On the pade tablé and its relationship to the r and sarrays and arm a modeling

The Box-Jenkins method is a popular and important technique for modeling and forecasting of time series. Unfortunately the problem of determining the appropriate ARMA forecasting model (or indeed if an ARMA model holds) is a major drawback to the use of the Box-Jenkins methodology. Gray et al. (1978) and Woodward and Gray (1979) have proposed methods of estimating p and qin ARMA modeling based on the R and Sarrays that circumvent some of these modeling difficulties.

In this paper we generalize the R and S arrays by showing a relationship to Padé approximunts and then show that these arrays have a much wider application than in just determining model order. Particular non-ARMA models can be identified as well. This includes certain processes that consist of deterministic functions plus ARMA noise, indeed we believe that the combined R and S arrays are the best overall tool so fur developed for the identification of general 2nd order (not just stationary) time scries models.     

Confidence intervals for n in the exponential order statistics problem

A simplified proof of the basic properties of the estimators in the Exponential Order Statistics (Jelinski-Moranda) Model is given. The method of constructing confidence intervals from hypothesis tests is applied to find conservative confidence intervals for the unknown parameters in the model.     

The Classification and Ordering of Responses to the Question “Who am I?”*

The question “Who Am I?” (WAI?) has generated considerable research by social psychologists concerned with self phenomena. “Self theory,” from which the “WAI?” technique was derived, hypothesizes an ordinal pattern among consensual self statements. Our data do not confirm this hypothesis nor do they confirm the widespread assumptions of a direct relationship between the salience and importance of self statements or between salience and positively evaluated self statements. We discuss the implications of these findings for the principles of “self theory” and for the validity and reliability of the “WAI?” question.     

Household Telephone Service and Usage Patterns in the United states in 2004: Implications for Telephone Samples

Changes in the U.S. telephone system, especially the rapid growthin the prevalence and use of cell phones, raise concerns aboutundercoverage error in random digit dial (RDD) telephone samples.A supplement to the Current Population Survey (CPS) was conductedin 2004 to examine telephone service and usage in U.S. households.This article explores the potential for biases in RDD surveysresulting from the increases in cell phones by presenting estimatesof the percentage of households with different types of telephoneservice, including the percentage of cell-only households, andgiving demographic profiles of households by type of telephoneservice. Logistic regression models examine variables that predictwhether households are without a telephone or only have cellphones. These predictors may be used for weighting adjustmentsto reduce undercoverage biases. We address some additional issues,including the wording of questions for measuring telephone service,that are relevant if telephone-sampling methods are revisedto include cell phones. The estimates from the CPS supplementare also used to help understand some of the new sampling andweighting problems associated with selecting samples from cellphone numbers.     

Changing patterns of migration between metropolitan and nonmetropolitan areas in the United States: Recent evidence

Data from the 1975 Current Population Survey confirm that, during 1970–1975, there was a reversal of the traditional net migration stream between metropolitan and nonmetropolitan areas in the United States. During this period, there was net in-migration of 1,600,000 persons to nonmetropolitan areas, in contrast to net out-migration of 350,000 persons from these areas in 1965–1970. Reversal was caused by a 12 percent decrease in the number of nonmetropolitan out-migrants and a 23 percent increase in the number of SMSA residents moving to nonmetropolitan territory over 1965–1970 levels. While some changes in the size of migration streams were due to changes in age structures and population bases in metropolitan and nonmetropolitan areas, they were caused primarily by real shifts in outmigration propensities at practically all ages in both areas.     

A FINE-TUNED ESTIMATOR OF A GENERAL CONVERGENCE RATE

A general rate estimation method based on the in‐sample evolution of appropriately chosen diverging/converging statistics has recently been proposed by D.N. Politis [C. R. Acad. Sci. Paris, Ser. I, vol. 335, pp. 279–282, 2002] and T. McElroy & D.N. Politis [Ann. Statist., vol. 35, pp. 1827–1848, 2007]. In this paper, we show how a modification of the original estimators achieves a competitive rate of convergence. The modified estimators require the choice of a tuning parameter; an optimal such choice is generally a non‐trivial problem in practice. Some discussion to that effect is given, as well as a small simulation study in a heavy‐tailed setting.