A two-sided cusum for first-order integer-valued autoregressive processes of poisson counts

Download
2011
Yontay, Petek
Count data are often encountered in manufacturing and service industries due to ease of data collection. These counts can be useful in process monitoring to detect shifts of a process from an in-control state to various out-of-control states. It is usually assumed that the observations are independent and identically distributed. However, in practice, observations may be autocorrelated and this may adversely affect the performance of the control charts developed under the assumption of independence. In this thesis, the cumulative sum (CUSUM) control chart for monitoring autocorrelated processes of counts is investigated. To describe the autocorrelation structure of counts, a Poisson integer-valued autoregressive moving average model of order 1, Poisson INAR(1), is employed. Changes in the process mean in both positive and negative directions are taken into account while designing the CUSUM chart. A trivariate Markov Chain approach is utilized for evaluating the performance of the chart.

Suggestions

A Two-Sided Cumulative Sum Chart for First-Order Integer-Valued Autoregressive Processes of Poisson Counts
Yontay, Petek; Weiss, Christian H.; TESTİK, MURAT CANER; Bayındır, Zeynep Pelin (2013-02-01)
Count data processes are often encountered in manufacturing and service industries. To describe the autocorrelation structure of such processes, a Poisson integer-valued autoregressive model of order 1, namely, Poisson INAR(1) model, might be used. In this study, we propose a two-sided cumulative sum control chart for monitoring Poisson INAR(1) processes with the aim of detecting changes in the process mean in both positive and negative directions. A trivariate Markov chain approach is developed for exact e...
On the Solution of Data Association Problem Using Rollout Algorithms
Ozgen, Selim; Demirekler, Mübeccel; Orguner, Umut (2016-07-08)
The quality and precision of tracking maneuvering targets under heavy clutter is highly dependent on both the data association and the state estimation algorithms. In this study, measurement-to-track association problem for a single target when P-D = 1 is discussed. The problem considers the batch set of measurements in a time interval. An approximate stochastic optimization algorithm for data association is presented. To reduce the computational load, the rollout algorithm is utilized. The algorithm is app...
A Similarity Based Oversampling Method for Multi-Label Imbalanced Text Data
Karaman, İsmail Hakkı; Köksal, Gülser; Erişkin, Levent; Department of Industrial Engineering (2022-9-1)
In the real world, while the amount of data increases, it is not easy to find labeled data for Machine Learning projects, because of the compelling cost and effort requirements for labeling data. Also, most Machine Learning projects, especially multi-label classification problems, struggle with the data imbalance problem. In these problems, some classes, even, do not have enough data to train a classifier. In this study, an over sampling method for multi-label text classification problems is developed and s...
A multi-phase heuristic for the production routing problem
Solyali, Oguz; Süral, Haldun (2017-11-01)
This study considers the production routing problem where a plant produces and distributes a single item to multiple retailers over a multi-period time horizon. The problem is to decide on when and how much to produce and stock at the plant, when and how much to serve and stock at each retailer, and vehicle routes for shipments such that the sum of fixed production setup cost, variable production cost, distribution cost, and inventory carrying cost at the plant and retailers is minimized. A multi-phase heur...
Using Pad-Stripped Acausally Filtered Strong-Motion Data
Boore, David M.; Sisi, Aida Azari; Akkar, Dede Sinan (2012-04-01)
Most strong-motion data processing involves acausal low-cut filtering, which requires the addition of sometimes lengthy zero pads to the data. These padded sections are commonly removed by organizations supplying data, but this can lead to incompatibilities in measures of ground motion derived in the usual way from the padded and the pad-stripped data. One way around this is to use the correct initial conditions in the pad-stripped time series when computing displacements, velocities, and linear oscillator ...
Citation Formats
P. Yontay, “A two-sided cusum for first-order integer-valued autoregressive processes of poisson counts,” M.S. - Master of Science, Middle East Technical University, 2011.