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281.
282.
Linea Kjellsdotter Ivert 《生产规划与管理》2013,24(6):452-467
The purpose of this article is to investigate how the manufacturing process, the shop type and the data quality, i.e. the shop floor characteristics, influence the use of advanced planning and scheduling (APS) systems in production activity and control (PAC). The methodology implemented is a multiple case study at three case companies. Each company has different shop floor characteristics, but all use a scheduling module in an APS system, which supports production scheduling. A theoretical framework is developed suggesting how APS system are used in the PAC activities, and which major aspect to consider. The case analysis shows that the scheduling module in APS system, foremost supports sequencing and dispatching. In particular, the shop type is influenced by the decision of how often the APS runs and what freedom is given to the shop floor. The manufacturing process influences how the dispatch list is created. Contrary to the literature presuming that APS systems are most suitable in job shop processes, it is found that the manufacturing process is not a crucial factor when deciding whether APS systems are an appropriate investment. It is found that the level of data quality needed in the APS system depends to a large extent on how the dispatch list is used. For example, is the dispatch list used as a guideline, not a regulation, the need for accurate data in the module is reduced. This article extends the previous literature concerning APS systems by analysing how APS systems influence PAC as a whole and increase the understanding of the challenges of using APS systems in PAC. 相似文献
283.
We propose an efficient and robust method for variance function estimation in semiparametric longitudinal data analysis. The method utilizes a local log‐linear approximation for the variance function and adopts a generalized estimating equation approach to account for within subject correlations. We show theoretically and empirically that our method outperforms estimators using working independence that ignores the correlations. The Canadian Journal of Statistics 39: 656–670; 2011. © 2011 Statistical Society of Canada 相似文献
284.
货币政策与财政政策的分区域产业效应比较 总被引：1，自引：0，他引：1
在具有总量效应的同时,货币政策和财政政策在产业效应方面各自表现如何？本文运用1990～2008年东、中、西部地区的动态面板数据模型进行实证分析,结果显示：东部与中部地区的货币政策和财政政策都存在产业效应,而西部地区货币政策和财政政策的效应均不理想,同时,货币政策和财政政策对三次产业的效应都存在明显的区域性。并且,结合相关理论,文章从产业和区域两个层面对实证结果予以分析,揭示出产业间在增量资本产出率和政府扶持力度以及区域间在银行集中度和基础设施投资方面存在的差异,是实证结果的主要致因。 相似文献
285.
E. James Harner 《Australian & New Zealand Journal of Statistics》2011,53(3):271-288
Three new entropy estimators of multivariate distributions are introduced. The two cases considered here concern when the distribution is supported by a unit sphere and by a unit cube. In the former case, the consistency and the upper bound of the absolute error for the proposed entropy estimator are established. In the latter one, under the assumption that only the moments of the underlying distribution are available, a non‐traditional estimator of the entropy is suggested. We also study the practical performances of the constructed estimators through simulation studies and compare the estimators based on the moment‐recovered approaches with their counterparts derived by using the histogram and k th nearest neighbour constructions. In addition, one worked example is briefly discussed. 相似文献
286.
287.
Javier Arroyo Gloria Gonzlez‐Rivera Carlos Mat Antonio Muoz San Roque 《Statistical Analysis and Data Mining》2011,4(2):216-228
We adapt smoothing methods to histogram‐valued time series (HTS) by introducing a barycentric histogram that emulates the “average” operation, which is the key to any smoothing filter. We show that, due to its linear properties, only the Mallows‐barycenter is acceptable if we wish to preserve the essence of any smoothing mechanism. We implement a barycentric exponential smoothing to forecast the HTS of daily histograms of intradaily returns to both the SP500 and the IBEX 35 indexes. We construct a one‐step‐ahead histogram forecast, from which we retrieve a desired γ‐value‐at‐risk (VaR) forecast. In the case of the SP500 index, a barycentric exponential smoothing delivers a better forecast, in the MSE sense, than those derived from vector autoregression models, especially for the 5% VaR. In the case of IBEX35, the forecasts from both methods are equally good. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 216–228, 2011 相似文献
288.
This paper introduces symbolic data analysis, explaining how it extends the classical data models to take into account more complete and complex information. Several examples motivate the approach, before the modeling of variables assuming new types of realizations are formally presented. Some methods for the (multivariate) analysis of symbolic data are presented and discussed. This is however far from being exhaustive, given the present dynamic development of this new field of research. © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 157–170, 2011 相似文献
289.
A massive dataset is characterized by its size and complexity. In its most basic form, such a dataset can be represented as a collection of n observations on p variables. Aggravation or even impasse can result if either number is huge. The more difficult challenge is usually associated with the case of very high dimensionality or ‘big p’. There is a fast growing literature on how to handle such challenges, but most of it is in a supervised learning context involving a specific objective function, as in regression or classification. Much less is known about effective strategies for more exploratory data analytic activities. The purpose of this article is to put into historical perspective much of the recent research on dimensionality reduction and variable selection in such problems. Examples of applications that have stimulated this research are discussed along with a sampling of the latest methodologies to illustrate the onslaught of creative ideas that have surfaced. From a practitioner's perspective, the most effective strategy may be to emphasize the role of interdisciplinary teamwork with decisions on how best to grapple with high dimensionality emerging from a mixture of statistical thinking and consideration of the circumstances of the application. WIREs Comp Stat 2011 3 95–103 DOI: 10.1002/wics.141 This article is categorized under:
- Statistical Learning and Exploratory Methods of the Data Sciences > Exploratory Data Analysis
- Data: Types and Structure > Massive Data
- Statistical and Graphical Methods of Data Analysis > Multivariate Analysis
290.
Arnold Goodman 《Statistical Analysis and Data Mining》2011,4(1):3-8
The Preview integrates a sample of emerging topics in statistical analysis and data mining which I collected at 4 relevant 2010 meetings and major challenges which correspond to them. They are grouped into Mixtures of Problem Data, Methodologies for Solutions, Challenges for Statistical Analysis and Data Mining, and Challenges Suggested during Review. This Preview is meant to be a provocative overview, but it is not meant to be a comprehensive or definitive research article. A vision of the near future in any area is there for us to perceive when we look for it carefully. It has the advantages of short term predictions and its disadvantages may be overcome by checking against current literature. In times of cascading change, such an informed Preview may be even more valuable than the far more typical Reviews of what has already been accomplished that are provided by most Journals in overabundance. Now let us welcome the new decade full of things that have never been–imagine the possibilities! © 2011 Wiley Periodicals, Inc. Statistical Analysis and Data Mining 4: 3–8 2011 相似文献