Spline Regression in the Estimation of the Finite Population Total
Joseph Kipyegon Cheruiyot
Issue:
Volume 3, Issue 5, October 2015
Pages:
214-224
Received:
10 August 2015
Accepted:
20 August 2015
Published:
2 September 2015
Abstract: This study sought to estimate finite population total using Spline regression function. It compared the Spline regression with Sample Mean estimator, design-based and model - based estimators. To measure the performance of each estimator, the study considered average bias, the efficiency by use of the mean square error and the robustness using the rate change of efficiency. In this research, five populations were used. Three of them were simulated according to the following models: linear homoscedastic, quadratic homoscedastic and linear heteroscedastic and two natural populations. The performances of the five estimators were studied under the five populations. The sudy found that Sample Mean(SM), Horvitz-Thompson (HT) and Ratio (R) estimators are not robust while Nadaraya-Watson(NW) and Periodic Spline(PS) are robust when linearity and homoscedasticity of the population structure are violated.
Abstract: This study sought to estimate finite population total using Spline regression function. It compared the Spline regression with Sample Mean estimator, design-based and model - based estimators. To measure the performance of each estimator, the study considered average bias, the efficiency by use of the mean square error and the robustness using the ...
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Application of Logistic Regression Model in an Epidemiological Study
Renhao Jin,
Fang Yan,
Jie Zhu
Issue:
Volume 3, Issue 5, October 2015
Pages:
225-229
Received:
13 July 2015
Accepted:
22 July 2015
Published:
17 September 2015
Abstract: This paper use the logistic regression model to an epidemiological study, i.e. bovine tuberculosis (bTB) occurrence in cattle herds, together with well-established risk factors in the area known as West Wicklow, in the east of Ireland. The binary target variable is whether the herd is in the restricted status, which is defined by whether any bTB reactor is detected in the herd. With the stepwise variables selection procedure, a final logistical regression model is found to adequately describe the data. Herd bTB incidence was positively associated with annual total rainfall, herd size and a herd bTB history in the previous three years, and presence /absence of commonage.
Abstract: This paper use the logistic regression model to an epidemiological study, i.e. bovine tuberculosis (bTB) occurrence in cattle herds, together with well-established risk factors in the area known as West Wicklow, in the east of Ireland. The binary target variable is whether the herd is in the restricted status, which is defined by whether any bTB re...
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Selection of the Samples with Probability Proportional to Size
Maskurul Alam,
Sharmin Akter Sumy,
Yasin Ali Parh
Issue:
Volume 3, Issue 5, October 2015
Pages:
230-233
Received:
26 August 2015
Accepted:
6 September 2015
Published:
22 September 2015
Abstract: It is manifested to all that sample size varies from unit to unit. It goes without saying that large units contain more apropos information than the smaller units. So if the unit size is larger then there is a greater possibility to choose sample from the large unit than smaller one. It actually means the probability of selecting a unit is positively proportional to its sizes. The selection of unit is done corresponding to choose a number at random from the totality of numbers associated. My main aim is to prefer a method of selecting units on the basis of its size.
Abstract: It is manifested to all that sample size varies from unit to unit. It goes without saying that large units contain more apropos information than the smaller units. So if the unit size is larger then there is a greater possibility to choose sample from the large unit than smaller one. It actually means the probability of selecting a unit is positive...
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