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complex sampling

Bootstrap inference for the finite population total under complex sampling designs

Bootstrap inference for the finite population total under complex sampling designs

... the sampling distribution of the design-based estimator under some popular sampling designs, including Poisson sam- pling, simple random sampling (SRS) and probability-proportional-to-size (PPS) ...

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Estimating models for panel survey data under complex sampling

Estimating models for panel survey data under complex sampling

... Complex designs are often used to select the sample which is followed over time in a panel survey. We consider some parametric models for panel data and discuss methods of estimating the model parameters which ...

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A Direct Bootstrap Method for Complex Sampling Designs From a Finite Population

A Direct Bootstrap Method for Complex Sampling Designs From a Finite Population

... The simulations show that the classical bootstrap with re- placement is not appropriate under unequal probability sam- pling without replacement, or if the sample size is random. For simple random sampling without ...

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Empirical likelihood based inference under complex sampling designs

Empirical likelihood based inference under complex sampling designs

... The proposed approached can be generalised in numerous ways. Berger & De La Riva Torres [3] proposed a penalised empirical likelihood function to accommodate large sam- pling fraction. They also show how unit ...

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Small area estimation methods under complex sampling designs

Small area estimation methods under complex sampling designs

... random sampling without replacement, informative sampling and presence of outliers in the ...the sampling design is ...informative sampling or severe outliers in large ...

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Complex sampling designs for the Customer Satisfaction Index estimation

Complex sampling designs for the Customer Satisfaction Index estimation

... From the three artificial populations, 2,000 samples of size n = 50, 100 and 200 were drawn both by simple random sampling with replacement and without re- placement. Each simulated sample was used to start the ...

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Nonparametric regression estimation under complex sampling designs

Nonparametric regression estimation under complex sampling designs

... Breidt and Opsomer (2000) consider nonparametric models for a working model £ in a model-assisted framework to improve the design properties of estimators, and the[r] ...

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Variance estimation for a low income proportion

Variance estimation for a low income proportion

... Proportions below a given fraction of a quantile of an income distribution are often estimated from survey data in poverty comparisons. We consider the estimation of the variance of such a proportion, estimated from ...

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Measures of precision for dissimilarity based multivariate analysis of ecological communities

Measures of precision for dissimilarity based multivariate analysis of ecological communities

... replicate sampling unit (poten- tially comprised of a number of pooled sub-samples) has been defined, we ask: ‘How many replicates are needed to suffi- ciently characterise the community being sampled with rea- ...

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Sampling Probability and Inference

Sampling Probability and Inference

... the sampling error, which is the portion of error in the estimates which is due to the fact that only a sub-set of the population is ...probability sampling is simple random sampling, where all ...

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Testing and evaluating non extractive sampling platforms to assess deep water rocky reef ecosystems on the continental shelf

Testing and evaluating non extractive sampling platforms to assess deep water rocky reef ecosystems on the continental shelf

... extractive sampling methods, such as netting and trawling, to assess benthic species diversity, size and abundance are unable to sample complex hard substrates, ...non-extractive sampling platforms, ...

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Performance of Flow-based Anomaly Detection in Sampled Traffic

Performance of Flow-based Anomaly Detection in Sampled Traffic

... use sampling to manage the high volume of flow traffic. Sampling methods negatively affect the accuracy of anomaly ...of sampling on flow-based anomaly ...

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HOW PROBABILITY SAMPLING DIFFERENTIATE WITH NONPROBABILITY SAMPLING

HOW PROBABILITY SAMPLING DIFFERENTIATE WITH NONPROBABILITY SAMPLING

... the sampling were to be repeated many times, the expected value of the results from the repeated samples would be the same as the result we would get if we surveyed the whole ...

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Quantitative proteomics signature profiling based on network contextualization

Quantitative proteomics signature profiling based on network contextualization

... each complex is fairly stable, and therefore, even across random samplings, are consistently ...various sampling sizes (4, 6 and 8), qPSP consistently reported more significant complexes than t-test ...

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Variance approximation under balanced sampling

Variance approximation under balanced sampling

... balanced sampling in several projects has dramatically improved eDciency, allowing the reduction of the variance from 20% to 90% comparatively to simple random sampling in some cases (see for instance ...

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Action classification using a discriminative non parametric hidden Markov model

Action classification using a discriminative non parametric hidden Markov model

... slice sampling, an auxiliary variable ~ [0, ( )] is drawn from a likelihood function using the current state ...slice sampling [7] provides a much more efficient way of proposing new states even for high ...

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RPS. Sanitary sampling valves SAMPLING

RPS. Sanitary sampling valves SAMPLING

... Foro di flussaggio - ∅ 3 Flushing orifice 45° Vite di riferimento Locking screw Dimensioni in mm All dimensions in mm 3/4" Clamp 3/4" Clamp Butt Weld 1/8" BSPT Tappo in silic[r] ...

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Representation of complex probabilities and complex Gibbs sampling

Representation of complex probabilities and complex Gibbs sampling

... Abstract. Complex weights appear in Physics which are beyond a straightforward im- portance sampling treatment, as required in Monte Carlo ...The complex Langevin approach amounts to effectively ...

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Some Multi Convex Programming Problems Arising  in Multivariate Sampling

Some Multi Convex Programming Problems Arising in Multivariate Sampling

... [8] Optimum Allocation in Two-stage and Stratified Two-stage Sampling for Multivariate Surveys by M.G.M. Khan, Munish A. Chand, and Nesar Ahmad School of Computing, Information and Mathematical Sciences Faculty ...

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Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci

Sampling strategies for accurate computational inferences of gametic phase across highly polymorphic major histocompatibility complex loci

... Histocompatibility Complex (MHC) have become very popular molecular markers among evolutionary biologists because of their traditional consideration as ‘good genes’ involved in patho- gen resistance and sexual ...

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