Systematic sampling is a commonly used technique due to its simplicity and ease of implementation. The drawback of this simplicity is that it is not possible to estimate the design variance without bias. There are several ways to circumvent this problem. One method is to suppose that the variable of interest has a random order in the population, so the sample variance of simple random sampling ...

Because of high costs or complex logistics, scientific populations cannot be measured entirely and must be sampled. Accepted scientific practice holds that sample selection be based on statistical principles to assure objectivity when estimating totals and variances. Probability sampling--obtaining samples with known probabilities--is the only method that assures these results. However, probabi...

Gibbs sampling is a Markov Chain Monte Carlo sampling technique that iteratively samples variables from their conditional distributions. There are two common scan orders for the variables: random scan and systematic scan. Due to the benefits of locality in hardware, systematic scan is commonly used, even though most statistical guarantees are only for random scan. While it has been conjectured ...

primary information about different methods of vegetation sampling is important to researchers to decide about their sampling. in this study we applied five distance methods (closest individual, nearest neighbor, random pairs, point-centered quarter and angle orderd) to estimate plant density in three vegetation types including artemisia sieberi, juncus littoralis and punica granatum in mazanda...