The use of power transformations in small area estimation

Sample surveys are usually designed and analysed to produce estimates for larger areas. Nevertheless, sample sizes are often not large enough to give adequate precision for small area estimates of interest. To overcome such difficulties, borrowing strength from related small areas via modelling becomes essential. In line with this, we propose components of variance models with power transformations for small area estimation. This paper reports the results of a study aimed at incorporating the power transformation in small area estimation for improving the quality of small area predictions. The proposed methods are demonstrated on satellite data in conjunction with survey data to estimate mean acreage under a specified crop for counties in Iowa.     

The accuracy of population projections

A review of past population projection errors is presented as a means for constructing confidence intervals for future projections. The author first defines a statistic to measure projection errors independent of the size of population and the length of the projection period. A sample of U.S. and U.N. projections is used to show that the distributions of components of the error statistic are relatively stable. This information is then used to construct confidence intervals for the U.S. population up to the year 2000.     

Review of the use of context in statistical image analysis

SUMMARY This paper is a review of the use of contextual information in statistical image analysis. After defining what we mean by 'context', we describe the Bayesian approach to high-level image analysis using deformable templates. We describe important aspects of work on character recognition and syntactic pattern recognition; in particular, aspects of the work which are relevant to scene understanding. We conclude with a review of some work on knowledge-based systems which use context to aid object recognition.     

The total bootstrap median: a robust and efficient estimator of location and scale for small samples

We propose the total bootstrap median (TBM) as a robust and efficient estimator of location and scale for small samples. We demonstrate its performance by estimating the mean and variance of a variety of distributions. We also show that, if the underlying distribution is unknown and there is either no contamination or low to moderate contamination, the TBM provides a better estimate of the mean, in mean square terms, than the sample mean or the sample median. In addition, the TBM is a better estimator of the variance of the underlying distribution than the sample variance or the square of the bias-corrected median absolute deviation from the median estimator. We also show that the TBM is an explicit L-estimator, which allows a direct study of its properties.     

Orthant probabilities of elliptical distributions from orthogonal projections to subspaces

Statistics and Computing - A new procedure is proposed for evaluating non-centred orthant probabilities of elliptical distributed vectors, which is the probabilities that all elements of a vector...     

The offender group reconviction scale: a statistical reconviction score for use by probation officers

The criminal courts in England and Wales may request the probation service to submit pre-sentence reports which are considered by magistrates and judges before making their sentencing decision. Pre-sentence reports must include an assessment of the risk of reoffending and the risk of harm to the public which the convicted offender presents. The offender group reconviction scale is a statistical aid to such risk assessment. We describe the scale and the statistical analysis on which it is based, and we discuss some statistical aspects of its interpretation and use.     

Comparison of a genetic algorithm and simulated annealing in an application to statistical image reconstruction

Genetic algorithms (GAs) are adaptive search techniques designed to find near-optimal solutions of large scale optimization problems with multiple local maxima. Standard versions of the GA are defined for objective functions which depend on a vector of binary variables. The problem of finding the maximum a posteriori (MAP) estimate of a binary image in Bayesian image analysis appears to be well suited to a GA as images have a natural binary representation and the posterior image probability is a multi-modal objective function. We use the numerical optimization problem posed in MAP image estimation as a test-bed on which to compare GAs with simulated annealing (SA), another all-purpose global optimization method. Our conclusions are that the GAs we have applied perform poorly, even after adaptation to this problem. This is somewhat unexpected, given the widespread claims of GAs' effectiveness, but it is in keeping with work by Jennison and Sheehan (1995) which suggests that GAs are not adept at handling problems involving a great many variables of roughly equal influence.We reach more positive conclusions concerning the use of the GA's crossover operation in recombining near-optimal solutions obtained by other methods. We propose a hybrid algorithm in which crossover is used to combine subsections of image reconstructions obtained using SA and we show that this algorithm is more effective and efficient than SA or a GA individually.     

A study of simulated annealing and a revised cascade algorithm for image reconstruction

We describe an image reconstruction problem and the computational difficulties arising in determining the maximum a posteriori (MAP) estimate. Two algorithms for tackling the problem, iterated conditional modes (ICM) and simulated annealing, are usually applied pixel by pixel. The performance of this strategy can be poor, particularly for heavily degraded images, and as a potential improvement Jubb and Jennison (1991) suggest the cascade algorithm in which ICM is initially applied to coarser images formed by blocking squares of pixels. In this paper we attempt to resolve certain criticisms of cascade and present a version of the algorithm extended in definition and implementation. As an illustration we apply our new method to a synthetic aperture radar (SAR) image. We also carry out a study of simulated annealing, with and without cascade, applied to a more tractable minimization problem from which we gain insight into the properties of cascade algorithms.     

Shrinkage estimation of scale in exponential distribution from censored samples

In this paper some shrunken and pretest shrunken estimators are suggested for the scale parameter of an exponential distribution, when observations become available from life test experiments. These estimators are shown to be more efficient than the usual estimator when a guessed value is nearer to the true value.     

The similarity of changes in mortality by age and their relevance to demographic projections

The similarity in mortality trends for both sexes in Poland for the period 1960-1980 is noted using correlation coefficients. The relevance of these trends for making future population projections is examined.     

C338. Misspecified location and scale. 111. the use of S2

The observed high kurtosis of stock market returns and other variables of a speculative nature has aroused interest in stable law distributions. This paper makes the point that most historical findings that returns indeed follow stable laws may have been caused by conditional heteroskedasticity. This presumption is enhanced by Monte Carlo simulations.     

Data and projections of HIV and AIDS in Portugal

Projections of AIDS incidence are critical for assessing future healthcare needs. This paper focuses on the method of back-calculation for obtaining forecasts. The first problem faced was the need to account for delays and underreporting in reporting of cases and to adjust the incidence data. The method used to estimate the reporting delay distribution is based on Poisson regression and involves cross-classifying each reported case by calendar time of diagnosis and reporting delay. The adjusted AIDS incidence data are then used to obtain short-term projections and lower bounds on the size of the AIDS epidemic. The estimation procedure 'back-calculates' from AIDS incidence data using the incubation period distribution to obtain estimates of the numbers previously infected. These numbers are then projected forward. The problem can be shown to reduce to estimating the size of a multinomial population. The expectation-maximization (EM) algorithm is used to obtain maximum-likelihood estimates when the density of infection times is parametrized as a step function. The methodology is applied to AIDS incidence data in Portugal for four different transmission categories: injecting drug users, sexual transmission (homosexual/bisexual and heterosexual contact) and other, mainly haemophilia and blood transfusion related, to obtain short-term projections and an estimate of the minimum size of the epidemic.     

Joint projections of temperature and precipitation change from multiple climate models: a hierarchical Bayesian approach

Summary.  Posterior distributions for the joint projections of future temperature and precipitation trends and changes are derived by applying a Bayesian hierachical model to a rich data set of simulated climate from general circulation models. The simulations that are analysed here constitute the future projections on which the Intergovernmental Panel on Climate Change based its recent summary report on the future of our planet's climate, albeit without any sophisticated statistical handling of the data. Here we quantify the uncertainty that is represented by the variable results of the various models and their limited ability to represent the observed climate both at global and at regional scales. We do so in a Bayesian framework, by estimating posterior distributions of the climate change signals in terms of trends or differences between future and current periods, and we fully characterize the uncertain nature of a suite of other parameters, like biases, correlation terms and model-specific precisions. Besides presenting our results in terms of posterior distributions of the climate signals, we offer as an alternative representation of the uncertainties in climate change projections the use of the posterior predictive distribution of a new model's projections. The results from our analysis can find straightforward applications in impact studies, which necessitate not only best guesses but also a full representation of the uncertainty in climate change projections. For water resource and crop models, for example, it is vital to use joint projections of temperature and precipitation to represent the characteristics of future climate best, and our statistical analysis delivers just that.     

The 50% breakdown point in simultaneous M-estimation of location and scale

Received: November 8, 1999; revised version: March 13, 2000     

CD生产函数应用于侧估隐形就业规模

隐形就业 ,主要包括未公开的兼职者、未登记的自营者、企业秘密雇工和非法职业者等 ,它又称非正规经济从业。按照国际劳工组织 (ＩＬＯ)在 1993年第15届国际劳工统计大会的“关于非正规部门就业统计的决议” ,非正规部门被定义为主要目的是为某些人创造就业和收入而提供货物和服务的生产单位。非正规部门的生产单位具有住户企业的特点 ,必须对生产过程中发生的负债承担无限责任。隐形就业规模的大小一般取决于一个国家或地区的地下经济规模。近年来 ,美国各种非公开职业者达到 2 5 0 0万人。据在美国国会研究机构任职的经济学家认为 ,1980年…     

The use of GARCH models in VaR estimation

We evaluate the performance of an extensive family of ARCH models in modeling the daily Value-at-Risk (VaR) of perfectly diversified portfolios in five stock indices, using a number of distributional assumptions and sample sizes. We find, first, that leptokurtic distributions are able to produce better one-step-ahead VaR forecasts; second, the choice of sample size is important for the accuracy of the forecast, whereas the specification of the conditional mean is indifferent. Finally, the ARCH structure producing the most accurate forecasts is different for every portfolio and specific to each equity index.