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The latest content from StatisticsViews.http://www.statisticsviews.comA Panorama of Statistics: An interview with authors Eric Sowey and Peter Petocz
http://www.statisticsviews.com/details/feature/10736191/A-Panorama-of-Statistics-An-interview-with-authors-Eric-Sowey-and-Peter-Petocz.html
Earlier this year, Wiley was proud to publish A Panorama of Statistics: Perspectives, Puzzles and Paradoxes in Statistics, which offers a stimulating panoramic tour – quite different from a textbook journey – of the world of statistics in both its theory and practice, for teachers, students and practitioners.
At each stop on the tour, the authors investigate unusual and quirky aspects of statistics, highlighting historical, biographical and philosophical dimensions of this field of knowledge. Each...]]>2017-12-08T10:00:00ZDeregulating Overtime Hours Restrictions on Women and its Effects on Female Employment: Evidence from a Natural Experiment in Japan
http://www.statisticsviews.com/details/journalArticle/10736623/Deregulating-Overtime-Hours-Restrictions-on-Women-and-its-Effects-on-Female-Empl.html
Abstract
This paper provides novel evidence on the effect of deregulating overtime hours restrictions on women by using the 1985 Amendments
to the Labour Standards Act (LSA) in Japan as a natural experiment. The original LSA of 1947 prohibited women from working
overtime exceeding two hours a day; six hours a week; and 150 hours a year. The 1985 Amendments exempted a variety of occupations
and industries from such an overtime...]]>2017-12-08T04:50:48ZControl charts for monitoring the mean and percentiles of Weibull processes with variance components
http://www.statisticsviews.com/details/journalArticle/10736686/Control-charts-for-monitoring-the-mean-and-percentiles-of-Weibull-processes-with.html
Abstract
In this article, we study Shewhart and exponentially weighted moving average control charts for monitoring the mean or, equivalently,
the percentiles of a Weibull process when additional sources of variation, also known as variance components, are present.
We adopt a frailty model to describe the monitored process. We derive analytical properties for this model and use them to
develop control charts. We consider charts for...]]>2017-12-08T03:59:15ZThe performance of EWMA median and CUSUM median control charts for a normal process with measurement errors
http://www.statisticsviews.com/details/journalArticle/10736687/The-performance-of-EWMA-median-and-CUSUM-median-control-charts-for-a-normal-proc.html
Abstract
Measurement error is often occurred in statistical process control. The effect of a linearly covariate error model on the
exponentially weighted moving average (EWMA) median and cumulative sum (CUSUM) median charts is investigated. The results
indicate that the EWMA median and CUSUM median charts are significantly affected in the presence of measurement errors. We
compared the performance of the EWMA median and CUSUM median...]]>2017-12-08T03:46:57ZUnconditional analogues of Cochran–Mantel–Haenszel tests
http://www.statisticsviews.com/details/journalArticle/10736689/Unconditional-analogues-of-CochranMantelHaenszel-tests.html
Summary
The Cochran–Mantel–Haenszel tests are a suite of tests that are usually defined as conditional tests, tests that assume all
marginal totals are known before sighting the data. Here unconditional analogues of these tests are defined for the more usual
situation when the marginal totals are not known before sighting the data.]]>2017-12-08T02:13:37ZImproving the detection of unusual observations in high‐dimensional settings
http://www.statisticsviews.com/details/journalArticle/10736688/Improving-the-detection-of-unusual-observations-in-highdimensional-settings.html
Summary
Multivariate control charts are used to monitor stochastic processes for changes and unusual observations. Hotelling's T2 statistic is calculated for each new observation and an out‐of‐control signal is issued if it goes beyond the control limits.
However, this classical approach becomes unreliable as the number of variables p approaches the number of observations n, and impossible when p exceeds n. In this paper, we devise an improvement to the...]]>2017-12-08T02:11:18ZMeasuring Agreement: Models, Methods, and Applications
http://www.statisticsviews.com/details/book/10666580/Measuring-Agreement-Models-Methods-and-Applications.html
Measuring Agreement Methodology and Applications successfully blends the currently available statistical methodologies for agreement evaluation in a unified, coherent, and lucid manner. This up-to-date and comprehensive book describes the theoretical underpinnings of the methodologies and presents case studies using several real data sets to illustrate the application of the methodologies. A perfect reference for statisticians, biostatisticians, clinical chemists, and biomedical scientists]]>2017-12-08T00:00:00ZAn algorithmic hypergraph regularity lemma
http://www.statisticsviews.com/details/journalArticle/10736625/An-algorithmic-hypergraph-regularity-lemma.html
Abstract
Szemerédi 's Regularity Lemma is a powerful tool in graph theory. It asserts that all large graphs admit bounded partitions
of their edge sets, most classes of which consist of uniformly distributed edges. The original proof of this result was nonconstructive,
and a constructive proof was later given by Alon, Duke, Lefmann, Rödl, and Yuster. Szemerédi's Regularity Lemma was extended
to hypergraphs by various authors. Frankl...]]>2017-12-07T23:42:40ZTo Pool or Not to Pool: Revisited
http://www.statisticsviews.com/details/journalArticle/10736624/To-Pool-or-Not-to-Pool-Revisited.html
Abstract
This paper provides a new comparative analysis of pooled least squares and fixed effects (FE) estimators of the slope coefficients
in the case of panel data models when the time dimension (T) is fixed while the cross section dimension (N) is allowed to increase without bounds. The individual effects are allowed to be correlated with the regressors, and the
comparison is carried out in terms of an exponent coefficient, δ, which measures...]]>2017-12-07T22:56:38ZNegative Binomial Quasi‐Likelihood Inference for General Integer‐Valued Time Series Models
http://www.statisticsviews.com/details/journalArticle/10736685/Negative-Binomial-QuasiLikelihood-Inference-for-General-IntegerValued-Time-Serie.html
Two negative binomial quasi‐maximum likelihood estimates (NB‐QMLEs) for a general class of count time series models are proposed.
The first one is the profile NB‐QMLE calculated while arbitrarily fixing the dispersion parameter of the negative binomial
likelihood. The second one, termed two‐stage NB‐QMLE, consists of four stages estimating both conditional mean and dispersion
parameters. It is shown that the two estimates are consistent...]]>2017-12-07T22:51:26Z