Influence diagnostics in regression with complex designs through conditional bias
Conditional bias, influential observation, design-based regression, survey sampling, 62D05, 62J20,
Juan Moreno-Rebollo +3 more
core +1 more source
A novel proposed class of estimators under ranked set sampling: Simulation and diverse applications. [PDF]
Heliyon, 2023 Yusuf M +4 more
europepmc +1 more source
Difference estimators of quantiles in finite populations
Auxiliary information, difference estimator, finite population quantiles, confidence interval, 62D05,
M. Mar Rueda +2 more
core +1 more source
New estimators for estimating population total: an application to water demand in Thailand under unequal probability sampling without replacement for missing data. [PDF]
PeerJ, 2022 Ponkaew C, Lawson N.
europepmc +1 more source
An Alternative Approach to Estimation of Population Mean in Two-Stage Sampling [PDF]
, 2013 This paper considers the problem of estimating the population mean in two-stage sampling with unequal first stage unit (fsu) for ratio, product and regression estimators when the population mean of the auxiliary variable is not known in advance.
Singh, Ravendra +3 more
core
Mixed model prediction and small area estimation
Benchmarking, borrowing strength, design-consistency, mean squared errors, empirical Bayes, EBLUP, generalized linear mixed models, higher order asymptotics, resampling methods, sample surveys, variance components, 62C12, 62C25, 62G09, 62D05, 62F11 ...
P. Lahiri, Jiming Jiang
core +1 more source
Constructing efficient strata boundaries in stratified sampling using survey cost. [PDF]
Heliyon, 2023 Reddy KG, Khan MGM.
europepmc +1 more source
Ratio-cum-product Type Estimators for Rare and Hidden Clustered Population. [PDF]
Sankhya B (2008), 2023 Singh R, Mishra R.
europepmc +1 more source
Extension of Fill's perfect rejection sampling algorithm to general chains
, 1999 By developing and applying a broad framework for rejection sampling using auxiliary randomness, we provide an extension of the perfect sampling algorithm of Fill (1998) to general chains on quite general state spaces, and describe how use of bounding ...
Motoya Machida +3 more
core
Extension of Fill's perfect rejection sampling algorithm to general chains (Extended Abstract)
, 1999 . We provide an extension of the perfect sampling algorithm of Fill (1998) to general chains, and describe how use of bounding processes can ease computational burden. Along the way, we unearth a simple connection between the Coupling From The Past (CFTP)
Motoya Machida +3 more
core