Shift Detection Comparison For Sized Biased And Area Biased Exponential Distributions Based Control Charts
Bibliographic Data
| ID | 15537489 |
|---|---|
| Authors | Adeel Anjum (0000-0001-5083-0019, corresponding author), Muhammad Z Iqbal (0000-0001-5369-5588), Muhammad Kashif (0000-0001-7951-6568), Madiha Ghamkhar (0000-0002-1897-6939) |
| Year | 2024 |
| Volume | 21 |
| Issue | 8 |
| Pages | 1-13 |
| Publication date | 2024-06-06 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | MIGRATION LETTERS (JOURNAL) |
| Journal identifiers | ISSN: 1741-8984 • E-ISSN: 1741-8992 |
| Publisher | Dewspublication (PUBLISHER) |
| DOI | 10.59670/ml.v21is11.10731 |
| OpenAlex | W4400062463 |
| Language | EN |
| References cited | 1 |
Probability distribution models are very helpful to solving many real-life problems. The development of new or extensions to an existing model is a very attractive area of research. Among many types of probability distribution models, weighted distributions are becoming more important for modeling data. Weighted distributions can help discover defects in manufacturing and outliers by weighting significant observations. Control charts are the most important tools to monitor process efficiency. In recent decades, researchers have focused on weighted distributions, especially those with size and area biased exponential distribution. This research introduces a novel control chart for a characteristic following a size-biased and area-biased exponential distribution to emphasize the relevance of weighted distributions. Charts are effectively determines size-biased and area-biased exponential distribution control chart limits also Monte Carlo simulations are used to assess different Average Run Length (ARL) values
Chart · Control chart · Econometrics · Exponential distribution · Exponential function · Gamma distribution · Monte Carlo method · Outlier · Probability distribution · Process (computing · Statistical process control · Statistics · Weighting · Advanced Statistical Methods and Models · Advanced Statistical Process Monitoring · Computer Science · Fault Detection and Control Systems · Mathematics
| Highly cited | No |
|---|