The higher education environment in Pakistan has become very aggressive and universities have to struggle for recruiting highly intellectual students. The students have become consumerists due to increasing fees of higher education institutes. The primary focus of this study was to uncover the factors that students deem vital related to their choice of university and desired courses. Undergradu...

Through the monitoring network for cultivated land quality in county area, distribution and changing trend of the quality should be reflected. Besides, the quality of non-sampled locations should also be estimated with the data of sampling points. Due to the correlation among spatial samples, traditional methods such as simple random sampling, stratified sampling and systematic sampling are ine...

Recently, Zhou and Robles-Kelly proposed a novel quasi-random sampling (QuaRS) approach for CBIR [4]. This approach uses EM algorithm to organize the images in the database into compact clusters, then compares the similarity between the query and the clustered images to govern the sampling process within clusters. The sampling can be viewed as a stratified sampling one which is random at the cl...

The following techniques for uncertainty and sensitivity analysis are briefly summarized: Monte Carlo analysis, differential analysis, response surface methodology, Fourier amplitude sensitivity test, Sobol’ variance decomposition, and fast probability integration. Desirable features of Monte Carlo analysis in conjunction with Latin hypercube sampling are described in discussions of the followi...

This paper solves a specialized regression problem to obtain sampling probabilities for records in databases. The goal is to sample a small set of records over which evaluating aggregate queries can be done both efficiently and accurately. We provide a principled and provable solution for this problem; it is parameterless and requires no data insights. Unlike standard regression problems, the l...

High accuracy in cancer prediction is important to improve the quality of the treatment and to improve the rate of survivability of patients. As the data volume is increasing rapidly in the healthcare research, the analytical challenge exists in double. The use of effective sampling technique in classification algorithms always yields good prediction accuracy. The SEER public use cancer databas...

In these notes we discuss the efficiency of a Monte-Carlo estimator. This naturally leads to the search for more efficient estimators and towards this end we describe some simple variance reduction techniques. In particular, we describe common random numbers, control variates, antithetic Variates and conditional Monte-Carlo, all of which are designed to reduce the variance of our Monte-Carlo es...

In this paper, we propose a new quantitative randomized response model based on Mangat and Singh [7] two-stage randomized response model. We derive the estimator of the sensitive variable mean, and show that our method is more efficient than other randomized response models suggested by Greenberg et al. [3] and Gupta et al. [4] estimators.

This paper presents the conditioned Latin hypercube as a sampling strategy of an area with prior information represented as exhaustive ancillary data. Latin hypercube sampling (LHS) is a stratified random procedure that provides an efficient way of sampling variables from their multivariate distributions. It provides a full coverage of the range of each variable by maximally stratifying the mar...

A new efficient technique to impose the statistical correlation when using the Monte Carlo type method for the statistical analysis of computational problems is proposed. The technique is based on the stochastic optimization method called Simulated Annealing. The comparison with other techniques presently used and intensive numerical testing showed the superiority and robustness of the method. ...