Now showing items 1-8 of 8

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    A study of controlled sampling with varying probabilities without replacement 

    Wimon Sonchaem; Prachoom Suwattee, advisor (National Institute of Development Administration, 2001)
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    Estimation of regression coefficients with outliers 

    Pimpan Amphanthong; Prachoom Suwattee, advisor (National Institute of Development Administration, 2009)

    In linear models, the ordinary least squares estimators of have always turned out to be the best linear unbiased estimates. When the sample data contain outliers, the outliers may have a considerable effect on the least-squares estimates of , and an alternative approach to the problem is needed to obtain a better fit of the model or more precise estimates of . In this study, new weights were constructed for the sample data from two new influence functions and applied in the estimation of regression coefficients with outliers. Two sets of ...
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    Estimators in finite population sampling on successive occasions 

    Bongkoj Wibultananun; Prachoom Suwattee, advisor (National Institute of Development Administration, 2006)
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    Management and development of labour in Thai aviation industry 

    Watana Manon; Prachoom Suwattee, advisor (National Institute of Development Administration, 2010)

    The objectives of this research are to study the current situation of management and development of labour in the Thai aviation industry and to present the guidelines for competency increasing of employees especially those working in the airlines, at the airport and at the site of air cargo. The target population in this study is employees in Thai Airways International Public Company Limited, Airports of Thailand Public Company Limited and Bangkok Flight Services Company Limited. Primary data was collected from 585 samples employed in these three ...
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    Model-assisted estimation in inverse sampling 

    Sureeporn Sungsuwan; Prachoom Suwattee, advisor (National Institute of Development Administration, 2010)

    Inverse sampling is a method of sampling which requires the continued drawing of units until certain specified conditions depending on the results of those draws have been fulfilled, and there are many studies on the estimation of inverse simple random sampling under a design-based approach. In this study, a modelassisted approach is used to estimate the parameters and the statistical properties of the estimators were evaluated under design-based inference. The main purpose of this dissertation is to propose estimators of the population total, ...
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    Probability density estimation using new kernel functions 

    Manachai Rodchuen; Prachoom Suwattee, advisor (National Institute of Development Administration, 2010)

    This dissertation propose two new kernel functions to estimate a density unction with small biases and errors .The errors of the estimats are measured using mean squared error (MSEf (f(x,X ))), mean integrated squared error (MISE(f) and asymptotic mean integrated squared error (AMISE(f) ), and The estimates of these error measures are also given .The AMISE0(f) of the density estimates are compared to the kernel density estimates for the uniform, Epanechnikov and Gaussian kernel functions. One kernel function is derived by minimizing the sum of ...
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    Stratified inverse sampling 

    Prayad Sangngam; Prachoom Suwattee, advisor (National Institute of Development Administration, 2010)

    This dissertation is concerned with stratified inverse sampling and four different sampling schemes are considered, namely inverse random sampling with replacement, inverse random sampling without replacement, inverse PPS sampling with replacement and inverse PPS sampling without replacement. Unbiased estimators of the mean of a study variable in the whole population, the number of units in a class of interest and the prevalence of a characteristic are given together with their unbiased variance estimators. Estimation of the mean per unit in the ...
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    Testing means of several Pareto distributions 

    Lakhana Watthanacheewakul; Prachoom Suwattee, advisor (National Institute of Development Administration, 2007)