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generalized linear model-based control charts for discrete semiconductor process data

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2004年第8期20卷 777-786页

作者： Skinner, KR Montgomery, DC Runger, GC Arizona State Univ Tempe AZ 85287 USA Maricopa Adv Technol Res Ctr Tempe AZ 85281 USA

In previous simple cases generalized linear model (GLM)-based control charts have been shown to be very effective in detecting shifts in multivariate counts when input variables are measurable. This paper studies the effectiveness of GLM-based control charts on more complicated data sets with multiple inputs and outputs whose relationships are varied. Results show that the GLM-based charts were most effective in detecting changes in the means of overdispersed counts (when compared with counts with normal dispersion). The GLM-based charts were more effective than multiple C charts in detecting changes in the means of counts when multiple complicated relationships exist. Copyright (C) 2004 John Wiley Sons, Ltd.

关键词： generalized linear model model-based control chart overdispersion

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generalized linear model based gamma control chart

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QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2024年第1期40卷 699-711页

作者： Ali, Sajid Asghar, Maria Shah, Ismail Quaid i Azam Univ Dept Stat Islamabad Pakistan Univ Padua Dept Stat Sci Padua Italy Quaid i Azam Univ Dept Stat 45320 Islamabad 44000 Pakistan

Traditional monitoring techniques are frequently used for monitoring a response variable, while ignoring the other important variables. A simple linear regression model to introduce covariates-based charts has received a lot of attention in the recent publications. When the response variable belongs to the exponential family, the generalized linear model (GLM) is a flexible approach to model a phenomenon. This study uses gamma distribution to introduce GLM-based Shewhart-type control charts. The monitoring statistic is developed using the Pearson residuals (PRs) obtained from the gamma regression model. The suggested charts' performance is evaluated using the run-length properties and extensive Monte Carlo simulations. A comparison of Pearson-residual to the deviance-residual charts is also discussed in this article. Finally, to emphasize the significance of the study, the proposed control charts are implemented on a real-life data set.

关键词： average run length deviance residuals gamma distribution generalized linear model Pearson residuals Shewhart chart

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generalized linear model (GLM) analysis: Multivariables of microcalcification specimens obtained via X-ray guided by stereotactic wire localization biopsy

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JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2019年第3期27卷 493-502页

作者： Wang, Qian Li, Erni Song, Ying Ma, Peiqing Wang, Yipeng Liu, Xia Qi, Weiwei Zhao, Xinming Chinese Acad Med Sci Dept Imaging Diag Natl Canc Ctr Natl Clin Res Ctr CancCanc Hosp Beijing 100021 Peoples R China Peking Union Med Coll Beijing 100021 Peoples R China Chinese Acad Med Sci Dept Pathol Natl Canc Ctr Natl Clin Res Ctr CancCanc Hosp Beijing Peoples R China Chinese Acad Med Sci Dept Breast Surg Natl Canc Ctr Natl Clin Res Ctr CancCanc Hosp Beijing Peoples R China Peking Univ Peoples Hosp Dept Radiol Beijing 100044 Peoples R China

OBJECTIVE: To retrospectively explore correlation of the resected specimen volume of breast microcalcification lesions and endogenous and exogenous factors of stereotactic needle localization biopsy (SNLB). MATERIALS AND METHODS: Totally 214 patients underwent SNLB for non-palpable breast lesion with microcalcification lesions. Of 211 patients, 198 patients underwent single needle localization and 13 patients underwent multi-needle localization (26 lesions). Lesion sizes, distribution characteristics, lesion localization accuracy and resected specimen volumes were recorded and analyzed using a generalized linear model (GLM). RESULTS: The average lesion diameter is 2.63 +/- 1.73 cm. The localization accuracy of 187 lesions were moderate, 26 were too deep and 11 were too superficial. The mean resected specimen volume (V) was 17.51 +/- 5.14 cm(3). One-way ANOVA analysis showed that 3 factors, including lesion sizes, distribution characteristics and the localization accuracy were associated with resected specimen volume (F = 67.56-112.78, P < 0.001). GLM revealed that lesion sizes, single clustered distribution and accurate localization were significant factors for resected specimen volume (F = -4.82-11.36, P < 0.05). The ratio (%) of the resected specimen volume to the involved breast volume (VO) was defined as the degree of breast defect. The mean breast defect of 125 benign patients (V/V0) was 27.5% ranging from 10.1% to 42.3%. CONCLUSION: Average lesion diameter and localization accuracy are highly significant variables for the resected specimen volume. Localization accuracy as a subjective controllable variable is one of the important factors that determine the volume of lesion resection. Single clustered distribution was more susceptible localization accuracy than other characteristic distributions. Improving localization accuracy can reduce resected specimen volume, which can reduce breast defect to a certain extent.

关键词： generalized linear model stereotactic wire localization biopsy non-palpable breast lesions breast cancer microcalcifications

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generalized linear model for subordinated Levy processes

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SCANDINAVIAN JOURNAL OF STATISTICS 2022年第2期49卷 772-801页

作者： Mselmi, Farouk Euromed Univ Fes UEMF Bldg B4 Fes Morocco Sfax Univ Dept Math Sfax Tunisia

generalized linear models, introduced by Nelder and Wedderburn, allowed to model the regression of normal and nonnormal data. While doing so, the analysis of these models could not be obtained without the explicit form of the variance function. In this paper, we determine the link and variance functions of the natural exponential family generated by the class of subordinated Levy processes. In this framework, we introduce a class of variance functions that depends on the Lambert function. In this regard, we call it the Lambert class, which covers the variance functions of the natural exponential families generated by the subordinated gamma processes and the subordinated Levy processes by the Poisson subordinator. Notice that the gamma process subordinated by the Poisson one is excluded from this class. The concept of reciprocity in natural exponential families was given in order to obtain an exponential family from another one. In this context, we get the reciprocal class of the natural exponential family generated by the class of subordinated Levy processes. It is well known that the variance function represents an essential element for the determination of the quasi-likelihood and deviance functions. Then, we use the expression of our variance function in order to maintain them. This leads us to analyze the proposed generalized linear model. We illustrate some of our models with applications to the daily exchange rate returns of the Tunisian Dinar against the U.S. Dollar and the damage incidents of ships.

关键词： generalized linear model Levy processes quasi-likelihood function subordinated variance function

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generalized linear model selection using R²

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JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2008年第12期138卷 3705-3712页

作者： Hu, Bo Shao, Jun Univ Wisconsin Dept Stat Madison WI 53706 USA Cleveland Clin Dept Quantitat Hlth Sci Cleveland OH 44195 USA

The problem of model selection in generalized linear models amounts to selecting a subset of useful covariates from a set of possible covariates and choosing a link function from a set of possible link functions. A model selection procedure based on a modified R-2 statistic is proposed. Like in linear models, R-2 statistics in generalized linear models are used to quantify the proportion of variance in the response explained by covariates. model selection using R-2 statistics is natural for investigators who are familiar with the use of R-2 statistics. The modified R-2 statistic is obtained by introducing an extra penalty term on the complexity of the candidate model. Under weak conditions, the proposed procedure is shown to be consistent in the sense that with probability tending to one (as the sample size increases) the selected model equals the optimal model between the response and covariates. Simulation results are presented to demonstrate the effectiveness of the proposed procedure in finite sample applications. (C) 2008 Elsevier B.V. All rights reserved.

关键词： model selection generalized linear model R-2 optimal model consistency

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generalized linear model with software mathematica® 17

Generalized linear model with software mathematica®

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17th Conference on Applied Mathematics, APLIMAT 2018

作者： Janiga, Ivan Gabková, Jana Institute of Mathematics and Physics Faculty of Mechanical Engineering Slovak University of Technology in Bratislava Nám. slobody 17 Bratislava812 31 Slovakia

generalized linear model is used to model the functional dependencies, where one variable is a random variable and the second variable is non-random. © 2018 Slovak University of Technology in Bratislava. All righ... 详细信息

ISBN: (纸本)9788022747653

关键词： Covariance matrix Design matrix generalized linear model Vector of measurements Vector of parameters

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M-Estimator of a generalized linear model with Measurement Errors

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2011年第3期40卷 532-546页

作者： Huang, Yujie Song, Lixin Dalian Univ Technol Sch Math Sci Dalian 116024 Peoples R China Anshan Normal Univ Dept Math Anshan Peoples R China

In this article, we propose a generalized linear model and estimate the unknown parameters using robust M-estimator. Under suitable conditions and by the strong law of large numbers and central limits theorem, the proposed M-estimators are proved to be consistent and asymptotically normal. We also evaluate the finite sample performance of our estimator through a Monte Carlo study.

关键词： Asymptotic normality Consistency generalized linear model M-estimator

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The gamma generalized linear model, log transformation, and the robust Yuen-Welch test for analyzing group means with skewed and heteroscedastic data

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COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION 2019年第8期48卷 2269-2286页

作者： Ng, Victoria K. Y. Cribbie, Robert A. York Univ Dept Psychol Toronto ON Canada

Alternatives for positively skewed and heteroscedastic data include the Yuen-Welch (YW) test, data transformations, and the generalized linear model (GzLM). Because the GzLM is rarely considered in psychology compared to the other two, we compared these strategies conceptually and empirically. The YW test generally has satisfactory power, but its trimmed mean can deviate substantially from the arithmetic mean, which is often the desired parameter. The gamma GzLM can be used as a substitute for the log transformation and addresses the limitations in inference for the YW and data transformations.

关键词： Arithmetic mean ANOVA Box-Cox Gamma generalized linear model Geometric mean Robust statistics Transformations Trimmed mean

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Drought forecasting with regionalization of climate variables and generalized linear model

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METEOROLOGICAL APPLICATIONS 2024年第6期31卷

作者： Lee, Taesam Kong, Yejin Lee, Joo-Heon Won, Chang-Hee Gyeongsang Natl Univ Dept Civil Engn Jinju Gyeongnam South Korea Joongbu Univ Dept Civil Engn Goyang Chungnam Do South Korea Natl Disaster Management Res Inst Natl Integrated Drought Ctr Ulsan South Korea

Spring drought forecasting is essential in South Korea for managing water resources reliably and cultivating agricultural products efficiently, as seasonal rainfall difference often drives water shortage during spring. In the current study, a novel scheme for spring drought forecasting was suggested by extensively searching appropriate predictors from the global climate variable: here mean sea level pressure (MSLP) of the winter season due to its time lag for forecasting. The target series was estimated with the median of the spring precipitation series of the weather stations over South Korea, called the accumulated spring precipitation (ASP). A number of points of the MSLP data were detected as significant cross-correlation with the ASP and also the points were regionally grouped. Therefore, the regionalization for the high correlation points was performed, resulting in three regions, such as Arctic Ocean (R1), South Pacific (R2), and South Africa (R3). The R1 and R2 regions are located at the places where climate indices have been developed such as Arctic Oscillation and North Atlantic Oscillation for R1 and the indicator of El-Nino and Southern Oscillation for R2. The generalized linear model (GLM) was adopted in ASP drought forecasting with the driven three regionalized indices as the predictors of the ASP. The result indicates that the regionalized indices can produce a good performance in forecasting the ASP. The forecasting result can be employed as a good tool for managing water resources and planning better cultivation in agriculture industries.

关键词： climate indices drought forecasting generalized linear model regionalization

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Estimating organ doses from tube current modulated CT examinations using a generalized linear model

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MEDICAL PHYSICS 2017年第4期44卷 1500-1513页

作者： Bostani, Maryam McMillan, Kyle Lu, Peiyun Kim, Grace Hyun J. Cody, Dianna Arbique, Gary Greenberg, S. Bruce DeMarco, John J. Cagnon, Chris H. McNitt-Gray, Michael F. Univ Calif Los Angeles David Geffen Sch Med Dept Biomed Phys Los Angeles CA 90024 USA Univ Calif Los Angeles David Geffen Sch Med Dept Radiol Los Angeles CA 90024 USA Mayo Clin CT Clin Innovat Ctr Dept Radiol Rochester MN 55905 USA Univ Texas MD Anderson Canc Ctr Dept Imaging Phys Houston TX 77030 USA UT Southwestern Med Ctr Dallas TX 75390 USA Arkansas Childrens Hosp Dept Radiol Little Rock AR 72202 USA Cedars Sinai Med Ctr Dept Radiat Oncol Los Angeles CA 90048 USA

Purpose: Currently, available Computed Tomography dose metrics are mostly based on fixed tube current Monte Carlo (MC) simulations and/or physical measurements such as the size specific dose estimate (SSDE). In addition to not being able to account for Tube Current Modulation (TCM), these dose metrics do not represent actual patient dose. The purpose of this study was to generate and evaluate a dose estimation model based on the generalized linear model (GLM), which extends the ability to estimate organ dose from tube current modulated examinations by incorporating regional descriptors of patient size, scanner output, and other scan-specific variables as needed. Methods: The collection of a total of 332 patient CT scans at four different institutions was approved by each institution's IRB and used to generate and test organ dose estimation models. The patient population consisted of pediatric and adult patients and included thoracic and abdomen/pelvis scans. The scans were performed on three different CT scanner systems. Manual segmentation of organs, depending on the examined anatomy, was performed on each patient's image series. In addition to the collected images, detailed TCM data were collected for all patients scanned on Siemens CT scanners, while for all GE and Toshiba patients, data representing z-axis-only TCM, extracted from the DICOM header of the images, were used for TCM simulations. A validated MC dosimetry package was used to perform detailed simulation of CT examinations on all 332 patient models to estimate dose to each segmented organ (lungs, breasts, liver, spleen, and kidneys), denoted as reference organ dose values. Approximately 60% of the data were used to train a dose estimation model, while the remaining 40% was used to evaluate performance. Two different methodologies were explored using GLM to generate a dose estimation model: (a) using the conventional exponential relationship between normalized organ dose and size with regional water equ

关键词： CT generalized linear model Monte Carlo simulations organ dose estimation tube current modulation

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