Journal•

# Communications in Statistics-theory and Methods

Taylor & Francis

About: Communications in Statistics-theory and Methods is an academic journal. The journal publishes majorly in the area(s): Estimator & Asymptotic distribution. Over the lifetime, 12378 publications have been published receiving 133988 citations.

##### Papers published on a yearly basis

##### Papers

More filters

••

[...]

TL;DR: A method for identifying clusters of points in a multidimensional Euclidean space is described and its application to taxonomy considered and an informal indicator of the "best number" of clusters is suggested.

Abstract: A method for identifying clusters of points in a multidimensional Euclidean space is described and its application to taxonomy considered. It reconciles, in a sense, two different approaches to the investigation of the spatial relationships between the points, viz., the agglomerative and the divisive methods. A graph, the shortest dendrite of Florek etal. (1951a), is constructed on a nearest neighbour basis and then divided into clusters by applying the criterion of minimum within cluster sum of squares. This procedure ensures an effective reduction of the number of possible splits. The method may be applied to a dichotomous division, but is perfectly suitable also for a global division into any number of clusters. An informal indicator of the "best number" of clusters is suggested. It is a"variance ratio criterion" giving some insight into the structure of the points. The method is illustrated by three examples, one of which is original. The results obtained by the dendrite method are compared with those...

4,764 citations

••

[...]

TL;DR: In this article, a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, where the area of the scanning window is allowed to vary, and the baseline process may be any inhomogeneous Poisson process or Bernoulli process with intensity pro-portional to some known function.

Abstract: The scan statistic is commonly used to test if a one dimensional point process is purely random, or if any clusters can be detected. Here it is simultaneously extended in three directions:(i) a spatial scan statistic for the detection of clusters in a multi-dimensional point process is proposed, (ii) the area of the scanning window is allowed to vary, and (iii) the baseline process may be any inhomogeneous Poisson process or Bernoulli process with intensity pro-portional to some known function. The main interest is in detecting clusters not explained by the baseline process. These methods are illustrated on an epidemiological data set, but there are other potential areas of application as well.

3,027 citations

••

[...]

TL;DR: The ROSEPACK (RObust Statistical Estimation PACKAGE) as mentioned in this paper was developed by the authors and Virginia Klema at the Computer Research Center of the National Bureau of Economic Research, Inc. in Cambridge, Mass.

Abstract: The rapid development of the theory of robust estimation (Huber, 1973) has created a need for computational procedures to produce robust estimates. We will review a number of different computational approaches for robust linear regression but focus on one—iteratively reweighted least-squares (IRLS). The weight functions that we discuss are a part of a semi-portable subroutine library called ROSEPACK (RObust Statistical Estimation PACKage) that has been developed by the authors and Virginia Klema at the Computer Research Center of the National Bureau of Economic Research, Inc. in Cambridge, Mass. with the support of the National Science Foundation. This library (Klema, 1976) makes it relatively simple to implement an IRLS regression package.

1,741 citations

••

[...]

TL;DR: Using Akaike's information criterion, three examples of statistical data are reanalyzed and show reasonably definite conclusions in this paper, one is concerned with the multiple comparison problem for the means in normal populations.

Abstract: Using Akaike's information criterion, three examples of statistical data are reanalyzed and show reasonably definite conclusions. One is concerned with the multiple comparison problem for the means in normal populations. The second is concerned with the grouping of the categories in a contingency table. The third is concerned with the multiple comparison problem for the analysis of variance by the iogit model in contingency tables, Finite correction of Akaike's information criterionis also proposed.

1,570 citations

••

[...]

TL;DR: In this article, several test statistics are proposed for the purpose of assessing the goodness of fit of the multiple logistic regression model, which are obtained by applying a chi-square test for a contingency table in which the expected frequencies are determined using two different grouping strategies and two different sets of distributional assumptions.

Abstract: Several test statistics are proposed for the purpose of assessing the goodness of fit of the multiple logistic regression model. The test statistics are obtained by applying a chi-square test for a contingency table in which the expected frequencies are determined using two different grouping strategies and two different sets of distributional assumptions. The null distributions of these statistics are examined by applying the theory for chi-square tests of Moore Spruill (1975) and through computer simulations. All statistics are shown to have a chi-square distribution or a distribution which can be well approximated by a chi-square. The degrees of freedom are shown to depend on the particular statistic and the distributional assumptions. The power of each of the proposed statistics is examined for the normal, linear, and exponential alternative models using computer simulations.

1,307 citations