The method of maximum likelihood estimation based on ranked set sampling (RSS) and some of its modifications is used to estimate the unknown parameters of the new Weibull-Pareto distribution. The estimators are compared with the conventional estimators based on simple random sampling (SRS). The biases, mean squared errors, and confidence intervals are used to the comparison. The effect of the set size and number of cycles of the RSS schemes are addressed. Monte Carlo simulation is carried out by using R. The results showed that the RSS estimators are more efficient than their competitors using SRS
In this paper maximum ranked set sampling procedure with unequal samples (MRSSU) is proposed. Maximu...
Abstract. In statistical surveys, if the measurements of sampling units ac-cording to the variable u...
In this paper, the problem of estimation of R = P(Y < X) based on ranked set sampling, when (X,Y)...
In statistical literature, estimation of R=P(X<Y) is a commonly-investigated problem, and consequ...
This paper deals with making inferences regarding system reliability R = P(X < Y) when the distribut...
In this paper, the derivation of the likelihood function for parameter estimation based on double ra...
In this paper, the likelihood function for parameter estimation based on double ranked set sampling ...
A modification of ranked set sampling (RSS) called maximum ranked set sampling with unequal sample (...
In this paper, we have considered that ranked set sampling is able to estimate the parameters of exp...
In this paper, we provide Bayesian estimation for the parameters of the Pareto distribution based on...
Parameter estimation Based on Double Ranked Set Sampling (DRSS) designs was recently developed by Sa...
Ranked set sampling is applicable whenever ranking of a set of sampling units can be done easily by ...
AbstractThe closed-form maximum likelihood estimators (MLEs) of population mean and variance under r...
The closed-form maximum likelihood estimators (MLEs) of population mean and variance under ranked se...
Ranked set sampling (RSS) is an efficient method for estimating parameters when exact measurement of...
In this paper maximum ranked set sampling procedure with unequal samples (MRSSU) is proposed. Maximu...
Abstract. In statistical surveys, if the measurements of sampling units ac-cording to the variable u...
In this paper, the problem of estimation of R = P(Y < X) based on ranked set sampling, when (X,Y)...
In statistical literature, estimation of R=P(X<Y) is a commonly-investigated problem, and consequ...
This paper deals with making inferences regarding system reliability R = P(X < Y) when the distribut...
In this paper, the derivation of the likelihood function for parameter estimation based on double ra...
In this paper, the likelihood function for parameter estimation based on double ranked set sampling ...
A modification of ranked set sampling (RSS) called maximum ranked set sampling with unequal sample (...
In this paper, we have considered that ranked set sampling is able to estimate the parameters of exp...
In this paper, we provide Bayesian estimation for the parameters of the Pareto distribution based on...
Parameter estimation Based on Double Ranked Set Sampling (DRSS) designs was recently developed by Sa...
Ranked set sampling is applicable whenever ranking of a set of sampling units can be done easily by ...
AbstractThe closed-form maximum likelihood estimators (MLEs) of population mean and variance under r...
The closed-form maximum likelihood estimators (MLEs) of population mean and variance under ranked se...
Ranked set sampling (RSS) is an efficient method for estimating parameters when exact measurement of...
In this paper maximum ranked set sampling procedure with unequal samples (MRSSU) is proposed. Maximu...
Abstract. In statistical surveys, if the measurements of sampling units ac-cording to the variable u...
In this paper, the problem of estimation of R = P(Y < X) based on ranked set sampling, when (X,Y)...