Propriedades e aspectos geométricos de estimadores tipo James-Stein e do estimador de Hartigan

The James-Stein estimator is a biased shrinkage estimator with uniformly smaller risk than the risk of the sample mean estimator for the mean of multivariate normal distribution, except in the one-dimensional or two-dimensional cases. In this work we have used more heuristic arguments and intensified the geometric treatment of the theory of James-Stein estimator. New type James-Stein shrinking estimators are proposed and the Mahalanobis metric used to address the James-Stein estimator. . To evaluate the performance of the estimator proposed, in relation to the sample mean estimator, we used the computer simulation by the Monte Carlo method by calculating the mean square error. The result indicates that the new estimator has better performance relative to the sample mean estimator.

A Bayesian analysis for spatial processes with application to mapping

In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

A generalized Stein's estimation approach to speech enhancement based on perceptual criteria

We address the problem of speech enhancement using a risk- estimation approach. In particular, we propose the use the Stein’s unbiased risk estimator (SURE) for solving the problem. The need for a suitable finite-sample risk estimator arises because the actual risks invariably depend on the unknown ground truth. We consider the popular mean-squared error (MSE) criterion first, and then compare it against the perceptually-motivated Itakura-Saito (IS) distortion, by deriving unbiased estimators of the corresponding risks. We use a generalized SURE (GSURE) development, recently proposed by Eldar for MSE. We consider dependent observation models from the exponential family with an additive noise model,and derive an unbiased estimator for the risk corresponding to the IS distortion, which is non-quadratic. This serves to address the speech enhancement problem in a more general setting. Experimental results illustrate that the IS metric is efficient in suppressing musical noise, which affects the MSE-enhanced speech. However, in terms of global signal-to-noise ratio (SNR), the minimum MSE solution gives better results.

AN OPTIMUM SHRINKAGE ESTIMATOR BASED ON MINIMUM-PROBABILITY-OF-ERROR CRITERION AND APPLICATION TO SIGNAL DENOISING

We address the problem of designing an optimal pointwise shrinkage estimator in the transform domain, based on the minimum probability of error (MPE) criterion. We assume an additive model for the noise corrupting the clean signal. The proposed formulation is general in the sense that it can handle various noise distributions. We consider various noise distributions (Gaussian, Student's-t, and Laplacian) and compare the denoising performance of the estimator obtained with the mean-squared error (MSE)-based estimators. The MSE optimization is carried out using an unbiased estimator of the MSE, namely Stein's Unbiased Risk Estimate (SURE). Experimental results show that the MPE estimator outperforms the SURE estimator in terms of SNR of the denoised output, for low (0 -10 dB) and medium values (10 - 20 dB) of the input SNR.

Office of the University President Sous fonds: Dr. James A. Gibson

Dr. James A. Gibson was born in Ottawa on January 29, 1912 to John W. and Belle Gibson. At an early age the family moved to Victoria, B.C. where John W. Gibson was a director of the Elementary Agricultural Education Branch, Department of Education. Gibson received his early education in Victoria, receiving a B.A. (honours) at UBC in 1931. In 1931 he was awarded the Rhodes scholarship and received his B.A., M.A., B.Litt and D. Phil at New College, Oxford. This was to be the beginning of a long and dedicated relationship with the Rhodes Scholar Association. Upon his return to Canada, Dr. Gibson lectured in Economics and Government at the University of British Columbia. In 1938 he was married to Caroline Stein in Philadelphia, and the same year joined the staff of the Department of External Affairs as a Foreign Service officer. Within twenty minutes of his arrival he was seconded to the Office of the Prime Minister and Secretary of State for External Affairs, W. L. Mackenzie King in charge of War Records and Liaison Officer. This was a critical time in the history of Canada, and Dr. Gibson experienced firsthand several milestones, including the Royal Visit of King George VI and Queen Elizabeth in 1939. Dr. Gibson was present at the formation of the United Nations in San Francisco in 1945, being part of the Prime Minister’s professional staff as well as attending conferences in Washington, Quebec and London as an advisor to the Canadian delegation. Gibson contributed many articles to the publication bout de papier about his experiences during these years. After his resignation in 1947, Gibson joined the staff of the fledgling Carleton College, as a lecturer. In 1949 he was appointed a professor and in 1951 became Dean of Arts and Sciences. Dr. Gibson acted as President from 1955 to 1956 upon the sudden death of Dr. MacOdrum. In 1963 Dr. Gibson accepted the invitation of the Brock University Founders’ Committee, chaired by Arthur Schmon, to become the founding president. Dr. Gibson guided the new University from a converted refrigeration plant, to an ever expanding University campus on the brow of the Niagara Escarpment. Dr. Gibson remained firmly “attached” to Brock University. Even after official retirement, in 1974, he retained the title President Emeritus. Gibson’s final official contribution was an unpublished ten year history of the University. In retirement Gibson remained active in scholarly pursuits. He was a visiting scholar at the Center of Canadian Studies, University of Edinburgh; continued his ongoing research activities focusing on W. L. Mackenzie King, the Office of the Governor General of Canada, and political prisoners transported to Van Dieman’s Land. He remained active in the Canadian Association of Rhodes Scholars, becoming editor from 1975 to 1994 and was appointed Editor Emeritus and Director for Life in 1995 in honour of his dedicated and outstanding service. In 1993 he was awarded one of Canada’s highest achievements, the Order of Canada. Gibson retained close ties with Brock University and many of its faculty. He maintained an office in the Politics Department where he became a vital part of the department. In 1996 Brock University honoured Gibson by naming the University Library in his honour. James A. Gibson Library staff was instrumental in celebrating the 90th birthday of Gibson in 2002, with a widely attended party in the Pond Inlet where many former students, including Silver Badgers. The attendees also included former and current colleagues from Brock University, Canadian Rhodes Scholars Association, family and friends. Gibson was later to remark that the highlight of this event was the gift of his original academic robe which he had personally designed in 1964. In 2003 Dr. Gibson moved to Ottawa to be near some of his children and the city of his birth and early career. In that year “two visits to Brock ensued: the first, to attend a special celebration of the James A. Gibson Library; his late to attend the 74th Convocation on Saturday, October 18, 2003. A week later, in Ottawa, he went for a long walk, returned to his residence, Rideau Gardens, went into the lounge area, took off his coat and folded it up, put it on the back of his chair, sat down, folded his hands in his lap, closed his eyes, and died”. With sources from: Carleton University The Charlatan, Gibson CV, and Memorial Service Programme

A bagging-based correction for the mixture model estimator of population size

Estimation of a population size by means of capture-recapture techniques is an important problem occurring in many areas of life and social sciences. We consider the frequencies of frequencies situation, where a count variable is used to summarize how often a unit has been identified in the target population of interest. The distribution of this count variable is zero-truncated since zero identifications do not occur in the sample. As an application we consider the surveillance of scrapie in Great Britain. In this case study holdings with scrapie that are not identified (zero counts) do not enter the surveillance database. The count variable of interest is the number of scrapie cases per holding. For count distributions a common model is the Poisson distribution and, to adjust for potential heterogeneity, a discrete mixture of Poisson distributions is used. Mixtures of Poissons usually provide an excellent fit as will be demonstrated in the application of interest. However, as it has been recently demonstrated, mixtures also suffer under the so-called boundary problem, resulting in overestimation of population size. It is suggested here to select the mixture model on the basis of the Bayesian Information Criterion. This strategy is further refined by employing a bagging procedure leading to a series of estimates of population size. Using the median of this series, highly influential size estimates are avoided. In limited simulation studies it is shown that the procedure leads to estimates with remarkable small bias.

The lumber estimator : Board and surface measure contents of fractional sizes of lumber, specially arranged for rapid estimating of contents of stock used in manufacture of doors, sash, blinds, door and window frames, interior and exterior finish, furniture, boxes, veneers, etc., etc. /

p. 113, advertising matter.

Leaver's official feetage estimator ...

Mode of access: Internet.

The American builder's general price book and estimator ... [microform] /

Mode of access: Internet.

The American builder's general price book and estimator, now first published to elucidate the principles of ascertaining the correct value of every description of artificers' work required in building, from the prime cost of materials and labour in any part of the United States ... to which are added, a variety of useful tables, memorandums, etc.

Microfilm. Ann Arbor, Mich., University Microfilms [n.d.] (American culture series, Reel 35.10)

Pooling data for pest management analysis : a Stein-rule approach /

"August 1987"--P. iii.