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A new concept for tuning design weights in survey sampling : by Sarjinder Singh, Stephen A. Sedory, Maria Del Mar Rueda,

By Sarjinder Singh, Stephen A. Sedory, Maria Del Mar Rueda, Antonio Arcos, Raghunath Arnab

A New notion for Tuning layout Weights in Survey Sampling: Jackknifing in thought and Practice introduces the recent thought of tuning layout weights in survey sampling via featuring 3 strategies: calibration, jackknifing, and imputing the place wanted. This new method permits survey statisticians to strengthen statistical software program for interpreting facts in a extra accurately and pleasant method than with latest innovations.

  • Explains how one can calibrate layout weights in survey sampling
  • Discusses how Jackknifing is required in layout weights in survey sampling
  • Describes how layout weights are imputed in survey sampling

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We remind the reader that the first bridge between the traditional linear regression and traditional greg estimators was built by Singh (2003). 52) is a kind of Beale (1962) estimator of the regression coefficient. 47) either to the exact product estimator or to the exact ¨ traditional generalized regression (greg) estimator due to Deville À and Sa Á rndal (1992). R. 2. 2. 22). Note that the modified greg estimator is far from the traditional greg estimator. Therefore the estimator yTunedðcsÞ is recommended so long as one is concerned about estimating the weight of a pumpkin using small samples.

2 Notation Let yi and xi, i ¼ 1, 2, …,N be the values of the study variable and auxiliary variable, respectively, of the ith unit in the population Ω. 2) i¼1 of the auxiliary variable is known. Let (yi, xi), i ¼ 1,2, …, n be the values of the study variable and auxiliary variable of the ith unit in the sample s drawn using a simple random sampling (SRS) scheme. 4) i2s be the sample means for the study variable and the auxiliary variable, respectively. A New Concept for Tuning Design Weights in Survey Sampling.

88) where r ! 90) j¼1 nyn À yj has its usual meaning. Determine c such that μ ^rðJackÞ can be used nÀ1 as a jackknife estimator of the rth central moment μr. Hint: Finucan, Galbraith, and Stone (1974). 10 Consider a farmer growing organic pumpkins and chemically treated pumpkins. A buyer took a random sample of n organic pumpkin and another random sample of m treated pumpkins, both using SRSWR schemes. Let yn and ym be the sample mean weights of the first and second samples, respectively. 91) be the pooled estimator of the pooled population mean weight, Y, of both types of pumpkins on the farm.

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