On unequal probability sampling without replacement, sample size 2.
Optimal Prediction for a Finite Population Total with Connected Designs and Related Model-Based Results.
Optimal random sampling for spectrum estimation in DASP applications
In this paper we analyse a class of DASP (Digital Alias-free Signal Processing) methods for spectrum estimation of sampled signals. These methods consist in sampling the processed signals at randomly selected time instants. We construct estimators of Fourier transforms of the analysed signals. The estimators are unbiased inside arbitrarily wide frequency ranges, regardless of how sparsely the signal samples are collected. In order to facilitate quality assessment of the estimators, we calculate...
Optimal Stratification and Grouping by Dynamic Programming.
Optimale Aufteilung des Stichprobenumfangs bei mehreren Merkmalen.
Optimum Allocation in Bayesian Stratified Two Phase Sampling when there are m-Attributes.
Optimum Allocation in Multivariate Stratified Random Sampling with Overhead Cost.
Optimum Strategies for Estimating the Variance of a Finite Population Under a Superpopulation Model.
Particle filter with adaptive sample size
The paper deals with the particle filter in state estimation of a discrete-time nonlinear non-Gaussian system. The goal of the paper is to design a sample size adaptation technique to guarantee a quality of a filtering estimate produced by the particle filter which is an approximation of the true filtering estimate. The quality is given by a difference between the approximate filtering estimate and the true filtering estimate. The estimate may be a point estimate or a probability density function...
P-insesgadez asintótica y robustez en la estimación lineal con modelos de superpoblaciones: un criterio de selección.
Se analiza la estimación lineal de la media poblacional desde el punto de vista de los modelos de superpoblaciones con parámetros desconocidos y correlación no nula. La posible existencia de errores de especificación en el modelo determina el estudio de propiedades tales como la insesgadez asintótica respecto al diseño de muestreo y la robustez débil, deseables para asegurar la robustez de los estimadores frente a este tipo de errores. Se establece, así, un criterio de selección entre estimadores...
PPT designs with categorical variables for the estimation of dicho-ratios.
Predictive Estimation of Finite Population Mean Using Product Estimator.
Predikce výsledků voleb a stratifikované náhodné výběry
Koncept stratifikovaného náhodného výběru představuje užitečnou alternativu prostého náhodného výběru v situaci, kdy je zkoumaná populace složena z několika částí s různými vlastnostmi. Je tak možné například při stejném rozsahu výběru získat odhad průměru s menším rozptylem. V tomto příspěvku si představíme základy teorie stratifikovaných náhodných výběrů a na příkladu druhého kola prezidentských voleb 2023 si ukážeme jejich praktické použití.
Randomized minimax estimators under simple random sampling from a finite population.
Randomized Response: Estimating Mean Square Errors of Linear Estimators and Finding Optimal Unbiased Strategies.
Recent Advances on Some Aspects of Stratified Sample Design. A Review of the Literature.
Recovery of band-limited functions on locally compact Abelian groups from irregular samples
Using the techniques of approximation and factorization of convolution operators we study the problem of irregular sampling of band-limited functions on a locally compact Abelian group . The results of this paper relate to earlier work by Feichtinger and Gröchenig in a similar way as Kluvánek’s work published in 1969 relates to the classical Shannon Sampling Theorem. Generally speaking we claim that reconstruction is possible as long as there is sufficient high sampling density. Moreover, the iterative...
Recursive estimation of inventory quality classes using sampling.
Regression type estimators of finite population variance under multiphase sampling.
Regression-Type Estimators Using Two Auxiliary Variables and the Model of Double Sampling from Finite Populations.