Editorial: Journal of Statistical Distributions and Applications
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
© A m Introduction Statistical distributions are the foundations of statistical methodology in both theory and applications. They are the back bone of every parametric statistical method, including inference, modeling, survival, reliability, and others. In recent years, partly due to the advanced computing technology, there have been a series of developments of new methodology for generating new families of statistical distributions, which have greatly enhanced parametric statistical methods for handling real world scenarios that could not be modeled using existing distributions. One main reason for the need of generalized families is that each of the useful basic statistical distributions has its own weakness in real-world applications. The real-world phenomena are often much more complex for these commonly known basic statistical distributions to provide adequate fit. For example, Johnson et al. (2005) presented various modifications and generalizations of the Poisson distribution. Some of these distributions were developed in an attempt to explain the unequal mean and variance in the numerical data observed in different fields of applications. The history of statistical distributions started in the 18 century. The first major gathering on statistical distributions and their applications was in 1963 at McGill, Canada where experts participated in the International Symposium on Classical and Contagious Discrete Distributions. Another major gathering, the NATO Advanced Study Institute on Statistical Distributions in Scientific Work, was held at the University of Calgary, Canada from July 29 to August 10, 1974. Patil et al. (1974) in their preface to the Proceedings of the NATO Advanced Study Institute, referred to the McGill symposium as “a milestone in the recognition and development of the theory and application of statistical distributions.” According to Professor Kotz in his Foreword to the book by Consul and Famoye (2006) “The main impetus for the development of an orderly investigation of statistical distributions and their applications was the International Symposium on Classical and Contagious Discrete Distributions, organized by G.P. Patil in August of 1969 (1963) ...” Since then, various conferences and meetings have been organized on statistical distributions. However, no dedicated journal on statistical distributions was ever launched. In one of the Lukacs Symposia in the early 1990s held at Bowling Green State University, Bowling Green, Ohio, Dr. Adrienne Kemp (University of St. Andrews in Scotland) in her address stated that all research articles on statistical distributions are scattered in various journals and there is no dedicated journal for statistical distributions. To
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle