Finite Moment Formulare of h-Statistics and Their Estimates.
Fixed precision optimal allocation in two-stage sampling
Two-stage sampling schemes arise in survey sampling, especially in situations when the complete update of the frame is difficult. In this paper we solve the problem of fixed precision optimal allocation in two special two-stage sampling schemes. The solution is based on reducing the original question to an eigenvalue problem and then using the Perron-Frobenius theorem.
Formtest räumlicher Punkthaufen bei beliebiger Population.
Graphical models for hierarchical computations in the analysis and design of replications.
Inflated truncated negative binomial acceptance sampling plan
Intelligent control of the complex technology process based on adaptive pattern clustering and feature map.
Interpenetrating Sub-Samples Â? with and without Replacement.
Invited paper with discussion: Natural Induction: An objective Bayesian approach.
Jack-Knifing the Ratio and the Product Estimators in Double Sampling.
La articulación entre lo cuantitativo y lo cualitativo: de las grandes encuestas a la recogida de datos intensiva.
Son casi innumerables las reflexiones que se han hecho en el campo de la metodología de las ciencias sociales, sobre la dicotomía, real o inexistente, entre las perspectivas de análisis cuantitativo y cualitativo, mientras que han sido menos abundantes los trabajos teóricos, aunque van siendo más abundantes los empíricos, que han tratado de compatibilizar y/o complementar ambas perspectivas. En muchos casos los trabajos cualitativos cubren solamente los primeros pasos de la investigación social,...
Learning the naive Bayes classifier with optimization models
Naive Bayes is among the simplest probabilistic classifiers. It often performs surprisingly well in many real world applications, despite the strong assumption that all features are conditionally independent given the class. In the learning process of this classifier with the known structure, class probabilities and conditional probabilities are calculated using training data, and then values of these probabilities are used to classify new observations. In this paper, we introduce three novel optimization...
Limit theorem for random walk in weakly dependent random scenery
Let S=(Sk)k≥0 be a random walk on ℤ and ξ=(ξi)i∈ℤ a stationary random sequence of centered random variables, independent of S. We consider a random walk in random scenery that is the sequence of random variables (Un)n≥0, where Un=∑k=0nξSk, n∈ℕ. Under a weak dependence assumption on the scenery ξ we prove a functional limit theorem generalizing Kesten and Spitzer’s [Z. Wahrsch. Verw. Gebiete50 (1979) 5–25] theorem.
Loss Functions and Admissible Estimators in Survey Sampling.
Metrika Vol. 31, page 1-4 - A Note on Necessary Best Estimator of Order Two, by Prabhu-Ajgaonkar, Aurangabad
Model Assisted Survey Sampling Strategy in Two Phases.
Mostratge i estimació de poblacions ocultes.
En este artículo se realiza una discusión detallada de las principales metodologías empleadas para el estudio de fenómenos marginales y ocultos, como son el muestreo en bola de nieve, el método de estimación de captura-recaptura y el método para estimar el número de consumidores de cocaína en una gran ciudad. Este nuevo método se basa en dos selecciones aleatorias y puede estimar la ocultación del fenómeno.
Multivariate Multistage Methodologies for Simultaneous All Pairwise Comparisons.
Note méthodologique. Statistiques de groupe, groupes d'observations
Cette note se situe dans le cadre d'un travail méthodologique en cours, sur la formalisation des procédures élémentaires d'analyse de données. Nous nous bornerons ci-dessous (§ 1) à rappeler les notions de base nécessaires à la compréhension de cette note. En sciences humaines, l'expression de «groupe d'observations» est souvent utilisée comme quasi-synonyme de «famille d'observations», mais avec une connotation plus restrictive : un groupe est une famille d'observations considérée comme «formant...
Notes for a Unified Theory of Estimation for Sample Surveys Taking into Account Response Errors.
On a famous problem of induction.
A Bayesian solution is provided to the problem of testing whether an entire finite population shows a certain characteristic, given that all the elements of a random sample are observed to have it. This is obtained as a direct application of existing theory and, it is argued, improves upon Jeffrey's solution.