| 1. |
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| 2. |
- Achcar, JA, et al.
(författare)
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25 years of applied statistics
- 1998
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Ingår i: JOURNAL OF APPLIED STATISTICS. - : CARFAX PUBL CO. - 0266-4763. ; 25:1, s. 3-22
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Tidskriftsartikel (refereegranskat)
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| 3. |
- Albing, Malin, et al.
(författare)
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Elliptical safety region plots for Cpk
- 2011
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Ingår i: Journal of Applied Statistics. - : Informa UK Limited. - 0266-4763 .- 1360-0532. ; 38:6, s. 1169-1187
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Tidskriftsartikel (refereegranskat)abstract
- The process capability index C pk is widely used when measuring the capability of a manufacturing process. A process is defined to be capable if the capability index exceeds a stated threshold value, e.g. C pk >4/3. This inequality can be expressed graphically using a process capability plot, which is a plot in the plane defined by the process mean and the process standard deviation, showing the region for a capable process. In the process capability plot, a safety region can be plotted to obtain a simple graphical decision rule to assess process capability at a given significance level. We consider safety regions to be used for the index C pk . Under the assumption of normality, we derive elliptical safety regions so that, using a random sample, conclusions about the process capability can be drawn at a given significance level. This simple graphical tool is helpful when trying to understand whether it is the variability, the deviation from target, or both that need to be reduced to improve the capability. Furthermore, using safety regions, several characteristics with different specification limits and different sample sizes can be monitored in the same plot. The proposed graphical decision rule is also investigated with respect to power.
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| 4. |
- Albing, Malin, et al.
(författare)
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Skewed zero-bound distributions and process capability indices for upper specifications
- 2009
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Ingår i: Journal of Applied Statistics. - : Informa UK Limited. - 0266-4763 .- 1360-0532. ; 36:2, s. 205-221
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Tidskriftsartikel (refereegranskat)abstract
- A common practical situation in process capability analysis, which is not well developed theoretically, is when the quality characteristic of interest has a skewed distribution with a long tail towards relatively large values and an upper specification limit only exists. In such situations it is not uncommon that the smallest possible value of the characteristic is 0 and this also is the best value to obtain. Hence a target value 0 is assumed to exist. We investigate a new class of process capability indices for this situation. Two estimators of the proposed index are studied and the asymptotic distributions of these estimators are derived. Furthermore we suggest a decision procedure useful when drawing conclusions about the capability at a given significance level, based on the estimated indices and their asymptotic distributions. A simulation study is also performed, assuming that the quality characteristic is Weibull distributed, to investigate the true significance level when the sample size is finite.
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| 5. |
- Alheety, M. I., et al.
(författare)
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A new kind of stochastic restricted biased estimator for logistic regression model
- 2021
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Ingår i: Journal of Applied Statistics. - : Taylor & Francis. - 0266-4763 .- 1360-0532. ; 48:9, s. 1559-1578
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Tidskriftsartikel (refereegranskat)abstract
- In the logistic regression model, the variance of the maximum likelihood estimator is inflated and unstable when the multicollinearity exists in the data. There are several methods available in literature to overcome this problem. We propose a new stochastic restricted biased estimator. We study the statistical properties of the proposed estimator and compare its performance with some existing estimators in the sense of scalar mean squared criterion. An example and a simulation study are provided to illustrate the performance of the proposed estimator.
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| 6. |
- Almasri, Abdullah, et al.
(författare)
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An Illustration of the Causality Relation between Government Spending and Revenue Using Wavelets Analysis on Finish Data
- 2003
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Ingår i: Journal of Applied Statistics, 2003, 30, 571-584. - : Informa UK Limited. ; 30:5, s. 571-584
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Tidskriftsartikel (refereegranskat)abstract
- Quarterly data for the period 1960:1 to 1997:2, conventional tests, a bootstrap simulation approach and a multivariate Rao's F-test have been used to investigate if the causality between government spending and revenue in Finland was changed at the beginning of 1990 due to future plans to create the European Monetary Union (EMU). The results indicate that during the period before 1990, the government revenue Granger-caused spending, while the opposite happened after 1990, which agrees better with Barro's tax smoothing hypothesis. However, when using monthly data instead of quarterly data for almost the same sample period, totally different results have been noted. The general conclusion is that the relationship between spending and revenue in Finland is still not completely understood. The ambiguity of these results may well be due to the fact that there are several time scales involved in the relationship, and that the conventional analyses may be inadequate to separate out the time scale structured relationships between these variables. Therefore, to investigate empirically the relation between these variables we attempt to use the wavelets analysis that enables us to separate out different time scales of variation in the data. We find that time scale decomposition is important for analysing these economic variables.
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| 7. |
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| 8. |
- Andersson, Eva M., 1968
(författare)
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Monitoring cyclical processes. A non-parametric approach.
- 2002
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Ingår i: Journal of Applied Statistics. - : Informa UK Limited. - 0266-4763 .- 1360-0532. ; 29:7, s. 973-990
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Tidskriftsartikel (refereegranskat)abstract
- Forecasting the turning points in business cycles is important to economic and political decisions. Time series of business indicators often exhibit cycles that cannot easily be modelled with a parametric function. This article presents a method for monitoring time-series with cycles in order to detect the turning points. A non-parametric estimation procedure that uses only monotonicity restrictions is used. The methodology of statistical surveillance is used for developing a system for early warnings of cycle turning points in monthly data. In monitoring, the inference situation is one of repeated decisions. Measurements of the performance of a method of surveillance are, for example, average run length and expected delay to a correct alarm. The properties of the proposed monitoring system are evaluated by means of a simulation study. The false alarms are controlled by a fixed median run length to the first false alarm. Results are given on the median delay time to a correct alarm for two situations: a peak after two and three years respectively .
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| 9. |
- Andersson, Eva M., 1968, et al.
(författare)
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Some statistical aspects of methods for detection of turning points in business cycles
- 2006
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Ingår i: Journal of Applied Statistics. - : Informa UK Limited. - 0266-4763 .- 1360-0532. ; 33:3, s. 257-278
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Tidskriftsartikel (refereegranskat)abstract
- Methods for online turning point detection in business cycles are discussed. The statistical properties of three likelihood-based methods are compared. One is based on a Hidden Markov Model, another includes a non-parametric estimation procedure and the third combines features of the other two. The methods are illustrated by monitoring a period of the Swedish industrial production. Evaluation measures that reflect timeliness are used. The effects of smoothing, seasonal variation, autoregression and multivariate issues on methods for timely detection are discussed.
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| 10. |
- Arvidsson, M, et al.
(författare)
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Identification of factors influencing dispersion in split-plot experiments
- 2001
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Ingår i: Journal of Applied Statistics. - 0266-4763 .- 1360-0532. ; 28:3-4, s. 269-283
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Tidskriftsartikel (refereegranskat)abstract
- As split-plot designs are commonly used in robust design it is important to identify factors in these designs that influence the dispersion of the response variable. In this article, the Bergman-Hynen method, developed for identification of dispersion effects in unreplicated experiments, is modified to be used in the context of split-plot experiments. The modification of the Bergman-Hynen method enables identification of factors that influence specific variance components in unreplicated two-level fractional factorial split-plot experiments. An industrial example is used to illustrate the proposed method.
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