.     

Assessing the effects of land use and land cover patterns on thermal conditions using landscape metrics in city of Indianapolis,United States

Direct applications of remote sensing thermal infrared (TIR) data in landscape ecological research are rare due to limitations in the sensors, calibration, and difficulty in interpretation. Currently there is a general lack of methodology for examining the relationship between land surface temperatures (LST) derived from TIR data and landscape patterns extracted from optical sensors. A separation of landscapes into values directly related to their scale and signature is a key step. In this study, a Landsat ETM+ image of Indianapolis, Unites States, acquired on June 22, 2000, was spectrally unmixed (using spectral mixture analysis, SMA) into fraction endmembers of green vegetation, soil, high albedo, and low albedo. Impervious surface was then computed from the high and low albedo images. A hybrid classification procedure was developed to classify the fraction images into seven land use and land cover (LULC) classes. Using the fractional images, the landscape composition and pattern were examined. Next, pixel-based LST measurements were correlated with the landscape fractional components to investigate LULC based relationships between LST and impervious surface and green vegetation fractions. An examination of the relationship between the LULC and LST maps with landscape metrics was finally conducted to deepen understanding of their interactions. Results indicate that SMA-derived fraction images were effective for quantifying the urban morphology and for providing reliable measurements of biophysical variables. LST was found to be positively correlated with impervious surface fraction but negatively correlated with green vegetation fraction. Each temperature zone was associated with a dominant LULC category. Further research should be directed to the theoretical and applied implications of describing such relationships between LULC patterns and urban thermal conditions.

＂大学生素质拓展计划＂实施现状调查及对策——以西南交通大学为例

“大学生素质拓展计划”是由共青团中央、教育部、全国学联为深入推进高校素质教育而联合实施的一项系统工程。对西南交通大学的大学生进行问卷调查,发现大学生对“大学生素质拓展计划”的认知度较高,评价较好,但“计划”实施环节中的职业设计指导还存在不足之处。因此,应加强职业设计的指导力度,提高素质拓展项目质量．进一步完善其评价体系。同时加强对“计划”的实施指导和宣传力度,强化素质拓展认证工作和社会认同度,使“计划”更好地服务于学生的成长成才。     

The t-information and its use in multivariate problems and time-series analysis

The second moment of recently introduced scalar inference function can be viewed as generalized Fisher information of the continuous probability distributions. In this paper we call it the t-information and give some possible applications of the new concept.     

高等教育人口规模对经济增长的影响：地区异质性检验

近年来我国高等教育人口规模不断扩张,对经济社会产生了积极的影响。本文通过建立数理模型阐释了高等教育人口扩张对经济增长的影响机理,并使用1995年到2013年的省级面板数据考察了我国高等教育人口扩张对经济增长的作用,以及这一作用在不同地区的异质性。固定效应和随机效应模型表明,我国高等教育人口扩张促进了地区经济增长,且中西部地区的促进作用要大于东部地区。为了克服由反向因果引起的内生性偏误,本文使用2SLS方法进行了相应处理,结果依旧稳健。本文的研究对于制定高等教育发展的相关政策具有一定的参考意义。     

Inequality for equireplicated n-ary block designs with unequal block sizes

It is shown that certain inequalities known for binary, equireplicated, equiblock-sized block designs remain valid for equireplicated n-ary block designs with unequal block sizes. The approach used here is based on the spectral expansion of the C-matrix of the block design. The main theorems include some useful and combinatorially interesting results.     

Testing lack of symmetry in spatial–temporal processes

Symmetry and separability of a covariance function are common assumptions to simplify the modeling effort of spatial–temporal processes. However, many studies in environmental sciences show that real data have complex spatial–temporal dependency structures resulting from lack of symmetry or violation of other standard assumptions of the covariance function. In this study, we propose new formal tests for lack of symmetry by using spectral representations of the spatial–temporal covariance functions of regularly spaced spatial–temporal data. The advantage of the proposed tests is that classical analysis of variance (ANOVA) models can be used for detecting lack of symmetry inherent in spatial–temporal processes. We evaluate the performance of the tests with simulation studies and we apply them to air pollution data.     

非负矩阵谱半径的估计

对非负矩阵谱半径的界值给出了一个新的估计.并引进某些自由参数,使谱半径得到了更一般的结果。