The focus of this paper is on finding suitable estimators of the entropy for different fixed size pips sampling designs. What estimator to use depends on the design and the situation. Some estimators are suitable only for small populations and samples. Other estimators can be used only for designs that have a known and practical probability function. Five different cases are covered. The entropy estimators presented are general and can be used for other sampling designs.
Calculating the Shannon entropy for symbolic sequences has been widely considered in many fields. Fo...
© 2020 Copyright held by the owner/author(s). This paper addresses a fundamental problem in random v...
The paper studies four entropy tests of normality of real valued observations using four statistics ...
The main objective in sampling is to select a sample from a population in order to estimate some unk...
This article concerns entropy estimation using judgment post stratification sampling. Some nonparame...
The total entropy utility function is considered for the dual purpose of Bayesian design for model d...
A large part of survey sampling literature is devoted to unequal probabilities sampling designs with...
When Shannon entropy is used as a criterion in the optimal design of experiments, advantage can be t...
We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one‐dimens...
This dissertation explores the use of Shannon’s entropy and mutual information to quantify uncertain...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
Since the entropy is a popular randomness measure, there are many studies for the estimation of entr...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
25 pagesCalibration methods have been widely studied in survey sampling over the last decades. Viewi...
We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one-dimens...
Calculating the Shannon entropy for symbolic sequences has been widely considered in many fields. Fo...
© 2020 Copyright held by the owner/author(s). This paper addresses a fundamental problem in random v...
The paper studies four entropy tests of normality of real valued observations using four statistics ...
The main objective in sampling is to select a sample from a population in order to estimate some unk...
This article concerns entropy estimation using judgment post stratification sampling. Some nonparame...
The total entropy utility function is considered for the dual purpose of Bayesian design for model d...
A large part of survey sampling literature is devoted to unequal probabilities sampling designs with...
When Shannon entropy is used as a criterion in the optimal design of experiments, advantage can be t...
We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one‐dimens...
This dissertation explores the use of Shannon’s entropy and mutual information to quantify uncertain...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
Since the entropy is a popular randomness measure, there are many studies for the estimation of entr...
It was recently shown that estimating the Shannon entropy H(p) of a discrete k-symbol distribution p...
25 pagesCalibration methods have been widely studied in survey sampling over the last decades. Viewi...
We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one-dimens...
Calculating the Shannon entropy for symbolic sequences has been widely considered in many fields. Fo...
© 2020 Copyright held by the owner/author(s). This paper addresses a fundamental problem in random v...
The paper studies four entropy tests of normality of real valued observations using four statistics ...