## SEARCH

#### Country

##### ( see all 114)

- United States [x] 10826 (%)
- USA 2438 (%)
- Canada 302 (%)
- United Kingdom 220 (%)

#### Institution

##### ( see all 3646)

- University of California 551 (%)
- Webster University 368 (%)
- Columbia University 254 (%)
- Stanford University 239 (%)
- Cornell University 229 (%)

#### Author

##### ( see all 12216)

- Quirk, Thomas J. 343 (%)
- Lehmann, E. L. 119 (%)
- Davis, Richard A. 118 (%)
- Kleinbaum, David G. 90 (%)
- Ahsanullah, Mohammad 89 (%)

#### Publication

##### ( see all 548)

- Annals of the Institute of Statistical Mathematics 939 (%)
- Journal of Medical Systems 302 (%)
- Lifetime Data Analysis 302 (%)
- Metrika 265 (%)
- Statistics and Computing 262 (%)

#### Subject

##### ( see all 213)

- Statistics [x] 10826 (%)
- Statistics, general 4624 (%)
- Statistical Theory and Methods 3887 (%)
- Statistics for Business/Economics/Mathematical Finance/Insurance 3272 (%)
- Statistics for Life Sciences, Medicine, Health Sciences 2857 (%)

## CURRENTLY DISPLAYING:

Most articles

Fewest articles

Showing 1 to 10 of 10826 matching Articles
Results per page:

## Fiducial Theory for Free-Knot Splines

### Contemporary Developments in Statistical Theory (2014-01-01) 68: 155-189 , January 01, 2014

We construct the fiducial model for free-knot splines and derive sufficient conditions to show asymptotic consistency of a multivariate fiducial estimator. We show that splines of degree four and higher satisfy those conditions and conduct a simulation study to evaluate quality of the fiducial estimates compared to the competing Bayesian solution. The fiducial confidence intervals achieve the desired confidence level while tending to be shorter than the corresponding Bayesian credible interval using the reference prior. AMS 2000 subject classifications: Primary 62F99, 62G08; secondary 62P10.

## The Method of Random Groups

### Introduction to Variance Estimation (2007-01-01): 21-106 , January 01, 2007

###
*Abstract*

The random group method of variance estimation amounts to selecting two or more samples from the population, usually using the same sampling design for each sample; constructing a separate estimate of the population parameter of interest from each sample and an estimate from the combination of all samples; and computing the sample variance among the several estimates. Historically, this was one of the first techniques developed to simplify variance estimation for complex sample surveys. It was introduced in jute acreage surveys in Bengal by Mahalanobis (1939, 1946), who called the various samples *interpenetrating samples*. Deming (1956), the United Nations Subcommission on Statistical Sampling (1949), and others proposed the alternative term *replicated samples*. Hansen, Hurwitz, and Madow (1953) referred to the *ultimate cluster* technique in multistage surveys and to the *random group* method in general survey applications. Beginning in the 1990s, various writers have referred to the *resampling* technique. All of these terms have been used in the literature by various authors, and all refer to the same basic method. We will employ the term *random group* when referring to this general method of variance estimation.

## Dickey-Fuller Tests

### International Encyclopedia of Statistical Science (2011-01-01): 385-388 , January 01, 2011

## Nonparametric Bayes Estimation

### Bayesian Theory and Methods with Applications (2011-01-01) 1: 79-121 , January 01, 2011

For a long time there were a lot of unsuccessful efforts directed toward the solution of many nonparametric problems with the help of the Bayes approach. This can be explained mainly by difficulties a researcher encounter, when he attempts to find a suitable prior distribution, determined on a sample space. Such a distribution in nonparametric problems is chosen in the form of a set of probability distributions on the given sample space. The first work in this field where some progress has been achieved belongs to Ferguson. Ferguson formulated the requirements which must be imposed on a prior distribution

## Multivariate Time Series

### Introduction to Time Series and Forecasting (2016-01-01): 227-257 , January 01, 2016

Many time series arising in practice are best considered as components of some vector- valued (multivariate) time series {*X*_{t}} having not only serial dependence within each component series {*X*_{ti}} but also interdependence between the different component series {*X*_{ti}} and {*X*_{tj}}, *i* ≠ *j*. Much of the theory of univariate time series extends in a natural way to the multivariate case; however, new problems arise.

## Components of Statistics

### International Encyclopedia of Statistical Science (2011-01-01): 274-275 , January 01, 2011

## Web-based Multi-center Data Management System for Clinical Neuroscience Research

### Journal of Medical Systems (2010-02-01) 34: 25-33 , February 01, 2010

Modern clinical research often involves multi-center studies, large and heterogeneous data flux, and intensive demands of collaboration, security and quality assurance. In the absence of commercial or academic management systems, we designed an open-source system to meet these requirements. Based on the Apache-PHP-MySQL platform on a Linux server, the system allows multiple users to access the database from any location on the internet using a web browser, and requires no specialized computer skills. Multi-level security system is implemented to safeguard the protected health information and allow partial or full access to the data by individual or class privilege. The system stores and manipulates various types of data including images, scanned documents, laboratory data and clinical ratings. Built-in functionality allows for various search, quality control, analytic data operations, visit scheduling and visit reminders. This approach offers a solution to a growing need for management of large multi-center clinical studies.

## The Spectral Analysis of Stationary Interval Functions

### Selected Works of David Brillinger (2012-01-01): 25-55 , January 01, 2012

We consider stationary. additive. interval functions X(Δ). These are vector valued stochastic processes having real intervals Δ = (α, β] as domain, having finite dimensional distributions invariant under time translation and satisfying

## Front Matter - The SPSS Guide to the New Statistical Analysis of Data

### The SPSS Guide to the New Statistical Analysis of Data (1997-01-01) , January 01, 1997

## The Utility of the Hui-Walter Paradigm for the Evaluation of Diagnostic Test in the Analysis of Social Science Data

### Diagnosis and Prediction (1999-01-01) 114: 7-29 , January 01, 1999

Just as in medical research, social scientists are concerned with the correct classification of individuals into well defined categories. Many economic policy decisions rely on the unemployment rate and related labor statistics. As the unemployment rate is the ratio of the estimated number of unemployed persons to the total labor force, misclassification of survey respondents may lead to an under or over estimate of it. Thus, estimating the accuracy of the original interview is quite important and the Census Bureau conducts a special reinterview study of about 20,000 respondents per year to monitor their error rates. In law, a large body of research (Hans and Vidmar; 1991, Blank and Rosenthal; 1991) has raised questions about how well the jury functions. The basic problem can be placed in the classification frame work. How well does the current system perform in correctly determining that a guilty party is found guilty and in not convicting an individual who should be acquitted ? This article reports some exploratory work we have carried out on extending and modifying the Hui-Walter methodology for evaluating the accuracy of diagnostic tests (see Vianna, 1995, for related work) to enable us to estimate the accuracy of the labor force data and to reanalyze a classic study (Kalven and Zeisel, 1966) of judge-jury agreements to estimate the accuracy of jury verdicts.